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Sample records for neural interface device

  1. Optimizing the performance of neural interface devices with hybrid poly(3,4-ethylene dioxythiophene) (PEDOT)

    Science.gov (United States)

    Kuo, Chin-chen

    This thesis describes methods for improving the performance of poly(3,4-ethylenedioxythiophene) (PEDOT) as a direct neural interfacing material. The chronic foreign body response is always a challenge for implanted bionic devices. After long-term implantation (typically 2-4 weeks), insulating glial scars form around the devices, inhibiting signal transmission, which ultimately leads to device failure. The mechanical mismatch at the device-tissue interface is one of the issues that has been associated with chronic foreign body response. Another challenge for using PEDOT as a neural interface material is its mechanical failure after implantation. We observed cracking and delamination of PEDOT coatings on devices after extended implantations. In the first part of this thesis, we present a novel method for directly measuring the mechanical properties of a PEDOT thin film. Before investigating methods to improve the mechanical behavior of PEDOT, a comprehensive understanding of the mechanical properties of PEDOT thin film is required. A PEDOT thin film was machined into a dog-bone shape specimen with a dual beam FIB-SEM. With an OmniProbe, this PEDOT specimen could be attached onto a force sensor, while the other side was attached to OmniProbe. By moving the OmniProbe, the specimen could be deformed in tension, and a force sensor recorded the applied load on the sample simultaneously. Mechanical tensile tests were conducted in the FIB-SEM chamber along with in situ observation. With precise force measurement from the force sensor and the corresponding high resolution SEM images, we were able to convert the data to a stress-strain curve for further analysis. By analyzing these stress-strain curves, we were able to obtain information about PEDOT including the Young's modulus, strength of failure, strain to failure, and toughness (energy to failure). This information should be useful for future material selection and molecular design for specific applications. The second

  2. Micro- and Nanotechnologies for Optical Neural Interfaces

    Science.gov (United States)

    Pisanello, Ferruccio; Sileo, Leonardo; De Vittorio, Massimo

    2016-01-01

    In last decade, the possibility to optically interface with the mammalian brain in vivo has allowed unprecedented investigation of functional connectivity of neural circuitry. Together with new genetic and molecular techniques to optically trigger and monitor neural activity, a new generation of optical neural interfaces is being developed, mainly thanks to the exploitation of both bottom-up and top-down nanofabrication approaches. This review highlights the role of nanotechnologies for optical neural interfaces, with particular emphasis on new devices and methodologies for optogenetic control of neural activity and unconventional methods for detection and triggering of action potentials using optically-active colloidal nanoparticles. PMID:27013939

  3. Investigation of amorphous silicon carbide:hydrogen and Parylene-C thin films as encapsulation materials for neural interface devices

    Science.gov (United States)

    Hsu, Jui-Mei

    Neural interface devices have been developed for neuroscience and neuroprosthetics applications to record and stimulate nerve signals. Chronic use of these devices is prevented by their lack of long-term stability due to device failure or immune system responses. Fully integrated, wireless, silicon-based neural interface (INI) devices are being developed to address the main failure modes by eliminating the wired connections. Furthermore, chronic stable, conformal, hermetic, biocompatible, and electrically insulating coating materials that sustain chronic implantation and guarantee stable recording or stimulation are needed. Even though a large selection of materials has been proposed and tested for this purpose, to date, no encapsulation material or coating process presented in scientific literature has been thoroughly characterized or qualified as long-term hermetic encapsulation for silicon micro-electrode arrays. In this work, hydrogenated amorphous silicon carbide (a-SiCx:H) and Parylene-C films were investigated as encapsulation materials. The deposition parameters and corresponding film properties were explored and correlated with the encapsulation characteristics. The bond configuration of the deposited a-SiCx:H films was analyzed by FT-IR in order to develop films with strong chemical structure and low defect density. Film properties were optimized based on the bond configuration and process temperature requirements ( 12 months). Oxygen plasma etching processes necessary for deinsulation of the electrode tips and the etching performance on the Parylene-C were investigated, and the relationship between tip exposure and electrode impedance was studied. Excellent encapsulation properties of Parylene-C were demonstrated. The correlation between process parameters and Parylene-C properties was investigated, including surface topography, adhesion, and crystallinity.

  4. Virtual reality interface devices in the reorganization of neural networks in the brain of patients with neurological diseases.

    Science.gov (United States)

    Gatica-Rojas, Valeska; Méndez-Rebolledo, Guillermo

    2014-04-15

    Two key characteristics of all virtual reality applications are interaction and immersion. Systemic interaction is achieved through a variety of multisensory channels (hearing, sight, touch, and smell), permitting the user to interact with the virtual world in real time. Immersion is the degree to which a person can feel wrapped in the virtual world through a defined interface. Virtual reality interface devices such as the Nintendo® Wii and its peripheral nunchuks-balance board, head mounted displays and joystick allow interaction and immersion in unreal environments created from computer software. Virtual environments are highly interactive, generating great activation of visual, vestibular and proprioceptive systems during the execution of a video game. In addition, they are entertaining and safe for the user. Recently, incorporating therapeutic purposes in virtual reality interface devices has allowed them to be used for the rehabilitation of neurological patients, e.g., balance training in older adults and dynamic stability in healthy participants. The improvements observed in neurological diseases (chronic stroke and cerebral palsy) have been shown by changes in the reorganization of neural networks in patients' brain, along with better hand function and other skills, contributing to their quality of life. The data generated by such studies could substantially contribute to physical rehabilitation strategies.

  5. Virtual reality interface devices in the reorganization of neural networks in the brain of patients with neurological diseases

    Science.gov (United States)

    Gatica-Rojas, Valeska; Méndez-Rebolledo, Guillermo

    2014-01-01

    Two key characteristics of all virtual reality applications are interaction and immersion. Systemic interaction is achieved through a variety of multisensory channels (hearing, sight, touch, and smell), permitting the user to interact with the virtual world in real time. Immersion is the degree to which a person can feel wrapped in the virtual world through a defined interface. Virtual reality interface devices such as the Nintendo® Wii and its peripheral nunchuks-balance board, head mounted displays and joystick allow interaction and immersion in unreal environments created from computer software. Virtual environments are highly interactive, generating great activation of visual, vestibular and proprioceptive systems during the execution of a video game. In addition, they are entertaining and safe for the user. Recently, incorporating therapeutic purposes in virtual reality interface devices has allowed them to be used for the rehabilitation of neurological patients, e.g., balance training in older adults and dynamic stability in healthy participants. The improvements observed in neurological diseases (chronic stroke and cerebral palsy) have been shown by changes in the reorganization of neural networks in patients’ brain, along with better hand function and other skills, contributing to their quality of life. The data generated by such studies could substantially contribute to physical rehabilitation strategies. PMID:25206907

  6. Conducting Polymers for Neural Prosthetic and Neural Interface Applications

    Science.gov (United States)

    2015-01-01

    Neural interfacing devices are an artificial mechanism for restoring or supplementing the function of the nervous system lost as a result of injury or disease. Conducting polymers (CPs) are gaining significant attention due to their capacity to meet the performance criteria of a number of neuronal therapies including recording and stimulating neural activity, the regeneration of neural tissue and the delivery of bioactive molecules for mediating device-tissue interactions. CPs form a flexible platform technology that enables the development of tailored materials for a range of neuronal diagnostic and treatment therapies. In this review the application of CPs for neural prostheses and other neural interfacing devices are discussed, with a specific focus on neural recording, neural stimulation, neural regeneration, and therapeutic drug delivery. PMID:26414302

  7. Virtual reality interface devices in the reorganization of neural networks in the brain of patients with neurological diseases

    OpenAIRE

    Gatica-Rojas, Valeska; Méndez-Rebolledo, Guillermo

    2014-01-01

    Two key characteristics of all virtual reality applications are interaction and immersion. Systemic interaction is achieved through a variety of multisensory channels (hearing, sight, touch, and smell), permitting the user to interact with the virtual world in real time. Immersion is the degree to which a person can feel wrapped in the virtual world through a defined interface. Virtual reality interface devices such as the Nintendo® Wii and its peripheral nunchuks-balance board, head mounted ...

  8. EDITORIAL: Focus on the neural interface Focus on the neural interface

    Science.gov (United States)

    Durand, Dominique M.

    2009-10-01

    The possibility of an effective connection between neural tissue and computers has inspired scientists and engineers to develop new ways of controlling and obtaining information from the nervous system. These applications range from `brain hacking' to neural control of artificial limbs with brain signals. Notwithstanding the significant advances in neural prosthetics in the last few decades and the success of some stimulation devices such as cochlear prosthesis, neurotechnology remains below its potential for restoring neural function in patients with nervous system disorders. One of the reasons for this limited impact can be found at the neural interface and close attention to the integration between electrodes and tissue should improve the possibility of successful outcomes. The neural interfaces research community consists of investigators working in areas such as deep brain stimulation, functional neuromuscular/electrical stimulation, auditory prostheses, cortical prostheses, neuromodulation, microelectrode array technology, brain-computer/machine interfaces. Following the success of previous neuroprostheses and neural interfaces workshops, funding (from NIH) was obtained to establish a biennial conference in the area of neural interfaces. The first Neural Interfaces Conference took place in Cleveland, OH in 2008 and several topics from this conference have been selected for publication in this special section of the Journal of Neural Engineering. Three `perspectives' review the areas of neural regeneration (Corredor and Goldberg), cochlear implants (O'Leary et al) and neural prostheses (Anderson). Seven articles focus on various aspects of neural interfacing. One of the most popular of these areas is the field of brain-computer interfaces. Fraser et al, report on a method to generate robust control with simple signal processing algorithms of signals obtained with electrodes implanted in the brain. One problem with implanted electrode arrays, however, is that

  9. Flexible and Organic Neural Interfaces: A Review

    Directory of Open Access Journals (Sweden)

    Nicolò Lago

    2017-12-01

    Full Text Available Neural interfaces are a fundamental tool to interact with neurons and to study neural networks by transducing cellular signals into electronics signals and vice versa. State-of-the-art technologies allow both in vivo and in vitro recording of neural activity. However, they are mainly made of stiff inorganic materials that can limit the long-term stability of the implant due to infection and/or glial scars formation. In the last decade, organic electronics is digging its way in the field of bioelectronics and researchers started to develop neural interfaces based on organic semiconductors, creating more flexible and conformable neural interfaces that can be intrinsically biocompatible. In this manuscript, we are going to review the latest achievements in flexible and organic neural interfaces for the recording of neuronal activity.

  10. Early interfaced neural activity from chronic amputated nerves

    Directory of Open Access Journals (Sweden)

    Kshitija Garde

    2009-05-01

    Full Text Available Direct interfacing of transected peripheral nerves with advanced robotic prosthetic devices has been proposed as a strategy for achieving natural motor control and sensory perception of such bionic substitutes, thus fully functionally replacing missing limbs in amputees. Multi-electrode arrays placed in the brain and peripheral nerves have been used successfully to convey neural control of prosthetic devices to the user. However, reactive gliosis, micro hemorrhages, axonopathy and excessive inflammation, currently limit their long-term use. Here we demonstrate that enticement of peripheral nerve regeneration through a non-obstructive multi-electrode array, after either acute or chronic nerve amputation, offers a viable alternative to obtain early neural recordings and to enhance long-term interfacing of nerve activity. Non restrictive electrode arrays placed in the path of regenerating nerve fibers allowed the recording of action potentials as early as 8 days post-implantation with high signal-to-noise ratio, as long as 3 months in some animals, and with minimal inflammation at the nerve tissue-metal electrode interface. Our findings suggest that regenerative on-dependent multi-electrode arrays of open design allow the early and stable interfacing of neural activity from amputated peripheral nerves and might contribute towards conveying full neural control and sensory feedback to users of robotic prosthetic devices. .

  11. Development of bioactive conducting polymers for neural interfaces.

    Science.gov (United States)

    Poole-Warren, Laura; Lovell, Nigel; Baek, Sungchul; Green, Rylie

    2010-01-01

    Bioelectrodes for neural recording and neurostimulation are an integral component of a number of neuroprosthetic devices, including the commercially available cochlear implant, and developmental devices, such as the bionic eye and brain-machine interfaces. Current electrode designs limit the application of such devices owing to suboptimal material properties that lead to minimal interaction with the target neural tissue and the formation of fibrotic capsules. In designing an ideal bioelectrode, a number of design criteria must be considered with respect to physical, mechanical, electrical and biological properties. Conducting polymers have the potential to address the synergistic interaction of these properties and show promise as superior coatings for next-generation electrodes in implant devices.

  12. Shaping the dynamics of a bidirectional neural interface.

    Directory of Open Access Journals (Sweden)

    Alessandro Vato

    Full Text Available Progress in decoding neural signals has enabled the development of interfaces that translate cortical brain activities into commands for operating robotic arms and other devices. The electrical stimulation of sensory areas provides a means to create artificial sensory information about the state of a device. Taken together, neural activity recording and microstimulation techniques allow us to embed a portion of the central nervous system within a closed-loop system, whose behavior emerges from the combined dynamical properties of its neural and artificial components. In this study we asked if it is possible to concurrently regulate this bidirectional brain-machine interaction so as to shape a desired dynamical behavior of the combined system. To this end, we followed a well-known biological pathway. In vertebrates, the communications between brain and limb mechanics are mediated by the spinal cord, which combines brain instructions with sensory information and organizes coordinated patterns of muscle forces driving the limbs along dynamically stable trajectories. We report the creation and testing of the first neural interface that emulates this sensory-motor interaction. The interface organizes a bidirectional communication between sensory and motor areas of the brain of anaesthetized rats and an external dynamical object with programmable properties. The system includes (a a motor interface decoding signals from a motor cortical area, and (b a sensory interface encoding the state of the external object into electrical stimuli to a somatosensory area. The interactions between brain activities and the state of the external object generate a family of trajectories converging upon a selected equilibrium point from arbitrary starting locations. Thus, the bidirectional interface establishes the possibility to specify not only a particular movement trajectory but an entire family of motions, which includes the prescribed reactions to unexpected

  13. Shaping the Dynamics of a Bidirectional Neural Interface

    Science.gov (United States)

    Vato, Alessandro; Semprini, Marianna; Maggiolini, Emma; Szymanski, Francois D.; Fadiga, Luciano; Panzeri, Stefano; Mussa-Ivaldi, Ferdinando A.

    2012-01-01

    Progress in decoding neural signals has enabled the development of interfaces that translate cortical brain activities into commands for operating robotic arms and other devices. The electrical stimulation of sensory areas provides a means to create artificial sensory information about the state of a device. Taken together, neural activity recording and microstimulation techniques allow us to embed a portion of the central nervous system within a closed-loop system, whose behavior emerges from the combined dynamical properties of its neural and artificial components. In this study we asked if it is possible to concurrently regulate this bidirectional brain-machine interaction so as to shape a desired dynamical behavior of the combined system. To this end, we followed a well-known biological pathway. In vertebrates, the communications between brain and limb mechanics are mediated by the spinal cord, which combines brain instructions with sensory information and organizes coordinated patterns of muscle forces driving the limbs along dynamically stable trajectories. We report the creation and testing of the first neural interface that emulates this sensory-motor interaction. The interface organizes a bidirectional communication between sensory and motor areas of the brain of anaesthetized rats and an external dynamical object with programmable properties. The system includes (a) a motor interface decoding signals from a motor cortical area, and (b) a sensory interface encoding the state of the external object into electrical stimuli to a somatosensory area. The interactions between brain activities and the state of the external object generate a family of trajectories converging upon a selected equilibrium point from arbitrary starting locations. Thus, the bidirectional interface establishes the possibility to specify not only a particular movement trajectory but an entire family of motions, which includes the prescribed reactions to unexpected perturbations. PMID

  14. Time to address the problems at the neural interface

    Science.gov (United States)

    Durand, Dominique M.; Ghovanloo, Maysam; Krames, Elliot

    2014-04-01

    interface with the CNS. In 2013, two symposia were held independently to discuss this problem: one was held at the International Neuromodulation Society's 11th World Congress in Berlin and supported by the International Neuromodulation Society1 and the other at the 6th International Neural Engineering conference in San Diego2 and was supported by the NSF. Clearly, the neuromodulation and the neural engineering communities are keen to solve this problem. Experts from the field were assembled to discuss the problems and potential solutions. Although many important points were raised, few emerged as key issues. (1) The ability to access remotely and reliably internal neural signals . Although some of the technological problems have already been solved, this ability to access neural signals is still a significant problem since reliable and robust transcutaneous telemetry systems with large numbers of signals, each with wide bandwidth, are not readily available to researchers. (2) A translation strategy taking basic research to the clinic . The lack of understanding of the biological response to implanted constructs and the inability to monitor the sites and match the mechanical properties of the probe to the neural tissue properties continue to be an unsolved problem. In addition, the low levels of collaboration among neuroscientists, clinicians, patients and other stakeholders throughout different phases of research and development were considered to be significant impediments to progress. (3) Fundamental tools development procedures for neural interfacing . There are many laboratories testing various devices with different sets of criteria, but there is no consensus on the failure modes. The reliability, robustness of metrics and testing standards for such devices have not been established, either in academia or in industry. To start addressing this problem, the FDA has established a laboratory to test the reliability of some neural devices. Although the discussion was mostly

  15. Neurosecurity: security and privacy for neural devices.

    Science.gov (United States)

    Denning, Tamara; Matsuoka, Yoky; Kohno, Tadayoshi

    2009-07-01

    An increasing number of neural implantable devices will become available in the near future due to advances in neural engineering. This discipline holds the potential to improve many patients' lives dramatically by offering improved-and in some cases entirely new-forms of rehabilitation for conditions ranging from missing limbs to degenerative cognitive diseases. The use of standard engineering practices, medical trials, and neuroethical evaluations during the design process can create systems that are safe and that follow ethical guidelines; unfortunately, none of these disciplines currently ensure that neural devices are robust against adversarial entities trying to exploit these devices to alter, block, or eavesdrop on neural signals. The authors define "neurosecurity"-a version of computer science security principles and methods applied to neural engineering-and discuss why neurosecurity should be a critical consideration in the design of future neural devices.

  16. Real-time decision fusion for multimodal neural prosthetic devices.

    Science.gov (United States)

    White, James Robert; Levy, Todd; Bishop, William; Beaty, James D

    2010-03-02

    The field of neural prosthetics aims to develop prosthetic limbs with a brain-computer interface (BCI) through which neural activity is decoded into movements. A natural extension of current research is the incorporation of neural activity from multiple modalities to more accurately estimate the user's intent. The challenge remains how to appropriately combine this information in real-time for a neural prosthetic device. Here we propose a framework based on decision fusion, i.e., fusing predictions from several single-modality decoders to produce a more accurate device state estimate. We examine two algorithms for continuous variable decision fusion: the Kalman filter and artificial neural networks (ANNs). Using simulated cortical neural spike signals, we implemented several successful individual neural decoding algorithms, and tested the capabilities of each fusion method in the context of decoding 2-dimensional endpoint trajectories of a neural prosthetic arm. Extensively testing these methods on random trajectories, we find that on average both the Kalman filter and ANNs successfully fuse the individual decoder estimates to produce more accurate predictions. Our results reveal that a fusion-based approach has the potential to improve prediction accuracy over individual decoders of varying quality, and we hope that this work will encourage multimodal neural prosthetics experiments in the future.

  17. Real-time decision fusion for multimodal neural prosthetic devices.

    Directory of Open Access Journals (Sweden)

    James Robert White

    Full Text Available BACKGROUND: The field of neural prosthetics aims to develop prosthetic limbs with a brain-computer interface (BCI through which neural activity is decoded into movements. A natural extension of current research is the incorporation of neural activity from multiple modalities to more accurately estimate the user's intent. The challenge remains how to appropriately combine this information in real-time for a neural prosthetic device. METHODOLOGY/PRINCIPAL FINDINGS: Here we propose a framework based on decision fusion, i.e., fusing predictions from several single-modality decoders to produce a more accurate device state estimate. We examine two algorithms for continuous variable decision fusion: the Kalman filter and artificial neural networks (ANNs. Using simulated cortical neural spike signals, we implemented several successful individual neural decoding algorithms, and tested the capabilities of each fusion method in the context of decoding 2-dimensional endpoint trajectories of a neural prosthetic arm. Extensively testing these methods on random trajectories, we find that on average both the Kalman filter and ANNs successfully fuse the individual decoder estimates to produce more accurate predictions. CONCLUSIONS: Our results reveal that a fusion-based approach has the potential to improve prediction accuracy over individual decoders of varying quality, and we hope that this work will encourage multimodal neural prosthetics experiments in the future.

  18. Flexible neural interfaces with integrated stiffening shank

    Energy Technology Data Exchange (ETDEWEB)

    Tooker, Angela C.; Felix, Sarah H.; Pannu, Satinderpall S.; Shah, Kedar G.; Sheth, Heeral; Tolosa, Vanessa

    2017-10-17

    A neural interface includes a first dielectric material having at least one first opening for a first electrical conducting material, a first electrical conducting material in the first opening, and at least one first interconnection trace electrical conducting material connected to the first electrical conducting material. A stiffening shank material is located adjacent the first dielectric material, the first electrical conducting material, and the first interconnection trace electrical conducting material.

  19. The conversational interface talking to smart devices

    CERN Document Server

    McTear, Michael; Griol, David

    2016-01-01

    This book provides a comprehensive introduction to the conversational interface, which is becoming the main mode of interaction with virtual personal assistants, smart devices, various types of wearables, and social robots. The book consists of four parts: Part I presents the background to conversational interfaces, examining past and present work on spoken language interaction with computers; Part II covers the various technologies that are required to build a conversational interface along with practical chapters and exercises using open source tools; Part III looks at interactions with smart devices, wearables, and robots, and then goes on to discusses the role of emotion and personality in the conversational interface; Part IV examines methods for evaluating conversational interfaces and discusses future directions. · Presents a comprehensive overview of the various technologies that underlie conversational user interfaces; · Combines descriptions of conversational user interface technologies with a gui...

  20. Vacuum-actuated percutaneous insertion/implantation tool for flexible neural probes and interfaces

    Energy Technology Data Exchange (ETDEWEB)

    Sheth, Heeral; Bennett, William J.; Pannu, Satinderpall S.; Tooker, Angela C.

    2017-03-07

    A flexible device insertion tool including an elongated stiffener with one or more suction ports, and a vacuum connector for interfacing the stiffener to a vacuum source, for attaching the flexible device such as a flexible neural probe to the stiffener during insertion by a suction force exerted through the suction ports to, and to release the flexible device by removing the suction force.

  1. Decoding Local Field Potentials for Neural Interfaces.

    Science.gov (United States)

    Jackson, Andrew; Hall, Thomas M

    2017-10-01

    The stability and frequency content of local field potentials (LFPs) offer key advantages for long-term, low-power neural interfaces. However, interpreting LFPs may require new signal processing techniques which should be informed by a scientific understanding of how these recordings arise from the coordinated activity of underlying neuronal populations. We review current approaches to decoding LFPs for brain-machine interface (BMI) applications, and suggest several directions for future research. To facilitate an improved understanding of the relationship between LFPs and spike activity, we share a dataset of multielectrode recordings from monkey motor cortex, and describe two unsupervised analysis methods we have explored for extracting a low-dimensional feature space that is amenable to biomimetic decoding and biofeedback training.

  2. A 2.1 μW/channel current-mode integrated neural recording interface

    NARCIS (Netherlands)

    Zjajo, A.; van Leuken, T.G.R.M.

    2016-01-01

    In this paper, we present a neural recording interface circuit for biomedical implantable devices, which includes low-noise signal amplification, band-pass filtering, and current-mode successive approximation A/D signal conversion. The integrated interface circuit is realized in a 65 nm CMOS

  3. Functional recordings from awake, behaving rodents through a microchannel based regenerative neural interface

    Science.gov (United States)

    Gore, Russell K.; Choi, Yoonsu; Bellamkonda, Ravi; English, Arthur

    2015-02-01

    Objective. Neural interface technologies could provide controlling connections between the nervous system and external technologies, such as limb prosthetics. The recording of efferent, motor potentials is a critical requirement for a peripheral neural interface, as these signals represent the user-generated neural output intended to drive external devices. Our objective was to evaluate structural and functional neural regeneration through a microchannel neural interface and to characterize potentials recorded from electrodes placed within the microchannels in awake and behaving animals. Approach. Female rats were implanted with muscle EMG electrodes and, following unilateral sciatic nerve transection, the cut nerve was repaired either across a microchannel neural interface or with end-to-end surgical repair. During a 13 week recovery period, direct muscle responses to nerve stimulation proximal to the transection were monitored weekly. In two rats repaired with the neural interface, four wire electrodes were embedded in the microchannels and recordings were obtained within microchannels during proximal stimulation experiments and treadmill locomotion. Main results. In these proof-of-principle experiments, we found that axons from cut nerves were capable of functional reinnervation of distal muscle targets, whether regenerating through a microchannel device or after direct end-to-end repair. Discrete stimulation-evoked and volitional potentials were recorded within interface microchannels in a small group of awake and behaving animals and their firing patterns correlated directly with intramuscular recordings during locomotion. Of 38 potentials extracted, 19 were identified as motor axons reinnervating tibialis anterior or soleus muscles using spike triggered averaging. Significance. These results are evidence for motor axon regeneration through microchannels and are the first report of in vivo recordings from regenerated motor axons within microchannels in a small

  4. Electronic device aspects of neural network memories

    Science.gov (United States)

    Lambe, J.; Moopenn, A.; Thakoor, A. P.

    1985-01-01

    The basic issues related to the electronic implementation of the neural network model (NNM) for content addressable memories are examined. A brief introduction to the principles of the NNM is followed by an analysis of the information storage of the neural network in the form of a binary connection matrix and the recall capability of such matrix memories based on a hardware simulation study. In addition, materials and device architecture issues involved in the future realization of such networks in VLSI-compatible ultrahigh-density memories are considered. A possible space application of such devices would be in the area of large-scale information storage without mechanical devices.

  5. Graphene in the Design and Engineering of Next-Generation Neural Interfaces.

    Science.gov (United States)

    Kostarelos, Kostas; Vincent, Melissa; Hebert, Clement; Garrido, Jose A

    2017-11-01

    Neural interfaces are becoming a powerful toolkit for clinical interventions requiring stimulation and/or recording of the electrical activity of the nervous system. Active implantable devices offer a promising approach for the treatment of various diseases affecting the central or peripheral nervous systems by electrically stimulating different neuronal structures. All currently used neural interface devices are designed to perform a single function: either record activity or electrically stimulate tissue. Because of their electrical and electrochemical performance and their suitability for integration into flexible devices, graphene-based materials constitute a versatile platform that could help address many of the current challenges in neural interface design. Here, how graphene and other 2D materials possess an array of properties that can enable enhanced functional capabilities for neural interfaces is illustrated. It is emphasized that the technological challenges are similar for all alternative types of materials used in the engineering of neural interface devices, each offering a unique set of advantages and limitations. Graphene and 2D materials can indeed play a commanding role in the efforts toward wider clinical adoption of bioelectronics and electroceuticals. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Alternate Interface Devices for the Physically Handicapped.

    Science.gov (United States)

    Burns, Monte B.

    Six interface devices which students with physical impairments may use when operating the Apple II computer are described along with advantages and disadvantages, and source (when appropriate). These are: the Time Delay Keyboard, Keyguard, Magic Keyboard, Presfax-100 Touch Key-Pad, Switches (single and multiple), and Optical Strip Printer. (MC)

  7. Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations.

    Science.gov (United States)

    Greenwald, Elliot; Masters, Matthew R; Thakor, Nitish V

    2016-01-01

    A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.

  8. ORGANIC ELECTRODE COATINGS FOR NEXT-GENERATION NEURAL INTERFACES

    Directory of Open Access Journals (Sweden)

    Ulises A Aregueta-Robles

    2014-05-01

    Full Text Available Traditional neuronal interfaces utilize metallic electrodes which in recent years have reached a plateau in terms of the ability to provide safe stimulation at high resolution or rather with high densities of microelectrodes with improved spatial selectivity. To achieve higher resolution it has become clear that reducing the size of electrodes is required to enable higher electrode counts from the implant device. The limitations of interfacing electrodes including low charge injection limits, mechanical mismatch and foreign body response can be addressed through the use of organic electrode coatings which typically provide a softer, more roughened surface to enable both improved charge transfer and lower mechanical mismatch with neural tissue. Coating electrodes with conductive polymers or carbon nanotubes offers a substantial increase in charge transfer area compared to conventional platinum electrodes. These organic conductors provide safe electrical stimulation of tissue while avoiding undesirable chemical reactions and cell damage. However, the mechanical properties of conductive polymers are not ideal, as they are quite brittle. Hydrogel polymers present a versatile coating option for electrodes as they can be chemically modified to provide a soft and conductive scaffold. However, the in vivo chronic inflammatory response of these conductive hydrogels remains unknown. A more recent approach proposes tissue engineering the electrode interface through the use of encapsulated neurons within hydrogel coatings. This approach may provide a method for activating tissue at the cellular scale, however several technological challenges must be addressed to demonstrate feasibility of this innovative idea. The review focuses on the various organic coatings which have been investigated to improve neural interface electrodes.

  9. Understanding and Design of Polymer Device Interfaces

    Energy Technology Data Exchange (ETDEWEB)

    Kahn, Antoine [Princeton Univ., NJ (United States)

    2015-10-26

    The research performed under grant DE-FG02-04ER46165 between May 2008 and April 2011 focused on the understanding and control of interfaces of organic semiconductors in general, and polymer interfaces more specifically. This work was a joined effort by three experimentalists and a theoretician. Emphasis was placed on the determination of the electronic structure of these interfaces, i.e. the relative energy position of molecular levels across these interfaces. From these electronic structures depend the injection, extraction and transport of charge carriers into, from and across, respectively, all (opto)electronic devices made of these semiconductors. A significant fraction of our work focused on ways to modify and optimize interfaces, for example via chemical doping of the semiconductors to reduce interface energy barriers or via deposition of ultra-thin work function-reducing polymer or self-assembled monolayers of dipolar molecules. Another significant fraction of our work was devoted to exploring alternate and unconventional interface formation methods, in particular the soft-contact lamination of both metal contacts and polymer overlayers on top of polymer films. These methods allowed us to better understand the impact of hot metal atom evaporation on a soft organic surface, as well as the key mechanisms that control the energetics of polymer/polymer heterojunctions. Finally, a significant fraction of the research was directed to understanding the electronic structure of buried polymer heterojunctions, in particular within donor/acceptor blends of interest in organic photovoltaic applications. The work supported by this grant resulted in 17 publications in some of the best peer-reviewed journals of the field, as well as numerous presentations at US and international conferences.

  10. 47 CFR 15.115 - TV interface devices, including cable system terminal devices.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false TV interface devices, including cable system... FREQUENCY DEVICES Unintentional Radiators § 15.115 TV interface devices, including cable system terminal devices. (a) Measurements of the radiated emissions of a TV interface device shall be conducted with the...

  11. An implantable wireless neural interface for recording cortical circuit dynamics in moving primates.

    Science.gov (United States)

    Borton, David A; Yin, Ming; Aceros, Juan; Nurmikko, Arto

    2013-04-01

    Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims and those living with severe neuromotor disease. Such systems must be chronically safe, durable and effective. We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based microelectrode array via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1 Hz to 7.8 kHz, 200× gain) and multiplexed by a custom application specific integrated circuit, digitized and then packaged for transmission. The neural data (24 Mbps) were transmitted by a wireless data link carried on a frequency-shift-key-modulated signal at 3.2 and 3.8 GHz to a receiver 1 m away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7 h continuous operation between recharge via an inductive transcutaneous wireless power link at 2 MHz. Device verification and early validation were performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight into how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile patient use, have the potential for wider diagnosis of

  12. Development and Evaluation of Micro-Electrocorticography Arrays for Neural Interfacing Applications

    Science.gov (United States)

    Schendel, Amelia Ann

    Neural interfaces have great promise for both electrophysiological research and therapeutic applications. Whether for the study of neural circuitry or for neural prosthetic or other therapeutic applications, micro-electrocorticography (micro-ECoG) arrays have proven extremely useful as neural interfacing devices. These devices strike a balance between invasiveness and signal resolution, an important step towards eventual human application. The objective of this research was to make design improvements to micro-ECoG devices to enhance both biocompatibility and device functionality. To best evaluate the effectiveness of these improvements, a cranial window imaging method for in vivo monitoring of the longitudinal tissue response post device implant was developed. Employment of this method provided valuable insight into the way tissue grows around micro-ECoG arrays after epidural implantation, spurring a study of the effects of substrate geometry on the meningeal tissue response. The results of the substrate footprint comparison suggest that a more open substrate geometry provides an easy path for the tissue to grow around to the top side of the device, whereas a solid device substrate encourages the tissue to thicken beneath the device, between the electrode sites and the brain. The formation of thick scar tissue between the recording electrode sites and the neural tissue is disadvantageous for long-term recorded signal quality, and thus future micro-ECoG device designs should incorporate open-architecture substrates for enhanced longitudinal in vivo function. In addition to investigating improvements for long-term device reliability, it was also desired to enhance the functionality of micro-ECoG devices for neural electrophysiology research applications. To achieve this goal, a completely transparent graphene-based device was fabricated for use with the cranial window imaging method and optogenetic techniques. The use of graphene as the conductive material provided

  13. Tactile Feedback for Above-Device Gesture Interfaces

    OpenAIRE

    Freeman, Euan; Brewster, Stephen; Lantz, Vuokko

    2014-01-01

    Above-device gesture interfaces let people interact in the space above mobile devices using hand and finger movements. For example, users could gesture over a mobile phone or wearable without having to use the touchscreen. We look at how above-device interfaces can also give feedback in the space over the device. Recent haptic and wearable technologies give new ways to provide tactile feedback while gesturing, letting touchless gesture interfaces give touch feedback. In this paper we take a f...

  14. Modality-specific axonal regeneration: toward selective regenerative neural interfaces.

    Science.gov (United States)

    Lotfi, Parisa; Garde, Kshitija; Chouhan, Amit K; Bengali, Ebrahim; Romero-Ortega, Mario I

    2011-01-01

    Regenerative peripheral nerve interfaces have been proposed as viable alternatives for the natural control of robotic prosthetic devices. However, sensory and motor axons at the neural interface are of mixed sub-modality types, which difficult the specific recording from motor axons and the eliciting of precise sensory modalities through selective stimulation. Here we evaluated the possibility of using type specific neurotrophins to preferentially entice the regeneration of defined axonal populations from transected peripheral nerves into separate compartments. Segregation of mixed sensory fibers from dorsal root ganglion neurons was evaluated in vitro by compartmentalized diffusion delivery of nerve growth factor (NGF) and neurotrophin-3 (NT-3), to preferentially entice the growth of TrkA+ nociceptive and TrkC+ proprioceptive subsets of sensory neurons, respectively. The average axon length in the NGF channel increased 2.5-fold compared to that in saline or NT-3, whereas the number of branches increased threefold in the NT-3 channels. These results were confirmed using a 3D "Y"-shaped in vitro assay showing that the arm containing NGF was able to entice a fivefold increase in axonal length of unbranched fibers. To address if such segregation can be enticed in vivo, a "Y"-shaped tubing was used to allow regeneration of the transected adult rat sciatic nerve into separate compartments filled with either NFG or NT-3. A significant increase in the number of CGRP+ pain fibers were attracted toward the sural nerve, while N-52+ large-diameter axons were observed in the tibial and NT-3 compartments. This study demonstrates the guided enrichment of sensory axons in specific regenerative chambers, and supports the notion that neurotrophic factors can be used to segregate sensory and perhaps motor axons in separate peripheral interfaces.

  15. NeuralWISP: A Wirelessly Powered Neural Interface With 1-m Range.

    Science.gov (United States)

    Yeager, D J; Holleman, J; Prasad, R; Smith, J R; Otis, B P

    2009-12-01

    We present the NeuralWISP, a wireless neural interface operating from far-field radio-frequency RF energy. The NeuralWISP is compatible with commercial RF identification readers and operates at a range up to 1 m. It includes a custom low-noise, low-power amplifier integrated circuit for processing the neural signal and an analog spike detection circuit for reducing digital computational requirements and communications bandwidth. Our system monitors the neural signal and periodically transmits the spike density in a user-programmable time window. The entire system draws an average 20 muA from the harvested 1.8-V supply.

  16. Electronic dura mater for long-term multimodal neural interfaces

    Science.gov (United States)

    Minev, Ivan R.; Musienko, Pavel; Hirsch, Arthur; Barraud, Quentin; Wenger, Nikolaus; Moraud, Eduardo Martin; Gandar, Jérôme; Capogrosso, Marco; Milekovic, Tomislav; Asboth, Léonie; Torres, Rafael Fajardo; Vachicouras, Nicolas; Liu, Qihan; Pavlova, Natalia; Duis, Simone; Larmagnac, Alexandre; Vörös, Janos; Micera, Silvestro; Suo, Zhigang; Courtine, Grégoire; Lacour, Stéphanie P.

    2015-01-01

    The mechanical mismatch between soft neural tissues and stiff neural implants hinders the long-term performance of implantable neuroprostheses. Here, we designed and fabricated soft neural implants with the shape and elasticity of dura mater, the protective membrane of the brain and spinal cord. The electronic dura mater, which we call e-dura, embeds interconnects, electrodes, and chemotrodes that sustain millions of mechanical stretch cycles, electrical stimulation pulses, and chemical injections. These integrated modalities enable multiple neuroprosthetic applications. The soft implants extracted cortical states in freely behaving animals for brain-machine interface and delivered electrochemical spinal neuromodulation that restored locomotion after paralyzing spinal cord injury.

  17. EDITORIAL: Special issue containing contributions from the 39th Neural Interfaces Conference Special issue containing contributions from the 39th Neural Interfaces Conference

    Science.gov (United States)

    Weiland, James D.

    2011-07-01

    Implantable neural interfaces provide substantial benefits to individuals with neurological disorders. That was the unequivocal message delivered by speaker after speaker from the podium of the 39th Neural Interfaces Conference (NIC2010) held in Long Beach, California, in June 2010. Giving benefit to patients is the most important measure for any biomedical technology, and myriad presentations at NIC2010 made clear that implantable neurostimulation technology has achieved this goal. Cochlear implants allow deaf people to communicate through speech. Deep brain stimulators give back mobility and dexterity necessary for so many daily tasks that are often taken for granted. Chronic pain can be alleviated through spinal cord stimulation. Motor prosthesis systems have been demonstrated in humans, through both reanimation of paralyzed limbs and neural control of robotic arms. Earlier this year, a retinal prosthesis was approved for sale in Europe, providing some hope for the blind. In sum, current clinical implants have been tremendously beneficial for today's patients and experimental systems that will be translated to the clinic promise to expand the number of people helped through bioelectronic therapies. Yet there are significant opportunities for improvement. For sensory prostheses, patients report an artificial sensation, clearly different from the natural sensation they remember. Neuromodulation systems, such as deep brain stimulation and pain stimulators, often have side effects that are tolerated as long as the side effects are less impactful than the disease. The papers published in the special issue from NIC2010 reflect the maturing and expanding field of neural interfaces. Our field has moved past proof-of-principle demonstrations and is now focusing on proving the longevity required for clinical implementation of new devices, extending existing approaches to new diseases and improving current devices for better outcomes. Closed-loop neuromodulation is a

  18. The Pursuit of Chronically Reliable Neural Interfaces: A Materials Perspective.

    Science.gov (United States)

    Guo, Liang

    2016-01-01

    Brain-computer interfaces represent one of the most astonishing technologies in our era. However, the grand challenge of chronic instability and limited throughput of the electrode-tissue interface has significantly hindered the further development and ultimate deployment of such exciting technologies. A multidisciplinary research workforce has been called upon to respond to this engineering need. In this paper, I briefly review this multidisciplinary pursuit of chronically reliable neural interfaces from a materials perspective by analyzing the problem, abstracting the engineering principles, and summarizing the corresponding engineering strategies. I further draw my future perspectives by extending the proposed engineering principles.

  19. Nanostructure and molecular interface for biosensing devices

    Science.gov (United States)

    Hiep, Ha M.; Endo, Tatsuro; Kim, Do-Kyun; Tamiya, Eiichi

    2007-09-01

    Nanostructure and molecular interface have currently received the great attractions for highly efficient, simultaneously analysis of a number of important biomolecules from proteomics to genomics. Outstanding optical property of noble metal nanostructures, localized surface plasmon resonance (LSPR), is a powerful phenomenon used in many chemical and biological sensing experiments. This report described two types of gold-capped nanostructures: nanoparticle and nanopore which reveal the strong excitation of LSPR spectra in the UV-visible region. The optical absorbance properties of these nanostructures governing its sensitivity to local environment were studied. The flexibility in design of the goldcapped nanostructures was evidently displayed on the wide-range capacity to develop in many types, from single to multiple to microfluidic formats. Moreover, chemical modifications on the nanostructure surface were thoroughly exploited to archive a highly sensitive protein and gene sensors such as using Protein A linker for orientation antibody or using specific binding of streptavidin and biotinylated PNA or DNA probes... Lastly, we introduced a new form of optical sensor, involving the coupling between interferometry and LSPR properties on the surface of gold-capped nanopore structure. Our optical biosensing devices connecting with the gold-capped nanostructures including both nanoparticle and nanopore are applicable to highly sensitive monitoring the interactions of other biomolecules, such as proteins, whole cells, or receptors with a massively parallel detection capability in a highly miniaturized package.

  20. Hafnium transistor process design for neural interfacing.

    Science.gov (United States)

    Parent, David W; Basham, Eric J

    2009-01-01

    A design methodology is presented that uses 1-D process simulations of Metal Insulator Semiconductor (MIS) structures to design the threshold voltage of hafnium oxide based transistors used for neural recording. The methodology is comprised of 1-D analytical equations for threshold voltage specification, and doping profiles, and 1-D MIS Technical Computer Aided Design (TCAD) to design a process to implement a specific threshold voltage, which minimized simulation time. The process was then verified with a 2-D process/electrical TCAD simulation. Hafnium oxide films (HfO) were grown and characterized for dielectric constant and fixed oxide charge for various annealing temperatures, two important design variables in threshold voltage design.

  1. Combining decoder design and neural adaptation in brain-machine interfaces.

    Science.gov (United States)

    Shenoy, Krishna V; Carmena, Jose M

    2014-11-19

    Brain-machine interfaces (BMIs) aim to help people with paralysis by decoding movement-related neural signals into control signals for guiding computer cursors, prosthetic arms, and other assistive devices. Despite compelling laboratory experiments and ongoing FDA pilot clinical trials, system performance, robustness, and generalization remain challenges. We provide a perspective on how two complementary lines of investigation, that have focused on decoder design and neural adaptation largely separately, could be brought together to advance BMIs. This BMI paradigm should also yield new scientific insights into the function and dysfunction of the nervous system. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Poled-glass devices: Influence of surfaces and interfaces

    DEFF Research Database (Denmark)

    Fage-Pedersen, Jacob; Jacobsen, Rune Shim; Kristensen, Martin

    2007-01-01

    Devices in periodically poled glass must have a large periodic variation of the built-in field. We show that the periodic variation can be severely degraded by charge dynamics taking place at the external (glass–air) interface or at internal (glass–glass) interfaces if the interfaces have imperfe...

  3. An implantable wireless neural interface for recording cortical circuit dynamics in moving primates

    Science.gov (United States)

    Borton, David A.; Yin, Ming; Aceros, Juan; Nurmikko, Arto

    2013-04-01

    Objective. Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims and those living with severe neuromotor disease. Such systems must be chronically safe, durable and effective. Approach. We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based microelectrode array via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1 Hz to 7.8 kHz, 200× gain) and multiplexed by a custom application specific integrated circuit, digitized and then packaged for transmission. The neural data (24 Mbps) were transmitted by a wireless data link carried on a frequency-shift-key-modulated signal at 3.2 and 3.8 GHz to a receiver 1 m away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7 h continuous operation between recharge via an inductive transcutaneous wireless power link at 2 MHz. Main results. Device verification and early validation were performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance. We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight into how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile

  4. Hafnium transistor design for neural interfacing.

    Science.gov (United States)

    Parent, David W; Basham, Eric J

    2008-01-01

    A design methodology is presented that uses the EKV model and the g(m)/I(D) biasing technique to design hafnium oxide field effect transistors that are suitable for neural recording circuitry. The DC gain of a common source amplifier is correlated to the structural properties of a Field Effect Transistor (FET) and a Metal Insulator Semiconductor (MIS) capacitor. This approach allows a transistor designer to use a design flow that starts with simple and intuitive 1-D equations for gain that can be verified in 1-D MIS capacitor TCAD simulations, before final TCAD process verification of transistor properties. The DC gain of a common source amplifier is optimized by using fast 1-D simulations and using slower, complex 2-D simulations only for verification. The 1-D equations are used to show that the increased dielectric constant of hafnium oxide allows a higher DC gain for a given oxide thickness. An additional benefit is that the MIS capacitor can be employed to test additional performance parameters important to an open gate transistor such as dielectric stability and ionic penetration.

  5. Targeted muscle reinnervation a neural interface for artificial limbs

    CERN Document Server

    Kuiken, Todd A; Barlow, Ann K

    2013-01-01

    Implement TMR with Your Patients and Improve Their Quality of Life Developed by Dr. Todd A. Kuiken and Dr. Gregory A. Dumanian, targeted muscle reinnervation (TMR) is a new approach to accessing motor control signals from peripheral nerves after amputation and providing sensory feedback to prosthesis users. This practical approach has many advantages over other neural-machine interfaces for the improved control of artificial limbs. Targeted Muscle Reinnervation: A Neural Interface for Artificial Limbs provides a template for the clinical implementation of TMR and a resource for further research in this new area of science. After describing the basic scientific concepts and key principles underlying TMR, the book presents surgical approaches to transhumeral and shoulder disarticulation amputations. It explores the possible role of TMR in the prevention and treatment of end-neuromas and details the principles of rehabilitation, prosthetic fitting, and occupational therapy for TMR patients. The book also describ...

  6. Designing Gestural Interfaces Touchscreens and Interactive Devices

    CERN Document Server

    Saffer, Dan

    2008-01-01

    If you want to get started in new era of interaction design, this is the reference you need. Packed with informative illustrations and photos, Designing Gestural Interfaces provides you with essential information about kinesiology, sensors, ergonomics, physical computing, touchscreen technology, and new interface patterns -- information you need to augment your existing skills in traditional" websites, software, or product development. This book will help you enter this new world of possibilities."

  7. Vertically aligned carbon nanofiber as nano-neuron interface for monitoring neural function

    Energy Technology Data Exchange (ETDEWEB)

    Ericson, Milton Nance [ORNL; McKnight, Timothy E [ORNL; Melechko, Anatoli Vasilievich [ORNL; Simpson, Michael L [ORNL; Morrison, Barclay [ORNL; Yu, Zhe [Columbia University

    2012-01-01

    Neural chips, which are capable of simultaneous, multi-site neural recording and stimulation, have been used to detect and modulate neural activity for almost 30 years. As a neural interface, neural chips provide dynamic functional information for neural decoding and neural control. By improving sensitivity and spatial resolution, nano-scale electrodes may revolutionize neural detection and modulation at cellular and molecular levels as nano-neuron interfaces. We developed a carbon-nanofiber neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes and demonstrated its capability of both stimulating and monitoring electrophysiological signals from brain tissues in vitro and monitoring dynamic information of neuroplasticity. This novel nano-neuron interface can potentially serve as a precise, informative, biocompatible, and dual-mode neural interface for monitoring of both neuroelectrical and neurochemical activity at the single cell level and even inside the cell.

  8. Neural growth into a microchannel network: towards a regenerative neural interface

    NARCIS (Netherlands)

    Wieringa, P.A.; Wiertz, Remy; le Feber, Jakob; Rutten, Wim

    2009-01-01

    We propose and validated a design for a highly selective 'endcap' regenerative neural interface towards a neuroprosthesis. In vitro studies using rat cortical neurons determine if a branching microchannel structure can counter fasciculated growth and cause neurites to separte from one another,

  9. Titania nanotube arrays as interfaces for neural prostheses

    Energy Technology Data Exchange (ETDEWEB)

    Sorkin, Jonathan A. [Department of Mechanical Engineering, Colorado State University, Fort Collins CO 80523 (United States); Hughes, Stephen [Department of Chemical and Biological Engineering, Colorado State University, Fort Collins CO 80523 (United States); School of Biomedical Engineering, Colorado State University, Fort Collins CO 80523 (United States); Soares, Paulo [Department of Mechanical Engineering, Polytechnic School, Pontifícia Universidade Católica do Paraná, Curitiba, PR 80215-901 (Brazil); Popat, Ketul C., E-mail: ketul.popat@colostate.edu [Department of Mechanical Engineering, Colorado State University, Fort Collins CO 80523 (United States); School of Biomedical Engineering, Colorado State University, Fort Collins CO 80523 (United States)

    2015-04-01

    Neural prostheses have become ever more acceptable treatments for many different types of neurological damage and disease. Here we investigate the use of two different morphologies of titania nanotube arrays as interfaces to advance the longevity and effectiveness of these prostheses. The nanotube arrays were characterized for their nanotopography, crystallinity, conductivity, wettability, surface mechanical properties and adsorption of key proteins: fibrinogen, albumin and laminin. The loosely packed nanotube arrays fabricated using a diethylene glycol based electrolyte, contained a higher presence of the anatase crystal phase and were subsequently more conductive. These arrays yielded surfaces with higher wettability and lower modulus than the densely packed nanotube arrays fabricated using water based electrolyte. Further the adhesion, proliferation and differentiation of the C17.2 neural stem cell line was investigated on the nanotube arrays. The proliferation ratio of the cells as well as the level of neuronal differentiation was seen to increase on the loosely packed arrays. The results indicate that loosely packed nanotube arrays similar to the ones produced here with a DEG based electrolyte, may provide a favorable template for growth and maintenance of C17.2 neural stem cell line. - Highlights: • Titania nanotube arrays can be fabricated with to have loosely or densely packed morphologies. • Titania nanotube arrays support higher C17.2 neural stem cell adhesion and proliferation. • Titania nanotube arrays support higher C17.2 neural stem cell differentiation towards neuronal lineage.

  10. A Multi-purpose Brain-Computer Interface Output Device

    Science.gov (United States)

    Thompson, David E; Huggins, Jane E

    2012-01-01

    While brain-computer interfaces (BCIs) are a promising alternative access pathway for individuals with severe motor impairments, many BCI systems are designed as standalone communication and control systems, rather than as interfaces to existing systems built for these purposes. While an individual communication and control system may be powerful or flexible, no single system can compete with the variety of options available in the commercial assistive technology (AT) market. BCIs could instead be used as an interface to these existing AT devices and products, which are designed for improving access and agency of people with disabilities and are highly configurable to individual user needs. However, interfacing with each AT device and program requires significant time and effort on the part of researchers and clinicians. This work presents the Multi-Purpose BCI Output Device (MBOD), a tool to help researchers and clinicians provide BCI control of many forms of AT in a plug-and-play fashion, i.e. without the installation of drivers or software on the AT device, and a proof-of-concept of the practicality of such an approach. The MBOD was designed to meet the goals of target device compatibility, BCI input device compatibility, convenience, and intuitive command structure. The MBOD was successfully used to interface a BCI with multiple AT devices (including two wheelchair seating systems), as well as computers running Windows (XP and 7), Mac and Ubuntu Linux operating systems. PMID:22208120

  11. A multi-purpose brain-computer interface output device.

    Science.gov (United States)

    Thompson, David E; Huggins, Jane E

    2011-10-01

    While brain-computer interfaces (BCIs) are a promising alternative access pathway for individuals with severe motor impairments, many BCI systems are designed as stand-alone communication and control systems, rather than as interfaces to existing systems built for these purposes. An individual communication and control system may be powerful or flexible, but no single system can compete with the variety of options available in the commercial assistive technology (AT) market. BCls could instead be used as an interface to these existing AT devices and products, which are designed for improving access and agency of people with disabilities and are highly configurable to individual user needs. However, interfacing with each AT device and program requires significant time and effort on the part of researchers and clinicians. This work presents the Multi-Purpose BCI Output Device (MBOD), a tool to help researchers and clinicians provide BCI control of many forms of AT in a plug-and-play fashion, i.e., without the installation of drivers or software on the AT device, and a proof-of-concept of the practicality of such an approach. The MBOD was designed to meet the goals of target device compatibility, BCI input device compatibility, convenience, and intuitive command structure. The MBOD was successfully used to interface a BCI with multiple AT devices (including two wheelchair seating systems), as well as computers running Windows (XP and 7), Mac and Ubuntu Linux operating systems.

  12. A microsystem integration platform dedicated to build multi-chip-neural interfaces.

    Science.gov (United States)

    Ayoub, Amer E; Gosselin, Benoit; Sawan, Mohamad

    2007-01-01

    In this paper, we present an electrical discharge machining (EDM) technique associated with electrochemical steps to construct an appropriate biological interface to neural tissues. The presented microprobe design permits to short the time of production compared to available techniques, while improving the integrity of the electrodes. In addition, we are using a 3D approach to create compact and independent microsystem integration platefrom incorporating array of electrodes and signal processing chips. System-in-package and die-stacking are used to connect the integrated circuits and the array of electrodes on the platform. This approach enables to build a device that will fit in a volume smaller than 1.7 x 1.7 x 3.0 mm(3). This demonstrates the possibility of creating small devices that are suitable to fit in restricted areas for interfacing the brain.

  13. Braided Multi-Electrode Probes (BMEPs) for Neural Interfaces

    Science.gov (United States)

    Kim, Tae Gyo

    Although clinical use of invasive neural interfaces is very limited, due to safety and reliability concerns, the potential benefits of their use in brain machine interfaces (BMIs) seem promising and so they have been widely used in the research field. Microelectrodes as invasive neural interfaces are the core tool to record neural activities and their failure is a critical issue for BMI systems. Possible sources of this failure are neural tissue motions and their interactions with stiff electrode arrays or probes fixed to the skull. To overcome these tissue motion problems, we have developed novel braided multi-electrode probes (BMEPs). By interweaving ultra-fine wires into a tubular braid structure, we obtained a highly flexible multi-electrode probe. In this thesis we described BMEP designs and how to fabricate BMEPs, and explore experiments to show the advantages of BMEPs through a mechanical compliance comparison and a chronic immunohistological comparison with single 50microm nichrome wires used as a reference electrode type. Results from the mechanical compliance test showed that the bodies of BMEPs have 4 to 21 times higher compliance than the single 50microm wire and the tethers of BMEPs were 6 to 96 times higher compliance, depending on combinations of the wire size (9.6microm or 12.7microm), the wire numbers (12 or 24), and the length of tether (3, 5 or 10 mm). Results from the immunohistological comparison showed that both BMEPs and 50microm wires anchored to the skull caused stronger tissue reactions than unanchored BMEPs and 50microm wires, and 50microm wires caused stronger tissue reactions than BMEPs. In in-vivo tests with BMEPs, we succeeded in chronic recordings from the spinal cord of freely jumping frogs and in acute recordings from the spinal cord of decerebrate rats during air stepping which was evoked by mesencephalic locomotor region (MLR) stimulation. This technology may provide a stable and reliable neural interface to spinal cord

  14. Video Game Device Haptic Interface for Robotic Arc Welding

    Energy Technology Data Exchange (ETDEWEB)

    Corrie I. Nichol; Milos Manic

    2009-05-01

    Recent advances in technology for video games have made a broad array of haptic feedback devices available at low cost. This paper presents a bi-manual haptic system to enable an operator to weld remotely using the a commercially available haptic feedback video game device for the user interface. The system showed good performance in initial tests, demonstrating the utility of low cost input devices for remote haptic operations.

  15. INTERFACE DEVICE FOR NONDESTRUCTIVE TESTING OF RESIDUAL SURFACE STRESSES

    Directory of Open Access Journals (Sweden)

    Gennady A. Perepelkin

    2016-01-01

    Full Text Available The paper considers the organization of connection of a personal computer with a device for nondestructive testing of residual surface stresses. The device works is based on the phenomenon of diffraction of ionizing radiation from the crystal lattice near the surface of the crystallites. Proposed software interface to the organization for each type of user: the device developers, administrators, users. Some aspects of the organization of communication microcontroller to a PC via USB-port

  16. Point-and-Click Cursor Control With an Intracortical Neural Interface System by Humans With Tetraplegia

    Science.gov (United States)

    Kim, Sung-Phil; Simeral, John D.; Hochberg, Leigh R.; Donoghue, John P.; Friehs, Gerhard M.; Black, Michael J.

    2012-01-01

    We present a point-and-click intracortical neural interface system (NIS) that enables humans with tetraplegia to volitionally move a 2-D computer cursor in any desired direction on a computer screen, hold it still, and click on the area of interest. This direct brain–computer interface extracts both discrete (click) and continuous (cursor velocity) signals from a single small population of neurons in human motor cortex. A key component of this system is a multi-state probabilistic decoding algorithm that simultaneously decodes neural spiking activity of a small population of neurons and outputs either a click signal or the velocity of the cursor. The algorithm combines a linear classifier, which determines whether the user is intending to click or move the cursor, with a Kalman filter that translates the neural population activity into cursor velocity. We present a paradigm for training the multi-state decoding algorithm using neural activity observed during imagined actions. Two human participants with tetraplegia (paralysis of the four limbs) performed a closed-loop radial target acquisition task using the point-and-click NIS over multiple sessions. We quantified point-and-click performance using various human-computer interaction measurements for pointing devices. We found that participants could control the cursor motion and click on specified targets with a small error rate (click 2-D cursor control of a personal computer. PMID:21278024

  17. Polymer Composite with Carbon Nanofibers Aligned during Thermal Drawing as a Microelectrode for Chronic Neural Interfaces.

    Science.gov (United States)

    Guo, Yuanyuan; Jiang, Shan; Grena, Benjamin J B; Kimbrough, Ian F; Thompson, Emily G; Fink, Yoel; Sontheimer, Harald; Yoshinobu, Tatsuo; Jia, Xiaoting

    2017-07-25

    Microelectrodes provide a direct pathway to investigate brain activities electrically from the external world, which has advanced our fundamental understanding of brain functions and has been utilized for rehabilitative applications as brain-machine interfaces. However, minimizing the tissue response and prolonging the functional durations of these devices remain challenging. Therefore, the development of next-generation microelectrodes as neural interfaces is actively progressing from traditional inorganic materials toward biocompatible and functional organic materials with a miniature footprint, good flexibility, and reasonable robustness. In this study, we developed a miniaturized all polymer-based neural probe with carbon nanofiber (CNF) composites as recording electrodes via the scalable thermal drawing process. We demonstrated that in situ CNF unidirectional alignment can be achieved during the thermal drawing, which contributes to a drastic improvement of electrical conductivity by 2 orders of magnitude compared to a conventional polymer electrode, while still maintaining the mechanical compliance with brain tissues. The resulting neural probe has a miniature footprint, including a recording site with a reduced size comparable to a single neuron and maintained impedance that was able to capture neural activities. Its stable functionality as a chronic implant has been demonstrated with the long-term reliable electrophysiological recording with single-spike resolution and the minimal tissue response over the extended period of implantation in wild-type mice. Technology developed here can be applied to basic chronic electrophysiological studies as well as clinical implementation for neuro-rehabilitative applications.

  18. Parietal neural prosthetic control of a computer cursor in a graphical-user-interface task

    Science.gov (United States)

    Revechkis, Boris; Aflalo, Tyson NS; Kellis, Spencer; Pouratian, Nader; Andersen, Richard A.

    2014-12-01

    Objective. To date, the majority of Brain-Machine Interfaces have been used to perform simple tasks with sequences of individual targets in otherwise blank environments. In this study we developed a more practical and clinically relevant task that approximated modern computers and graphical user interfaces (GUIs). This task could be problematic given the known sensitivity of areas typically used for BMIs to visual stimuli, eye movements, decision-making, and attentional control. Consequently, we sought to assess the effect of a complex, GUI-like task on the quality of neural decoding. Approach. A male rhesus macaque monkey was implanted with two 96-channel electrode arrays in area 5d of the superior parietal lobule. The animal was trained to perform a GUI-like ‘Face in a Crowd’ task on a computer screen that required selecting one cued, icon-like, face image from a group of alternatives (the ‘Crowd’) using a neurally controlled cursor. We assessed whether the crowd affected decodes of intended cursor movements by comparing it to a ‘Crowd Off’ condition in which only the matching target appeared without alternatives. We also examined if training a neural decoder with the Crowd On rather than Off had any effect on subsequent decode quality. Main results. Despite the additional demands of working with the Crowd On, the animal was able to robustly perform the task under Brain Control. The presence of the crowd did not itself affect decode quality. Training the decoder with the Crowd On relative to Off had no negative influence on subsequent decoding performance. Additionally, the subject was able to gaze around freely without influencing cursor position. Significance. Our results demonstrate that area 5d recordings can be used for decoding in a complex, GUI-like task with free gaze. Thus, this area is a promising source of signals for neural prosthetics that utilize computing devices with GUI interfaces, e.g. personal computers, mobile devices, and tablet

  19. Microfabrication, characterization and in vivo MRI compatibility of diamond microelectrodes array for neural interfacing

    Energy Technology Data Exchange (ETDEWEB)

    Hébert, Clément, E-mail: clement.hebert@cea.fr [Institut Néel, CNRS et Université Joseph Fourier, BP 166, F-38042 Grenoble Cedex 9 (France); Warnking, Jan; Depaulis, Antoine [INSERM, U836, Grenoble Institut des Neurosciences, Grenoble (France); Garçon, Laurie Amandine [Institut Néel, CNRS et Université Joseph Fourier, BP 166, F-38042 Grenoble Cedex 9 (France); CEA/INAC/SPrAM/CREAB, 17 rue des Martyrs, 38054 Grenoble Cedex 9 (France); Mermoux, Michel [Université Grenoble Alpes, LEPMI, F-38000 Grenoble (France); CNRS, LEPMI, F-38000 Grenoble (France); Eon, David [Institut Néel, CNRS et Université Joseph Fourier, BP 166, F-38042 Grenoble Cedex 9 (France); Mailley, Pascal [CEA-LETI-DTBS Minatec, 17 rue des Martyres, 38054 Grenoble (France); Omnès, Franck [Institut Néel, CNRS et Université Joseph Fourier, BP 166, F-38042 Grenoble Cedex 9 (France)

    2015-01-01

    Neural interfacing still requires highly stable and biocompatible materials, in particular for in vivo applications. Indeed, most of the currently used materials are degraded and/or encapsulated by the proximal tissue leading to a loss of efficiency. Here, we considered boron doped diamond microelectrodes to address this issue and we evaluated the performances of a diamond microelectrode array. We described the microfabrication process of the device and discuss its functionalities. We characterized its electrochemical performances by cyclic voltammetry and impedance spectroscopy in saline buffer and observed the typical diamond electrode electrochemical properties, wide potential window and low background current, allowing efficient electrochemical detection. The charge storage capacitance and the modulus of the electrochemical impedance were found to remain in the same range as platinum electrodes used for standard commercial devices. Finally we observed a reduced Magnetic Resonance Imaging artifact when the device was implanted on a rat cortex, suggesting that boron doped-diamond is a very promising electrode material allowing functional imaging. - Highlights: • Microfabrication of all-diamond microelectrode array • Evaluation of as-grown nanocrystalline boron-doped diamond for electrical neural interfacing • MRI compatibility of nanocrystalline boron-doped diamond.

  20. A Chronically Implantable Bidirectional Neural Interface for Non-human Primates

    Directory of Open Access Journals (Sweden)

    Misako Komatsu

    2017-09-01

    Full Text Available Optogenetics has potential applications in the study of epilepsy and neuroprostheses, and for studies on neural circuit dynamics. However, to achieve translation to clinical usage, optogenetic interfaces that are capable of chronic stimulation and monitoring with minimal brain trauma are required. We aimed to develop a chronically implantable device for photostimulation of the brain of non-human primates. We used a micro-light-emitting diode (LED array with a flexible polyimide film. The array was combined with a whole-cortex electrocorticographic (ECoG electrode array for simultaneous photostimulation and recording. Channelrhodopsin-2 (ChR2 was virally transduced into the cerebral cortex of common marmosets, and then the device was epidurally implanted into their brains. We recorded the neural activity during photostimulation of the awake monkeys for 4 months. The neural responses gradually increased after the virus injection for ~8 weeks and remained constant for another 8 weeks. The micro-LED and ECoG arrays allowed semi-invasive simultaneous stimulation and recording during long-term implantation in the brains of non-human primates. The development of this device represents substantial progress in the field of optogenetic applications.

  1. A Survey of Neural Front End Amplifiers and Their Requirements toward Practical Neural Interfaces

    Directory of Open Access Journals (Sweden)

    Eric Bharucha

    2014-11-01

    Full Text Available When designing an analog front-end for neural interfacing, it is hard to evaluate the interplay of priority features that one must upkeep. Given the competing nature of design requirements for such systems a good understanding of these trade-offs is necessary. Low power, chip size, noise control, gain, temporal resolution and safety are the salient ones. There is a need to expose theses critical features for high performance neural amplifiers as the density and performance needs of these systems increases. This review revisits the basic science behind the engineering problem of extracting neural signal from living tissue. A summary of architectures and topologies is then presented and illustrated through a rich set of examples based on the literature. A survey of existing systems is presented for comparison based on prevailing performance metrics.

  2. Neural Networks through Shared Maps in Mobile Devices

    Directory of Open Access Journals (Sweden)

    William Raveane

    2014-12-01

    Full Text Available We introduce a hybrid system composed of a convolutional neural network and a discrete graphical model for image recognition. This system improves upon traditional sliding window techniques for analysis of an image larger than the training data by effectively processing the full input scene through the neural network in less time. The final result is then inferred from the neural network output through energy minimization to reach a more precize localization than what traditional maximum value class comparisons yield. These results are apt for applying this process in a mobile device for real time image recognition.

  3. Drug release from porous silicon for stable neural interface

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Tao, E-mail: taosun@hotmail.com.hk [Institute of Microelectronics, Agency for Science, Technology and Research (A-STAR) (Singapore); Tsang, Wei Mong [Institute of Microelectronics, Agency for Science, Technology and Research (A-STAR) (Singapore); Park, Woo-Tae [Institute of Microelectronics, Agency for Science, Technology and Research (A-STAR) (Singapore); Department of Mechanical and Automotive Engineering, Seoul National University of Science and Technology, Seoul (Korea, Republic of)

    2014-02-15

    70 μm-thick porous Si (PSi) layer with the pore size of 11.1 ± 7.6 nm was formed on an 8-in. Si wafer via an anodization process for the microfabrication of a microelectrode to record neural signals. To reduce host tissue responses to the microelectrode and achieve a stable neural interface, water-soluble dexamethesone (Dex) was loaded into the PSi via incubation with the drug solution overnight. After the drug loading process, the pore size of PSi reduced to 4.7 ± 2.6 nm on the basis of scanning electron microscopic (SEM) images, while its wettability was remarkably enhanced. Fluorescence images demonstrated that Dex was loaded into the porous structure of the PSi. Degradation rate of the PSi was investigated by incubation in distilled water for 21 days. Moreover, the drug release profile of the Dex-loaded PSi was a combination of an initial burst release and subsequent sustained release. To evaluate cellular responses to the drug release from the PSi, primary astrocytes were seeded on the surface of samples. After 2 days of culture, the Dex-loaded PSi could not only moderately prevent astrocyte adhesion in comparison with Si, but also more effectively suppress the activation of primary astrocytes than unloaded PSi due to the drug release. Therefore, it might be an effective method to reduce host tissue responses and stabilize the quality of the recorded neural signal by means of loading drugs into the PSi component of the microelectrode.

  4. Titania nanotube arrays as interfaces for neural prostheses.

    Science.gov (United States)

    Sorkin, Jonathan A; Hughes, Stephen; Soares, Paulo; Popat, Ketul C

    2015-04-01

    Neural prostheses have become ever more acceptable treatments for many different types of neurological damage and disease. Here we investigate the use of two different morphologies of titania nanotube arrays as interfaces to advance the longevity and effectiveness of these prostheses. The nanotube arrays were characterized for their nanotopography, crystallinity, conductivity, wettability, surface mechanical properties and adsorption of key proteins: fibrinogen, albumin and laminin. The loosely packed nanotube arrays fabricated using a diethylene glycol based electrolyte, contained a higher presence of the anatase crystal phase and were subsequently more conductive. These arrays yielded surfaces with higher wettability and lower modulus than the densely packed nanotube arrays fabricated using water based electrolyte. Further the adhesion, proliferation and differentiation of the C17.2 neural stem cell line was investigated on the nanotube arrays. The proliferation ratio of the cells as well as the level of neuronal differentiation was seen to increase on the loosely packed arrays. The results indicate that loosely packed nanotube arrays similar to the ones produced here with a DEG based electrolyte, may provide a favorable template for growth and maintenance of C17.2 neural stem cell line. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. At the interface: convergence of neural regeneration and neural prostheses for restoration of function.

    Science.gov (United States)

    Grill, W M; McDonald, J W; Peckham, P H; Heetderks, W; Kocsis, J; Weinrich, M

    2001-01-01

    The rapid pace of recent advances in development and application of electrical stimulation of the nervous system and in neural regeneration has created opportunities to combine these two approaches to restoration of function. This paper relates the discussion on this topic from a workshop at the International Functional Electrical Stimulation Society. The goals of this workshop were to discuss the current state of interaction between the fields of neural regeneration and neural prostheses and to identify potential areas of future research that would have the greatest impact on achieving the common goal of restoring function after neurological damage. Identified areas include enhancement of axonal regeneration with applied electric fields, development of hybrid neural interfaces combining synthetic silicon and biologically derived elements, and investigation of the role of patterned neural activity in regulating various neuronal processes and neurorehabilitation. Increased communication and cooperation between the two communities and recognition by each field that the other has something to contribute to their efforts are needed to take advantage of these opportunities. In addition, creative grants combining the two approaches and more flexible funding mechanisms to support the convergence of their perspectives are necessary to achieve common objectives.

  6. A lysinated thiophene-based semiconductor as a multifunctional neural bioorganic interface.

    Science.gov (United States)

    Bonetti, Simone; Pistone, Assunta; Brucale, Marco; Karges, Saskia; Favaretto, Laura; Zambianchi, Massimo; Posati, Tamara; Sagnella, Anna; Caprini, Marco; Toffanin, Stefano; Zamboni, Roberto; Camaioni, Nadia; Muccini, Michele; Melucci, Manuela; Benfenati, Valentina

    2015-06-03

    Lysinated molecular organic semiconductors are introduced as valuable multifunctional platforms for neural cells growth and interfacing. Cast films of quaterthiophene (T4) semiconductor covalently modified with lysine-end moieties (T4Lys) are fabricated and their stability, morphology, optical/electrical, and biocompatibility properties are characterized. T4Lys films exhibit fluorescence and electronic transport as generally observed for unsubstituted oligothiophenes combined to humidity-activated ionic conduction promoted by the charged lysine-end moieties. The Lys insertion in T4 enables adhesion of primary culture of rat dorsal root ganglion (DRG), which is not achievable by plating cells on T4. Notably, on T4Lys, the number on adhering neurons/area is higher and displays a twofold longer neurite length than neurons plated on glass coated with poly-l-lysine. Finally, by whole-cell patch-clamp, it is shown that the biofunctionality of neurons cultured on T4Lys is preserved. The present study introduces an innovative concept for organic material neural interface that combines optical and iono-electronic functionalities with improved biocompatibility and neuron affinity promoted by Lys linkage and the softness of organic semiconductors. Lysinated organic semiconductors could set the scene for the fabrication of simplified bioorganic devices geometry for cells bidirectional communication or optoelectronic control of neural cells biofunctionality. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Poly(3,4-ethylene dioxythiophene (PEDOT as a micro-neural interface material for electrostimulation

    Directory of Open Access Journals (Sweden)

    Seth J Wilks

    2009-06-01

    Full Text Available Chronic microstimulation-based devices are being investigated to treat conditions such as blindness, deafness, pain, paralysis and epilepsy. Small area electrodes are desired to achieve high selectivity. However, a major trade-off with electrode miniaturization is an increase in impedance and charge density requirements. Thus, the development of novel materials with lower interfacial impedance and enhanced charge storage capacity is essential for the development of micro-neural interface-based neuroprostheses. In this report, we study the use of conducting polymer poly(3,4-ethylene dioxythiophene (PEDOT as a neural interface material for microstimulation of small area iridium electrodes on silicon-substrate arrays. Characterized by electrochemical impedance spectroscopy, electrodeposition of PEDOT results in lower interfacial impedance at physiologically-relevant frequencies, with the 1kHz impedance magnitude being 23.3 ± 0.7 kΩ compared to 113.6 ± 3.5 kΩ for iridium oxide (IrOx on 177μm2 sites. Further, PEDOT exhibits enhanced charge storage capacity at 75.6 ± 5.4 mC/cm2 compared to 28.8 ± 0.3 mC/cm2 for IrOx, characterized by cyclic voltammetry (50 mV/s. These improvements at the electrode interface were corroborated by observation of the voltage excursions that result from constant current pulsing. The PEDOT coatings provide both a lower amplitude voltage and a more ohmic representation of the applied current compared to IrOx. During repetitive pulsing, PEDOT-coated electrodes show stable performance and little change in electrical properties, even at relatively high current densities which cause IrOx instability. These findings support the potential of PEDOT coatings as a micro-neural interface material for electrostimulation.

  8. A Web Service and Interface for Remote Electronic Device Characterization

    Science.gov (United States)

    Dutta, S.; Prakash, S.; Estrada, D.; Pop, E.

    2011-01-01

    A lightweight Web Service and a Web site interface have been developed, which enable remote measurements of electronic devices as a "virtual laboratory" for undergraduate engineering classes. Using standard browsers without additional plugins (such as Internet Explorer, Firefox, or even Safari on an iPhone), remote users can control a Keithley…

  9. Conducting polymers with immobilised fibrillar collagen for enhanced neural interfacing.

    Science.gov (United States)

    Liu, Xiao; Yue, Zhilian; Higgins, Michael J; Wallace, Gordon G

    2011-10-01

    Conducting polymers with pendant functionality are advantageous in various bionic and organic bioelectronic applications, as they allow facile incorporation of bio-regulative cues to provide bio-mimicry and conductive environments for cell growth, differentiation and function. In this work, polypyrrole substrates doped with chondroitin sulfate (CS), an extracellular matrix molecule bearing carboxylic acid moieties, were electrochemically synthesized and conjugated with type I collagen. During the coupling process, the conjugated collagen formed a 3-dimensional fibrillar matrix in situ at the conducting polymer interface, as evidenced by atomic force microscopy (AFM) and fluorescence microscopy under aqueous physiological conditions. Cyclic voltammetry (CV) and impedance measurement confirmed no significant reduction in the electroactivity of the fibrillar collagen-modified conducting polymer substrates. Rat pheochromocytoma (nerve) cells showed increased differentiation and neurite outgrowth on the fibrillar collagen, which was further enhanced through electrical stimulation of the underlying conducting polymer substrate. Our study demonstrates that the direct coupling of ECM components such as collagen, followed by their further self-assembly into 3-dimensional matrices, has the potential to improve the neural-electrode interface of implant electrodes by encouraging nerve cell attachment and differentiation. Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. Point-and-click cursor control with an intracortical neural interface system by humans with tetraplegia.

    Science.gov (United States)

    Kim, Sung-Phil; Simeral, John D; Hochberg, Leigh R; Donoghue, John P; Friehs, Gerhard M; Black, Michael J

    2011-04-01

    We present a point-and-click intracortical neural interface system (NIS) that enables humans with tetraplegia to volitionally move a 2-D computer cursor in any desired direction on a computer screen, hold it still, and click on the area of interest. This direct brain-computer interface extracts both discrete (click) and continuous (cursor velocity) signals from a single small population of neurons in human motor cortex. A key component of this system is a multi-state probabilistic decoding algorithm that simultaneously decodes neural spiking activity of a small population of neurons and outputs either a click signal or the velocity of the cursor. The algorithm combines a linear classifier, which determines whether the user is intending to click or move the cursor, with a Kalman filter that translates the neural population activity into cursor velocity. We present a paradigm for training the multi-state decoding algorithm using neural activity observed during imagined actions. Two human participants with tetraplegia (paralysis of the four limbs) performed a closed-loop radial target acquisition task using the point-and-click NIS over multiple sessions. We quantified point-and-click performance using various human-computer interaction measurements for pointing devices. We found that participants could control the cursor motion and click on specified targets with a small error rate (one participant). This study suggests that signals from a small ensemble of motor cortical neurons (∼40) can be used for natural point-and-click 2-D cursor control of a personal computer.

  11. A New Animal Model for Developing a Somatosensory Neural Interface for Prosthetic Limbs

    Science.gov (United States)

    2008-02-12

    interface for neuroprosthetic limbs. PI: Douglas J. Weber, Ph.D. University of Pittsburgh 1 10/15/2007 Scientific progress and accomplishments. We...information to the brain. A new animal model for developing a somatosensory neural interface for neuroprosthetic limbs. PI: Douglas J. Weber, Ph.D...A new animal model for developing a somatosensory neural interface for neuroprosthetic limbs. PI: Douglas J. Weber, Ph.D. University of Pittsburgh

  12. Tissue-electronics interfaces: from implantable devices to engineered tissues

    Science.gov (United States)

    Feiner, Ron; Dvir, Tal

    2018-01-01

    Biomedical electronic devices are interfaced with the human body to extract precise medical data and to interfere with tissue function by providing electrical stimuli. In this Review, we outline physiologically and pathologically relevant tissue properties and processes that are important for designing implantable electronic devices. We summarize design principles for flexible and stretchable electronics that adapt to the mechanics of soft tissues, such as those including conducting polymers, liquid metal alloys, metallic buckling and meandering architectures. We further discuss technologies for inserting devices into the body in a minimally invasive manner and for eliminating them without further intervention. Finally, we introduce the concept of integrating electronic devices with biomaterials and cells, and we envision how such technologies may lead to the development of bionic organs for regenerative medicine.

  13. Design and manufacturing challenges of optogenetic neural interfaces: a review

    Science.gov (United States)

    Goncalves, S. B.; Ribeiro, J. F.; Silva, A. F.; Costa, R. M.; Correia, J. H.

    2017-08-01

    Optogenetics is a relatively new technology to achieve cell-type specific neuromodulation with millisecond-scale temporal precision. Optogenetic tools are being developed to address neuroscience challenges, and to improve the knowledge about brain networks, with the ultimate aim of catalyzing new treatments for brain disorders and diseases. To reach this ambitious goal the implementation of mature and reliable engineered tools is required. The success of optogenetics relies on optical tools that can deliver light into the neural tissue. Objective/Approach: Here, the design and manufacturing approaches available to the scientific community are reviewed, and current challenges to accomplish appropriate scalable, multimodal and wireless optical devices are discussed. Significance: Overall, this review aims at presenting a helpful guidance to the engineering and design of optical microsystems for optogenetic applications.

  14. Development of regenerative peripheral nerve interfaces for motor control of neuroprosthetic devices

    Science.gov (United States)

    Kemp, Stephen W. P.; Urbanchek, Melanie G.; Irwin, Zachary T.; Chestek, Cynthia A.; Cederna, Paul S.

    2017-05-01

    Traumatic peripheral nerve injuries suffered during amputation commonly results in debilitating neuropathic pain in the affected limb. Modern prosthetic technologies allow for intuitive, simultaneous control of multiple degrees of freedom. However, these state-of-the-art devices require separate, independent control signals for each degree of freedom, which is currently not possible. As a result, amputees reject up to 75% of myoelectric devices preferring instead to use body-powered artificial limbs which offer subtle sensory feedback. Without meaningful and intuitive sensory feedback, even the most advanced myoelectric prostheses remain insensate, burdensome, and are associated with enormous cognitive demand and mental fatigue. The ideal prosthetic device is one which is capable of providing intuitive somatosensory feedback essential for interaction with the environment. Critical to the design of such a bioprosthetic device is the development of a reliable biologic interface between human and machine. This ideal patient-prosthetic interface allows for transmission of both afferent somatosensory information and efferent motor signals for a closed-loop feedback system of neural control. Our lab has developed the Regenerative Peripheral Nerve Interface (RPNI) as a biologic nerve interface designed for stable integration of a prosthetic device with transected peripheral nerves in a residual limb. The RPNI is constructed by surgically implanting the distal end of a transected peripheral nerve into an autogenous muscle graft. Animal experiments in our lab have shown recording of motor signals from RPNI's implanted into both rodents and monkeys. Here, we achieve high amplitude EMG signals with a high signal to noise (SNR) ratio.

  15. A wireless transmission neural interface system for unconstrained non-human primates

    Science.gov (United States)

    Fernandez-Leon, Jose A.; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J.; Hansen, Bryan J.; Hu, Ming; Dragoi, Valentin

    2015-10-01

    Objective. Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. Approach. To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation. Main results. We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. Significance. We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.

  16. Neural bases of syntax-semantics interface processing.

    Science.gov (United States)

    Malaia, Evguenia; Newman, Sharlene

    2015-06-01

    The binding problem-question of how information between the modules of the linguistic system is integrated during language processing-is as yet unresolved. The remarkable speed of language processing and comprehension (Pulvermüller et al. 2009) suggests that at least coarse semantic information (e.g. noun animacy) and syntactically-relevant information (e.g. verbal template) are integrated rapidly to allow for coarse comprehension. This EEG study investigated syntax-semantics interface processing during word-by-word sentence reading. As alpha-band neural activity serves as an inhibition mechanism for local networks, we used topographical distribution of alpha power to help identify the timecourse of the binding process. We manipulated the syntactic parameter of verbal event structure, and semantic parameter of noun animacy in reduced relative clauses (RRCs, e.g. "The witness/mansion seized/protected by the agent was in danger"), to investigate the neural bases of interaction between syntactic and semantic networks during sentence processing. The word-by-word stimulus presentation method in the present experiment required manipulation of both syntactic structure and semantic features in the working memory. The results demonstrated a gradient distribution of early components (biphasic posterior P1-N2 and anterior N1-P2) over function words "by" and "the", and the verb, corresponding to facilitation or conflict resulting from the syntactic (telicity) and semantic (animacy) cues in the preceding portion of the sentence. This was followed by assimilation of power distribution in the α band at the second noun. The flattened distribution of α power during the mental manipulation with high demand on working memory-thematic role re-assignment-demonstrates a state of α equilibrium with strong functional coupling between posterior and anterior regions. These results demonstrate that the processing of semantic and syntactic features during sentence comprehension proceeds

  17. The Necessary Death of the Block Device Interface

    DEFF Research Database (Denmark)

    Bjørling, Matias; Bonnet, Philippe; Bouganim, Luc

    throughout the I/O stack to minimize CPU overhead. Finally, SSDs provide a high degree of parallelism that must be leveraged to reach nominal bandwidth. This evolution puts database system researchers at a crossroad. The first option is to hang on to the current architecture where secondary storage...... is encapsulated behind a block device interface. This is the mainstream option both in industry and academia. This leaves the storage and OS communities with the responsibility to deal with the complexity introduced by SSDs in the hope that they will provide us with a robust, yet simple, performance model...

  18. Computational Assessment of Neural Probe and Brain Tissue Interface under Transient Motion

    Directory of Open Access Journals (Sweden)

    Michael Polanco

    2016-06-01

    Full Text Available The functional longevity of a neural probe is dependent upon its ability to minimize injury risk during the insertion and recording period in vivo, which could be related to motion-related strain between the probe and surrounding tissue. A series of finite element analyses was conducted to study the extent of the strain induced within the brain in an area around a neural probe. This study focuses on the transient behavior of neural probe and brain tissue interface with a viscoelastic model. Different stages of the interface from initial insertion of neural probe to full bonding of the probe by astro-glial sheath formation are simulated utilizing analytical tools to investigate the effects of relative motion between the neural probe and the brain while friction coefficients and kinematic frequencies are varied. The analyses can provide an in-depth look at the quantitative benefits behind using soft materials for neural probes.

  19. Interpenetrating Conducting Hydrogel Materials for Neural Interfacing Electrodes.

    Science.gov (United States)

    Goding, Josef; Gilmour, Aaron; Martens, Penny; Poole-Warren, Laura; Green, Rylie

    2017-05-01

    Conducting hydrogels (CHs) are an emerging technology in the field of medical electrodes and brain-machine interfaces. The greatest challenge to the fabrication of CH electrodes is the hybridization of dissimilar polymers (conductive polymer and hydrogel) to ensure the formation of interpenetrating polymer networks (IPN) required to achieve both soft and electroactive materials. A new hydrogel system is developed that enables tailored placement of covalently immobilized dopant groups within the hydrogel matrix. The role of immobilized dopant in the formation of CH is investigated through covalent linking of sulfonate doping groups to poly(vinyl alcohol) (PVA) macromers. These groups control the electrochemical growth of the conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) and subsequent material properties. The effect of dopant density and interdopant spacing on the physical, electrochemical, and mechanical properties of the resultant CHs is examined. Cytocompatible PVA hydrogels with PEDOT penetration throughout the depth of the electrode are produced. Interdopant spacing is found to be the key factor in the formation of IPNs, with smaller interdopant spacing producing CH electrodes with greater charge storage capacity and lower impedance due to increased PEDOT growth throughout the network. This approach facilitates tailorable, high-performance CH electrodes for next generation, low impedance neuroprosthetic devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Connecting Neurons to a Mobile Robot: An In Vitro Bidirectional Neural Interface

    Directory of Open Access Journals (Sweden)

    A. Novellino

    2007-01-01

    Full Text Available One of the key properties of intelligent behaviors is the capability to learn and adapt to changing environmental conditions. These features are the result of the continuous and intense interaction of the brain with the external world, mediated by the body. For this reason x201C;embodiment” represents an innovative and very suitable experimental paradigm when studying the neural processes underlying learning new behaviors and adapting to unpredicted situations. To this purpose, we developed a novel bidirectional neural interface. We interconnected in vitro neurons, extracted from rat embryos and plated on a microelectrode array (MEA, to external devices, thus allowing real-time closed-loop interaction. The novelty of this experimental approach entails the necessity to explore different computational schemes and experimental hypotheses. In this paper, we present an open, scalable architecture, which allows fast prototyping of different modules and where coding and decoding schemes and different experimental configurations can be tested. This hybrid system can be used for studying the computational properties and information coding in biological neuronal networks with far-reaching implications for the future development of advanced neuroprostheses.

  1. Neural control of finger movement via intracortical brain–machine interface

    Science.gov (United States)

    Irwin, Z. T.; Schroeder, K. E.; Vu, P. P.; Bullard, A. J.; Tat, D. M.; Nu, C. S.; Vaskov, A.; Nason, S. R.; Thompson, D. E.; Bentley, J. N.; Patil, P. G.; Chestek, C. A.

    2017-12-01

    Objective. Intracortical brain–machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques. Approach. In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets. In the physical control condition, four rhesus macaques performed this task by moving all four fingers together in order to acquire a single target. This movement was equivalent to controlling the aperture of a power grasp. During this task performance, we recorded neural spikes from intracortical electrode arrays in primary motor cortex. Main results. Using a standard Kalman filter, we could reconstruct continuous finger movement offline with an average correlation of ρ  =  0.78 between actual and predicted position across four rhesus macaques. For two of the monkeys, this movement prediction was performed in real-time to enable direct brain control of the virtual hand. Compared to physical control, neural control performance was slightly degraded; however, the monkeys were still able to successfully perform the task with an average target acquisition rate of 83.1%. The monkeys’ ability to arbitrarily specify fingertip position was also quantified using an information throughput metric. During brain control task performance, the monkeys achieved an average 1.01 bits s‑1 throughput, similar to that achieved in previous studies which decoded upper-arm movements to control computer cursors using a standard Kalman filter. Significance. This is, to our knowledge, the first demonstration of brain control of finger-level fine motor skills. We

  2. Neural control of finger movement via intracortical brain-machine interface.

    Science.gov (United States)

    Irwin, Z T; Schroeder, K E; Vu, P P; Bullard, A J; Tat, D M; Nu, C S; Vaskov, A; Nason, S R; Thompson, D E; Bentley, J N; Patil, P G; Chestek, C A

    2017-12-01

    Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques. In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets. In the physical control condition, four rhesus macaques performed this task by moving all four fingers together in order to acquire a single target. This movement was equivalent to controlling the aperture of a power grasp. During this task performance, we recorded neural spikes from intracortical electrode arrays in primary motor cortex. Using a standard Kalman filter, we could reconstruct continuous finger movement offline with an average correlation of ρ  =  0.78 between actual and predicted position across four rhesus macaques. For two of the monkeys, this movement prediction was performed in real-time to enable direct brain control of the virtual hand. Compared to physical control, neural control performance was slightly degraded; however, the monkeys were still able to successfully perform the task with an average target acquisition rate of 83.1%. The monkeys' ability to arbitrarily specify fingertip position was also quantified using an information throughput metric. During brain control task performance, the monkeys achieved an average 1.01 bits s -1 throughput, similar to that achieved in previous studies which decoded upper-arm movements to control computer cursors using a standard Kalman filter. This is, to our knowledge, the first demonstration of brain control of finger-level fine motor skills. We believe that these results represent an important step

  3. In vivo electrical conductivity across critical nerve gaps using poly(3,4-ethylenedioxythiophene)-coated neural interfaces.

    Science.gov (United States)

    Egeland, Brent M; Urbanchek, Melanie G; Peramo, Antonio; Richardson-Burns, Sarah M; Martin, David C; Kipke, Daryl R; Kuzon, William M; Cederna, Paul S

    2010-12-01

    Bionic limbs require sensitive, durable, and physiologically relevant bidirectional control interfaces. Modern central nervous system interfacing is high risk, low fidelity, and failure prone. Peripheral nervous system interfaces will mitigate this risk and increase fidelity by greatly simplifying signal interpretation and delivery. This study evaluates in vivo relevance of a hybrid peripheral nervous system interface consisting of biological acellular muscle scaffolds made electrically conductive using poly(3,4-ethylenedioxythiophene). Peripheral nervous system interfaces were tested in vivo using the rat hind-limb conduction-gap model for motor (peroneal) and sensory (sural) nerves. Experimental groups included acellular muscle, iron(III) chloride-treated acellular muscle, and poly(3,4-ethylenedioxythiophene) polymerized on acellular muscle, each compared with intact nerve, autogenous nerve graft, and empty (nonreconstructed) nerve gap controls (n=5 for each). Interface lengths tested included 0, 5, 10, and 20 mm. Immediately following implantation, the interface underwent electrophysiologic characterization in vivo using nerve conduction studies, compound muscle action potentials, and antidromic sensory nerve action potentials. Both efferent and afferent electrophysiology demonstrates acellular muscle-poly(3,4-ethylenedioxythiophene) interfaces conduct physiologic action potentials across nerve conduction gaps of at least 20 mm with amplitude and latency not differing from intact nerve or nerve grafts, with the exception of increased velocity in the acellular muscle-poly(3,4-ethylenedioxythiophene) interfaces. Nonmetallic, biosynthetic acellular muscle-poly(3,4-ethylenedioxythiophene) peripheral nervous system interfaces both sense and stimulate physiologically relevant efferent and afferent action potentials in vivo. This demonstrates their relevance not only as a nerve-electronic coupling device capable of reaching the long-sought goal of closed-loop neural

  4. Intra-day signal instabilities affect decoding performance in an intracortical neural interface system

    Science.gov (United States)

    Perge, János A.; Homer, Mark L.; Malik, Wasim Q.; Cash, Sydney; Eskandar, Emad; Friehs, Gerhard; Donoghue, John P.; Hochberg, Leigh R.

    2013-06-01

    Objective. Motor neural interface systems (NIS) aim to convert neural signals into motor prosthetic or assistive device control, allowing people with paralysis to regain movement or control over their immediate environment. Effector or prosthetic control can degrade if the relationship between recorded neural signals and intended motor behavior changes. Therefore, characterizing both biological and technological sources of signal variability is important for a reliable NIS. Approach. To address the frequency and causes of neural signal variability in a spike-based NIS, we analyzed within-day fluctuations in spiking activity and action potential amplitude recorded with silicon microelectrode arrays implanted in the motor cortex of three people with tetraplegia (BrainGate pilot clinical trial, IDE). Main results. 84% of the recorded units showed a statistically significant change in apparent firing rate (3.8 ± 8.71 Hz or 49% of the mean rate) across several-minute epochs of tasks performed on a single session, and 74% of the units showed a significant change in spike amplitude (3.7 ± 6.5 µV or 5.5% of mean spike amplitude). 40% of the recording sessions showed a significant correlation in the occurrence of amplitude changes across electrodes, suggesting array micro-movement. Despite the relatively frequent amplitude changes, only 15% of the observed within-day rate changes originated from recording artifacts such as spike amplitude change or electrical noise, while 85% of the rate changes most likely emerged from physiological mechanisms. Computer simulations confirmed that systematic rate changes of individual neurons could produce a directional ‘bias’ in the decoded neural cursor movements. Instability in apparent neuronal spike rates indeed yielded a directional bias in 56% of all performance assessments in participant cursor control (n = 2 participants, 108 and 20 assessments over two years), resulting in suboptimal performance in these sessions

  5. An externally head-mounted wireless neural recording device for laboratory animal research and possible human clinical use.

    Science.gov (United States)

    Yin, Ming; Li, Hao; Bull, Christopher; Borton, David A; Aceros, Juan; Larson, Lawrence; Nurmikko, Arto V

    2013-01-01

    In this paper we present a new type of head-mounted wireless neural recording device in a highly compact package, dedicated for untethered laboratory animal research and designed for future mobile human clinical use. The device, which takes its input from an array of intracortical microelectrode arrays (MEA) has ninety-seven broadband parallel neural recording channels and was integrated on to two custom designed printed circuit boards. These house several low power, custom integrated circuits, including a preamplifier ASIC, a controller ASIC, plus two SAR ADCs, a 3-axis accelerometer, a 48MHz clock source, and a Manchester encoder. Another ultralow power RF chip supports an OOK transmitter with the center frequency tunable from 3GHz to 4GHz, mounted on a separate low loss dielectric board together with a 3V LDO, with output fed to a UWB chip antenna. The IC boards were interconnected and packaged in a polyether ether ketone (PEEK) enclosure which is compatible with both animal and human use (e.g. sterilizable). The entire system consumes 17mA from a 1.2Ahr 3.6V Li-SOCl2 1/2AA battery, which operates the device for more than 2 days. The overall system includes a custom RF receiver electronics which are designed to directly interface with any number of commercial (or custom) neural signal processors for multi-channel broadband neural recording. Bench-top measurements and in vivo testing of the device in rhesus macaques are presented to demonstrate the performance of the wireless neural interface.

  6. iSpike: a spiking neural interface for the iCub robot.

    Science.gov (United States)

    Gamez, D; Fidjeland, A K; Lazdins, E

    2012-06-01

    This paper presents iSpike: a C++ library that interfaces between spiking neural network simulators and the iCub humanoid robot. It uses a biologically inspired approach to convert the robot's sensory information into spikes that are passed to the neural network simulator, and it decodes output spikes from the network into motor signals that are sent to control the robot. Applications of iSpike range from embodied models of the brain to the development of intelligent robots using biologically inspired spiking neural networks. iSpike is an open source library that is available for free download under the terms of the GPL.

  7. Graphene nanocomposites as thermal interface materials for cooling energy devices

    Science.gov (United States)

    Dmitriev, A. S.; Valeev, A. R.

    2017-11-01

    The paper describes the technology of creating samples of graphene nanocomposites based on graphene flakes obtained by splitting graphite with ultrasound of high power. Graphene nanocomposites in the form of samples are made by the technology of weak sintering at high pressure (200-300 bar) and temperature up to 150 0 C, and also in the form of compositions with polymer matrices. The reflection spectra in the visible range and the near infrared range for the surface of nanocomposite samples are studied, the data of optical and electronic spectroscopy of such samples are givenIn addition, data on the electrophysical and thermal properties of the nanocomposites obtained are presented. Some analytical models of wetting and spreading over graphene nanocomposite surfaces have been constructed and calculated, and their effective thermal conductivity has been calculated and compared with the available experimental data. Possible applications of graphene nanocomposites for use as thermal interface materials for heat removal and cooling for power equipment, as well as microelectronics and optoelectronics devices are described.

  8. Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

    Science.gov (United States)

    Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

    2017-08-01

    Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a

  9. Investigation of Interface Charges at the Heterojunction Discontinuity in HBT Devices

    DEFF Research Database (Denmark)

    Fuente, Jesús Grajal de al; Krozer, Viktor

    2002-01-01

    In this paper we investigate the impact of interface charges at heterojunctions on the performance of heterostructure bipolar transistors (HBT). Interface charges can modify the limiting process for the carrier transport in a device. Therefore. intentional interface charges introduced by delta......-doped layers are basic tools for interface engineering. An accurate modelling of heterointerfaces which includes thermionic-field emission, surface charges, and surface dipoles allows to analyse the electrical performance of some modern devices based on band gap and interface engineering. It is demonstrated...... Science Ltd. All rights reserved....

  10. Hybrid Spintronic-CMOS Spiking Neural Network with On-Chip Learning: Devices, Circuits, and Systems

    Science.gov (United States)

    Sengupta, Abhronil; Banerjee, Aparajita; Roy, Kaushik

    2016-12-01

    Over the past decade, spiking neural networks (SNNs) have emerged as one of the popular architectures to emulate the brain. In SNNs, information is temporally encoded and communication between neurons is accomplished by means of spikes. In such networks, spike-timing-dependent plasticity mechanisms require the online programing of synapses based on the temporal information of spikes transmitted by spiking neurons. In this work, we propose a spintronic synapse with decoupled spike-transmission and programing-current paths. The spintronic synapse consists of a ferromagnet-heavy-metal heterostructure where the programing current through the heavy metal generates spin-orbit torque to modulate the device conductance. Low programing energy and fast programing times demonstrate the efficacy of the proposed device as a nanoelectronic synapse. We perform a simulation study based on an experimentally benchmarked device-simulation framework to demonstrate the interfacing of such spintronic synapses with CMOS neurons and learning circuits operating in the transistor subthreshold region to form a network of spiking neurons that can be utilized for pattern-recognition problems.

  11. Real-time decision fusion for multimodal neural prosthetic devices

    National Research Council Canada - National Science Library

    White, James Robert; Levy, Todd; Bishop, William; Beaty, James D

    2010-01-01

    ...) through which neural activity is decoded into movements. A natural extension of current research is the incorporation of neural activity from multiple modalities to more accurately estimate the user's intent...

  12. Studies in RF power communication, SAR, and temperature elevation in wireless implantable neural interfaces.

    Science.gov (United States)

    Zhao, Yujuan; Tang, Lin; Rennaker, Robert; Hutchens, Chris; Ibrahim, Tamer S

    2013-01-01

    Implantable neural interfaces are designed to provide a high spatial and temporal precision control signal implementing high degree of freedom real-time prosthetic systems. The development of a Radio Frequency (RF) wireless neural interface has the potential to expand the number of applications as well as extend the robustness and longevity compared to wired neural interfaces. However, it is well known that RF signal is absorbed by the body and can result in tissue heating. In this work, numerical studies with analytical validations are performed to provide an assessment of power, heating and specific absorption rate (SAR) associated with the wireless RF transmitting within the human head. The receiving antenna on the neural interface is designed with different geometries and modeled at a range of implanted depths within the brain in order to estimate the maximum receiving power without violating SAR and tissue temperature elevation safety regulations. Based on the size of the designed antenna, sets of frequencies between 1 GHz to 4 GHz have been investigated. As expected the simulations demonstrate that longer receiving antennas (dipole) and lower working frequencies result in greater power availability prior to violating SAR regulations. For a 15 mm dipole antenna operating at 1.24 GHz on the surface of the brain, 730 uW of power could be harvested at the Federal Communications Commission (FCC) SAR violation limit. At approximately 5 cm inside the head, this same antenna would receive 190 uW of power prior to violating SAR regulations. Finally, the 3-D bio-heat simulation results show that for all evaluated antennas and frequency combinations we reach FCC SAR limits well before 1 °C. It is clear that powering neural interfaces via RF is possible, but ultra-low power circuit designs combined with advanced simulation will be required to develop a functional antenna that meets all system requirements.

  13. Neural Operant Conditioning as a Core Mechanism of Brain-Machine Interface Control

    Directory of Open Access Journals (Sweden)

    Yoshio Sakurai

    2016-08-01

    Full Text Available The process of changing the neuronal activity of the brain to acquire rewards in a broad sense is essential for utilizing brain-machine interfaces (BMIs, which is essentially operant conditioning of neuronal activity. Currently, this is also known as neural biofeedback, and it is often referred to as neurofeedback when human brain activity is targeted. In this review, we first illustrate biofeedback and operant conditioning, which are methodological background elements in neural operant conditioning. Then, we introduce research models of neural operant conditioning in animal experiments and demonstrate that it is possible to change the firing frequency and synchronous firing of local neuronal populations in a short time period. We also debate the possibility of the application of neural operant conditioning and its contribution to BMIs.

  14. A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Xiong, Tao; Richardson, Andrew G; Lucas, Timothy H; Chin, Peter S; Etienne-Cummings, Ralph; Tran, Trac D; Van der Spiegel, Jan

    2016-07-18

    Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

  15. A Low Noise Amplifier for Neural Spike Recording Interfaces

    Directory of Open Access Journals (Sweden)

    Jesus Ruiz-Amaya

    2015-09-01

    Full Text Available This paper presents a Low Noise Amplifier (LNA for neural spike recording applications. The proposed topology, based on a capacitive feedback network using a two-stage OTA, efficiently solves the triple trade-off between power, area and noise. Additionally, this work introduces a novel transistor-level synthesis methodology for LNAs tailored for the minimization of their noise efficiency factor under area and noise constraints. The proposed LNA has been implemented in a 130 nm CMOS technology and occupies 0.053 mm-sq. Experimental results show that the LNA offers a noise efficiency factor of 2.16 and an input referred noise of 3.8 μVrms for 1.2 V power supply. It provides a gain of 46 dB over a nominal bandwidth of 192 Hz–7.4 kHz and consumes 1.92 μW. The performance of the proposed LNA has been validated through in vivo experiments with animal models.

  16. A Low Noise Amplifier for Neural Spike Recording Interfaces.

    Science.gov (United States)

    Ruiz-Amaya, Jesus; Rodriguez-Perez, Alberto; Delgado-Restituto, Manuel

    2015-09-30

    This paper presents a Low Noise Amplifier (LNA) for neural spike recording applications. The proposed topology, based on a capacitive feedback network using a two-stage OTA, efficiently solves the triple trade-off between power, area and noise. Additionally, this work introduces a novel transistor-level synthesis methodology for LNAs tailored for the minimization of their noise efficiency factor under area and noise constraints. The proposed LNA has been implemented in a 130 nm CMOS technology and occupies 0.053 mm-sq. Experimental results show that the LNA offers a noise efficiency factor of 2.16 and an input referred noise of 3.8 μVrms for 1.2 V power supply. It provides a gain of 46 dB over a nominal bandwidth of 192 Hz-7.4 kHz and consumes 1.92 μW. The performance of the proposed LNA has been validated through in vivo experiments with animal models.

  17. Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces

    Directory of Open Access Journals (Sweden)

    Miriam eZacksenhouse

    2015-05-01

    Full Text Available Recent experiments with brain-machine-interfaces (BMIs indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal.

  18. Engineering the Brain: Ethical Issues and the Introduction of Neural Devices.

    Science.gov (United States)

    Klein, Eran; Brown, Tim; Sample, Matthew; Truitt, Anjali R; Goering, Sara

    2015-01-01

    Neural devices now under development stand to interact with and alter the human brain in ways that may challenge standard notions of identity, normality, authority, responsibility, privacy and justice.

  19. Uniform and Non-uniform Perturbations in Brain-Machine Interface Task Elicit Similar Neural Strategies.

    Science.gov (United States)

    Armenta Salas, Michelle; Helms Tillery, Stephen I

    2016-01-01

    The neural mechanisms that take place during learning and adaptation can be directly probed with brain-machine interfaces (BMIs). We developed a BMI controlled paradigm that enabled us to enforce learning by introducing perturbations which changed the relationship between neural activity and the BMI's output. We introduced a uniform perturbation to the system, through a visuomotor rotation (VMR), and a non-uniform perturbation, through a decorrelation task. The controller in the VMR was essentially unchanged, but produced an output rotated at 30° from the neurally specified output. The controller in the decorrelation trials decoupled the activity of neurons that were highly correlated in the BMI task by selectively forcing the preferred directions of these cell pairs to be orthogonal. We report that movement errors were larger in the decorrelation task, and subjects needed more trials to restore performance back to baseline. During learning, we measured decreasing trends in preferred direction changes and cross-correlation coefficients regardless of task type. Conversely, final adaptations in neural tunings were dependent on the type controller used (VMR or decorrelation). These results hint to the similar process the neural population might engage while adapting to new tasks, and how, through a global process, the neural system can arrive to individual solutions.

  20. The Use of a Brain Computer Interface Remote Control to Navigate a Recreational Device

    Directory of Open Access Journals (Sweden)

    Shih Chung Chen

    2013-01-01

    Full Text Available People suffering from paralysis caused by serious neural disorder or spinal cord injury also need to be given a means of recreation other than general living aids. Although there have been a proliferation of brain computer interface (BCI applications, developments for recreational activities are scarcely seen. The objective of this study is to develop a BCI-based remote control integrated with commercial devices such as the remote controlled Air Swimmer. The brain is visually stimulated using boxes flickering at preprogrammed frequencies to activate a brain response. After acquiring and processing these brain signals, the frequency of the resulting peak, which corresponds to the user’s selection, is determined by a decision model. Consequently, a command signal is sent from the computer to the wireless remote controller via a data acquisition (DAQ module. A command selection training (CST and simulated path test (SPT were conducted by 12 subjects using the BCI control system and the experimental results showed a recognition accuracy rate of 89.51% and 92.31% for the CST and SPT, respectively. The fastest information transfer rate demonstrated a response of 105 bits/min and 41.79 bits/min for the CST and SPT, respectively. The BCI system was proven to be able to provide a fast and accurate response for a remote controller application.

  1. Polymer neural interface with dual-sided electrodes for neural stimulation and recording.

    Science.gov (United States)

    Tooker, Angela; Tolosa, Vanessa; Shah, Kedar G; Sheth, Heeral; Felix, Sarah; Delima, Terri; Pannu, Satinderpall

    2012-01-01

    We present here a demonstration of a dual-sided, 4-layer metal, polyimide-based electrode array suitable for neural stimulation and recording. The fabrication process outlined here utilizes simple polymer and metal deposition and etching steps, with no potentially harmful backside etches or long exposures to extremely toxic chemicals. These polyimide-based electrode arrays have been tested to ensure they are fully biocompatible and suitable for long-term implantation; their flexibility minimizes the injury and glial scarring that can occur at the implantation site. The creation of dual-side electrode arrays with more than two layers of trace metal enables the fabrication of neural probes with more electrodes without a significant increase in probe size. This allows for more stimulation/recording sites without inducing additional injury and glial scarring.

  2. Neural interface methods and apparatus to provide artificial sensory capabilities to a subject

    Energy Technology Data Exchange (ETDEWEB)

    Buerger, Stephen P.; Olsson, III, Roy H.; Wojciechowski, Kenneth E.; Novick, David K.; Kholwadwala, Deepesh K.

    2017-01-24

    Embodiments of neural interfaces according to the present invention comprise sensor modules for sensing environmental attributes beyond the natural sensory capability of a subject, and communicating the attributes wirelessly to an external (ex-vivo) portable module attached to the subject. The ex-vivo module encodes and communicates the attributes via a transcutaneous inductively coupled link to an internal (in-vivo) module implanted within the subject. The in-vivo module converts the attribute information into electrical neural stimuli that are delivered to a peripheral nerve bundle within the subject, via an implanted electrode. Methods and apparatus according to the invention incorporate implantable batteries to power the in-vivo module allowing for transcutaneous bidirectional communication of low voltage (e.g. on the order of 5 volts) encoded signals as stimuli commands and neural responses, in a robust, low-error rate, communication channel with minimal effects to the subjects' skin.

  3. Neural interface methods and apparatus to provide artificial sensory capabilities to a subject

    Science.gov (United States)

    Buerger, Stephen P.; Olsson, III, Roy H.; Wojciechowski, Kenneth E.; Novick, David K.; Kholwadwala, Deepesh K.

    2017-01-24

    Embodiments of neural interfaces according to the present invention comprise sensor modules for sensing environmental attributes beyond the natural sensory capability of a subject, and communicating the attributes wirelessly to an external (ex-vivo) portable module attached to the subject. The ex-vivo module encodes and communicates the attributes via a transcutaneous inductively coupled link to an internal (in-vivo) module implanted within the subject. The in-vivo module converts the attribute information into electrical neural stimuli that are delivered to a peripheral nerve bundle within the subject, via an implanted electrode. Methods and apparatus according to the invention incorporate implantable batteries to power the in-vivo module allowing for transcutaneous bidirectional communication of low voltage (e.g. on the order of 5 volts) encoded signals as stimuli commands and neural responses, in a robust, low-error rate, communication channel with minimal effects to the subjects' skin.

  4. Interfacing external quantum devices to a universal quantum computer.

    Directory of Open Access Journals (Sweden)

    Antonio A Lagana

    Full Text Available We present a scheme to use external quantum devices using the universal quantum computer previously constructed. We thereby show how the universal quantum computer can utilize networked quantum information resources to carry out local computations. Such information may come from specialized quantum devices or even from remote universal quantum computers. We show how to accomplish this by devising universal quantum computer programs that implement well known oracle based quantum algorithms, namely the Deutsch, Deutsch-Jozsa, and the Grover algorithms using external black-box quantum oracle devices. In the process, we demonstrate a method to map existing quantum algorithms onto the universal quantum computer.

  5. Interfacing external quantum devices to a universal quantum computer.

    Science.gov (United States)

    Lagana, Antonio A; Lohe, Max A; von Smekal, Lorenz

    2011-01-01

    We present a scheme to use external quantum devices using the universal quantum computer previously constructed. We thereby show how the universal quantum computer can utilize networked quantum information resources to carry out local computations. Such information may come from specialized quantum devices or even from remote universal quantum computers. We show how to accomplish this by devising universal quantum computer programs that implement well known oracle based quantum algorithms, namely the Deutsch, Deutsch-Jozsa, and the Grover algorithms using external black-box quantum oracle devices. In the process, we demonstrate a method to map existing quantum algorithms onto the universal quantum computer. © 2011 Lagana et al.

  6. Spintronics using C60 fullerenes: Interface and devices

    NARCIS (Netherlands)

    Tran, T. Lan Ahn

    2013-01-01

    The research described in this thesis focuses on spin polarized transport through thin films of C60 fullerene molecules in vertical spin valves, spin polarized hybridization effects at C60/bcc-Fe(001) interfaces, and the ordering of C60 molecules on epitaxial bcc-Fe(001) thin films. The spin

  7. Ontwikkeling Skid Resistance & Smart Ravelling Interface Testing Device

    NARCIS (Netherlands)

    Khedoe, RN; de Bondt, AH; Long, D.; Villani, M.M.; Scarpas, Athanasios

    De interface van een band van een auto en de weg is belangrijk voor de verschillende interacties. In termen van verkeersveiligheid is stroefheid is een belangrijke factor. Voor de weg is dit niet alleen aanvangsstroefheid, maar ook ontwikkeling van stroefheid is belangrijk. Dit geldt ook voor grip

  8. Development of a Math Input Interface with Flick Operation for Mobile Devices

    Science.gov (United States)

    Nakamura, Yasuyuki; Nakahara, Takahiro

    2016-01-01

    Developing online test environments for e-learning for mobile devices will be useful to increase drill practice opportunities. In order to provide a drill practice environment for calculus using an online math test system, such as STACK, we develop a flickable math input interface that can be easily used on mobile devices. The number of taps…

  9. Non-invasive control interfaces for intention detection in active movement-assistive devices

    NARCIS (Netherlands)

    Lobo-Prat, J.; Kooren, P.N.; Stienen, A.H.A.; Herder, J.L.; Koopman, B.F.J.M.; Veltink, P.H.

    2014-01-01

    Active movement-assistive devices aim to increase the quality of life for patients with neuromusculoskeletal disorders. This technology requires interaction between the user and the device through a control interface that detects the user’s movement intention. Researchers have explored a wide

  10. Lab-on-a-brain: Implantable micro-optical fluidic devices for neural cell analysis in vivo

    Science.gov (United States)

    Takehara, Hiroaki; Nagaoka, Akira; Noguchi, Jun; Akagi, Takanori; Kasai, Haruo; Ichiki, Takanori

    2014-10-01

    The high-resolution imaging of neural cells in vivo has brought about great progress in neuroscience research. Here, we report a novel experimental platform, where the intact brain of a living mouse can be studied with the aid of a surgically implanted micro-optical fluidic device; acting as an interface between neurons and the outer world. The newly developed device provides the functions required for the long-term and high-resolution observation of the fine structures of neurons by two-photon laser scanning microscopy and the microfluidic delivery of chemicals or drugs directly into the brain. A proof-of-concept experiment of single-synapse stimulation by two-photon uncaging of caged glutamate and observation of dendritic spine shrinkage over subsequent days demonstrated a promising use for the present technology.

  11. Testing of ROMPS robot mechanical interfaces and compliant device

    Science.gov (United States)

    Nguyen, Charles C.; Antrazi, Sami S.

    1993-01-01

    The Robot Operated Materials Processing System (ROMPS) has been developed at Goddard Space Flight Center (GSFC) under a flight project to investigate commercially promising in-space material processes and to design reflyable robot automated systems to be used in the above processes for low-cost operations. The ROMPS is currently scheduled for flight in 1994 as a Hitchhiker payload in a Get Away Special (GAS) can. An important component of the ROMPS is a three degree-of-freedom (DOF) robot which will be responsible for carrying out the required tasks of in-space processing of selected materials. This report deals with testing of the mating capability of the ROMPS robot fingers with its various mechanical interfaces. In particular, the test plan will focus on studying the capability of a compliance mechanism mounted on the robot fingers in accommodating misalignments between the robot fingers and the interfaces during the mating. The report is organized as follows: Section 2 represents the main components of the ROMPS robot and briefly describes its operations. Section 3 presents the objectives of the test and outlines the test plan. The testbed comprising a Steward Platform-based high precision manipulator and associated data acquisition and control systems is described in Section 4. Section 5 presents results of numerous experiments conducted to study the mating capability of the robot fingers with its various interfaces under misalignments. The report is concluded with observations and recommendations based on the test results.

  12. Plasticity in memristive devices for Spiking Neural Networks

    Directory of Open Access Journals (Sweden)

    Sylvain eSaïghi

    2015-03-01

    Full Text Available Memristive devices present a new device technology allowing for the realization of compact nonvolatile memories. Some of them are already in the process of industrialization. Additionally, they exhibit complex multilevel and plastic behaviors, which make them good candidates for the implementation of artificial synapses in neuromorphic engineering. However, memristive effects rely on diverse physical mechanisms, and their plastic behaviors differ strongly from one technology to another. Here, we present measurements performed on different memristive devices and the opportunities that they provide. We show that they can be used to implement different learning rules whose properties emerge directly from device physics: real time or accelerated operation, deterministic or stochastic behavior, long term or short term plasticity. We then discuss how such devices might be integrated into a complete architecture. These results highlight that there is no unique way to exploit memristive devices in neuromorphic systems. Understanding and embracing device physics is the key for their optimal use.

  13. The Wiimote and beyond: spatially convenient devices for 3D user interfaces.

    Science.gov (United States)

    Wingrave, Chadwick A; Williamson, Brian; Varcholik, Paul D; Rose, Jeremy; Miller, Andrew; Charbonneau, Emiko; Bott, Jared; LaViola, Joseph J

    2010-01-01

    The Nintendo Wii Remote (Wiimote) has served as an input device in 3D user interfaces (3DUIs) but differs from the general-purpose input hardware typically found in research labs and commercial applications. Despite this, no one has systematically evaluated the device in terms of what it offers 3DUI designers. Experience with the Wiimote indicates that it's an imperfect harbinger of a new class of spatially convenient devices, classified in terms of spatial data, functionality, and commodity design. This tutorial presents techniques for using the Wiimote in 3DUIs. It discusses the device's strengths and how to compensate for its limitations, with implications for future spatially convenient devices.

  14. Interface-engineered templates for molecular spin memory devices

    NARCIS (Netherlands)

    Raman, Karthik V.; Kamerbeek, Alexander M.; Mukherjee, Arup; Atodiresei, Nicolae; Sen, Tamal K.; Lazic, Predrag; Caciuc, Vasile; Michel, Reent; Stalke, Dietmar; Mandal, Swadhin K.; Bluegel, Stefan; Muenzenberg, Markus; Moodera, Jagadeesh S.

    2013-01-01

    The use of molecular spin state as a quantum of information for storage, sensing and computing has generated considerable interest in the context of next-generation data storage and communication devices(1,2), opening avenues for developing multifunctional molecular spintronics(3). Such ideas have

  15. Human Handheld-Device Interaction : An Adaptive User Interface

    NARCIS (Netherlands)

    Fitrianie, S.

    2010-01-01

    The move to smaller, lighter and more powerful (mobile) handheld devices, whe-ther PDAs or smart-phones, looks like a trend that is building up speed. With numerous embedded technologies and wireless connectivity, the drift opens up unlimited opportunities in daily activities that are both more

  16. Interface Electrode Morphology Effect on Carrier Concentration and Trap Defect Density in an Organic Photovoltaic Device.

    Science.gov (United States)

    Kesavan, Arul Varman; Rao, Arun D; Ramamurthy, Praveen C

    2017-08-30

    Formation of Schottky barrier contact (SBC) leads reconstruction of charges at the metal/semiconductor (MS) interface because of the wave function overlap between semiconductor and metal contact. Not only is the Schottky barrier contact formation a signature of the material's work function, but also it is sensitive to the interface trap states, the crystal orientation of the interacting materials, and other interface properties. In this work, the effect of aluminum cathode morphology on the polymer Schottky diode and bulk heterojunction (BHJ) photovoltaic device performance is studied. The electron collecting contacts in Schottky diode and BHJ device have been deposited using aluminum in pellet and nanoparticle forms. Devices fabricated by using Al nanoparticle showed improvement in dark as well as photocurrent density. Significant enhancement in JSC leads to overall improved power conversion efficiency. Enhanced performance in Schottky structured diode and OPV device have been correlated with electrode microstructure and its interface properties such as improved electrically active contact and enhanced charge transport. Electrical conductivity is discussed based on enhanced electrical coherence across organic semiconductor and electrode interface. Therefore, the contribution of electrical enhancement leads to improvement in short-circuit current density (JSC) in BHJ solar cell which is due to reduced trap density. Further, PCE was correlated with the density of interface trap states studied by drive level capacitance profiling technique.

  17. Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganization.

    Directory of Open Access Journals (Sweden)

    Eric A Pohlmeyer

    Full Text Available Brain-machine interface (BMI systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder's neural input space (e.g. neurons appearing or being lost amongst electrode recordings. These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled.

  18. Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganization.

    Science.gov (United States)

    Pohlmeyer, Eric A; Mahmoudi, Babak; Geng, Shijia; Prins, Noeline W; Sanchez, Justin C

    2014-01-01

    Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder's neural input space (e.g. neurons appearing or being lost amongst electrode recordings). These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI) to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled.

  19. Recent Advances in Electrospun Nanofiber Interfaces for Biosensing Devices

    OpenAIRE

    Sapountzi, Eleni; Braiek, Mohamed; Chateaux, Jean-Fran?ois; Jaffrezic-Renault, Nicole; Lagarde, Florence

    2017-01-01

    Electrospinning has emerged as a very powerful method combining efficiency, versatility and low cost to elaborate scalable ordered and complex nanofibrous assemblies from a rich variety of polymers. Electrospun nanofibers have demonstrated high potential for a wide spectrum of applications, including drug delivery, tissue engineering, energy conversion and storage, or physical and chemical sensors. The number of works related to biosensing devices integrating electrospun nanofibers has also i...

  20. Auto-deleting brain machine interface: Error detection using spiking neural activity in the motor cortex.

    Science.gov (United States)

    Even-Chen, Nir; Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

    2015-01-01

    Brain machine interfaces (BMIs) aim to assist people with paralysis by increasing their independence and ability to communicate, e.g., by using a cursor-based virtual keyboard. Current BMI clinical trials are hampered by modest performance that causes selection of wrong characters (errors) and thus reduces achieved typing rate. If it were possible to detect these errors without explicit knowledge of the task goal, this could be used to automatically "undo" wrong selections or even prevent upcoming wrong selections. We decoded imminent or recent errors during closed-loop BMI control from intracortical spiking neural activity. In our experiment, a non-human primate controlled a neurally-driven BMI cursor to acquire targets on a grid, which simulates a virtual keyboard. In offline analyses of this closed-loop BMI control data, we identified motor cortical neural signals indicative of task error occurrence. We were able to detect task outcomes (97% accuracy) and even predict upcoming task outcomes (86% accuracy) using neural activity alone. This novel strategy may help increase the performance and clinical viability of BMIs.

  1. Interface engineering: broadband light and low temperature gas detection abilities using a nano-heterojunction device.

    Science.gov (United States)

    Chang, Chien-Min; Hsu, Ching-Han; Liu, Yi-Wei; Chien, Tzu-Chiao; Sung, Chun-Han; Yeh, Ping-Hung

    2015-12-21

    Herein, we have designed a nano-heterojunction device using interface defects and band bending effects, which can have broadband light detection (from 365-940 nm) and low operating temperature (50 °C) gas detection abilities. The broadband light detection mechanism occurs because of the defects and band bending between the heterojunction interface. We have demonstrated this mechanism using CoSi2/SnO2, CoSi2/TiO2, Ge/SnO2 and Ge/TiO2 nano-heterojunction devices, and all these devices show broadband light detection ability. Furthermore, the nano-heterojunction of the nano-device has a local Joule-heating effect. For gas detection, the results show that the nano-heterojunction device presents a high detection ability. The reset time and sensitivity of the nano-heterojunction device are an order faster and larger than Schottky-contacted devices (previous works), which is due to the local Joule-heating effect between the interface of the nano-heterojunction. Based on the abovementioned idea, we can design diverse nano-devices for widespread use.

  2. An interpenetrating, microstructurable and covalently attached conducting polymer hydrogel for neural interfaces.

    Science.gov (United States)

    Kleber, Carolin; Bruns, Michael; Lienkamp, Karen; Rühe, Jürgen; Asplund, Maria

    2017-08-01

    This study presents a new conducting polymer hydrogel (CPH) system, consisting of the synthetic hydrogel P(DMAA-co-5%MABP-co-2,5%SSNa) and the conducting polymer (CP) poly(3,4-ethylenedioxythiophene) (PEDOT), intended as coating material for neural interfaces. The composite material can be covalently attached to the surface electrode, can be patterned by a photolithographic process to influence selected electrode sites only and forms an interpenetrating network. The hybrid material was characterized using cyclic voltammetry (CV), impedance spectroscopy (EIS) and X-ray photoelectron spectroscopy (XPS), which confirmed a homogeneous distribution of PEDOT throughout all CPH layers. The CPH exhibited a 2,5 times higher charge storage capacity (CSC) and a reduced impedance when compared to the bare hydrogel. Electrochemical stability was proven over at least 1000 redox cycles. Non-toxicity was confirmed using an elution toxicity test together with a neuroblastoma cell-line. The described material shows great promise for surface modification of neural probes making it possible to combine the beneficial properties of the hydrogel with the excellent electronic properties necessary for high quality neural microelectrodes. Conductive polymer hydrogels have emerged as a promising new class of materials to functionalize electrode surfaces for enhanced neural interfaces and drug delivery. Common weaknesses of such systems are delamination from the connection surface, and the lack of suitable patterning methods for confining the gel to the selected electrode site. Various studies have reported on conductive polymer hydrogels addressing one of these challenges. In this study we present a new composite material which offers, for the first time, the unique combination of properties: it can be covalently attached to the substrate, forms an interpenetrating network, shows excellent electrical properties and can be patterned via UV-irradiation through a structured mask. Copyright

  3. Asynchronous BCI and local neural classifiers: an overview of the Adaptive Brain Interface project.

    Science.gov (United States)

    Millán, José del R; Mouriño, Josep

    2003-06-01

    In this communication, we give an overview of our work on an asynchronous brain-computer interface (where the subject makes self-paced decisions on when to switch from one mental task to the next) that responds every 0.5 s. A local neural classifier tries to recognize three different mental tasks; it may also respond "unknown" for uncertain samples as the classifier has incorporated statistical rejection criteria. We report our experience with 15 subjects. We also briefly describe two brain-actuated applications we have developed: a virtual keyboard and a mobile robot (emulating a motorized wheelchair).

  4. Haptic Addition to a Visual Menu Selection Interface Controlled by an In-Vehicle Rotary Device

    OpenAIRE

    Camilla Grane; Peter Bengtsson

    2012-01-01

    Today, several vehicles are equipped with a visual display combined with a haptic rotary device for handling in-vehicle information system tasks while driving. This experimental study investigates whether a haptic addition to a visual interface interferes with or supports secondary task performance and whether haptic information could be used without taking eyes off road. Four interfaces were compared during simulated driving: visual only, partly corresponding visual-haptic, fully correspondi...

  5. NEVESIM: event-driven neural simulation framework with a Python interface.

    Science.gov (United States)

    Pecevski, Dejan; Kappel, David; Jonke, Zeno

    2014-01-01

    NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes) between the neurons at a network level from the implementation of the internal dynamics of individual neurons. In this paper we will present the simulation framework of NEVESIM, its concepts and features, as well as some aspects of the object-oriented design approaches and simulation strategies that were utilized to efficiently implement the concepts and functionalities of the framework. We will also give an overview of the Python user interface, its basic commands and constructs, and also discuss the benefits of integrating NEVESIM with Python. One of the valuable capabilities of the simulator is to simulate exactly and efficiently networks of stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality was implemented as an extension on top of the basic NEVESIM framework. Altogether, the intended purpose of the NEVESIM framework is to provide a basis for further extensions that support simulation of various neural network models incorporating different neuron and synapse types that can potentially also use different simulation strategies.

  6. NEVESIM: Event-Driven Neural Simulation Framework with a Python Interface

    Directory of Open Access Journals (Sweden)

    Dejan ePecevski

    2014-08-01

    Full Text Available NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes between the neurons at a network level from the implementation of the internal dynamics of individual neurons. In this paper we will present the simulation framework of NEVESIM, its concepts and features, as well as some aspects of the object-oriented design approaches and simulation strategies that were utilized to efficiently implement the concepts and functionalities of the framework. We will also give an overview of the Python user interface, its basic commands and constructs, and also discuss the benefits of integrating NEVESIM with Python. One of the valuable capabilities of the simulator is to simulate exactly and efficiently networks of stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality was implemented as an extension on top of the basic NEVESIM framework. Altogether, the intended purpose of the NEVESIM framework is to provide a basis for further extensions that support simulation of various neural network models incorporating different neuron and synapse types that can potentially also use different simulation strategies.

  7. Quantum neural network-based EEG filtering for a brain-computer interface.

    Science.gov (United States)

    Gandhi, Vaibhav; Prasad, Girijesh; Coyle, Damien; Behera, Laxmidhar; McGinnity, Thomas Martin

    2014-02-01

    A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning algorithm enables the RQNN to effectively capture the statistical behavior of the input signal and facilitates the estimation of signal embedded in noise with unknown characteristics. The results from a number of benchmark tests show that simple signals such as dc, staircase dc, and sinusoidal signals embedded within high noise can be accurately filtered and particle swarm optimization can be employed to select model parameters. The RQNN filtering procedure is applied in a two-class motor imagery-based brain-computer interface where the objective was to filter electroencephalogram (EEG) signals before feature extraction and classification to increase signal separability. A two-step inner-outer fivefold cross-validation approach is utilized to select the algorithm parameters subject-specifically for nine subjects. It is shown that the subject-specific RQNN EEG filtering significantly improves brain-computer interface performance compared to using only the raw EEG or Savitzky-Golay filtered EEG across multiple sessions.

  8. A 128-Channel Extreme Learning Machine-Based Neural Decoder for Brain Machine Interfaces.

    Science.gov (United States)

    Chen, Yi; Yao, Enyi; Basu, Arindam

    2016-06-01

    Currently, state-of-the-art motor intention decoding algorithms in brain-machine interfaces are mostly implemented on a PC and consume significant amount of power. A machine learning coprocessor in 0.35- μm CMOS for the motor intention decoding in the brain-machine interfaces is presented in this paper. Using Extreme Learning Machine algorithm and low-power analog processing, it achieves an energy efficiency of 3.45 pJ/MAC at a classification rate of 50 Hz. The learning in second stage and corresponding digitally stored coefficients are used to increase robustness of the core analog processor. The chip is verified with neural data recorded in monkey finger movements experiment, achieving a decoding accuracy of 99.3% for movement type. The same coprocessor is also used to decode time of movement from asynchronous neural spikes. With time-delayed feature dimension enhancement, the classification accuracy can be increased by 5% with limited number of input channels. Further, a sparsity promoting training scheme enables reduction of number of programmable weights by ≈ 2X.

  9. Brain-computer interface devices for patients with paralysis and amputation: a meeting report

    Science.gov (United States)

    Bowsher, K.; Civillico, E. F.; Coburn, J.; Collinger, J.; Contreras-Vidal, J. L.; Denison, T.; Donoghue, J.; French, J.; Getzoff, N.; Hochberg, L. R.; Hoffmann, M.; Judy, J.; Kleitman, N.; Knaack, G.; Krauthamer, V.; Ludwig, K.; Moynahan, M.; Pancrazio, J. J.; Peckham, P. H.; Pena, C.; Pinto, V.; Ryan, T.; Saha, D.; Scharen, H.; Shermer, S.; Skodacek, K.; Takmakov, P.; Tyler, D.; Vasudevan, S.; Wachrathit, K.; Weber, D.; Welle, C. G.; Ye, M.

    2016-04-01

    Objective. The Food and Drug Administration’s (FDA) Center for Devices and Radiological Health (CDRH) believes it is important to help stakeholders (e.g., manufacturers, health-care professionals, patients, patient advocates, academia, and other government agencies) navigate the regulatory landscape for medical devices. For innovative devices involving brain-computer interfaces, this is particularly important. Approach. Towards this goal, on 21 November, 2014, CDRH held an open public workshop on its White Oak, MD campus with the aim of fostering an open discussion on the scientific and clinical considerations associated with the development of brain-computer interface (BCI) devices, defined for the purposes of this workshop as neuroprostheses that interface with the central or peripheral nervous system to restore lost motor or sensory capabilities. Main results. This paper summarizes the presentations and discussions from that workshop. Significance. CDRH plans to use this information to develop regulatory considerations that will promote innovation while maintaining appropriate patient protections. FDA plans to build on advances in regulatory science and input provided in this workshop to develop guidance that provides recommendations for premarket submissions for BCI devices. These proceedings will be a resource for the BCI community during the development of medical devices for consumers.

  10. Expansion of Smartwatch Touch Interface from Touchscreen to Around Device Interface Using Infrared Line Image Sensors

    Directory of Open Access Journals (Sweden)

    Soo-Chul Lim

    2015-07-01

    Full Text Available Touchscreen interaction has become a fundamental means of controlling mobile phones and smartwatches. However, the small form factor of a smartwatch limits the available interactive surface area. To overcome this limitation, we propose the expansion of the touch region of the screen to the back of the user’s hand. We developed a touch module for sensing the touched finger position on the back of the hand using infrared (IR line image sensors, based on the calibrated IR intensity and the maximum intensity region of an IR array. For complete touch-sensing solution, a gyroscope installed in the smartwatch is used to read the wrist gestures. The gyroscope incorporates a dynamic time warping gesture recognition algorithm for eliminating unintended touch inputs during the free motion of the wrist while wearing the smartwatch. The prototype of the developed sensing module was implemented in a commercial smartwatch, and it was confirmed that the sensed positional information of the finger when it was used to touch the back of the hand could be used to control the smartwatch graphical user interface. Our system not only affords a novel experience for smartwatch users, but also provides a basis for developing other useful interfaces.

  11. Control Board Digital Interface Input Devices – Touchscreen, Trackpad, or Mouse?

    Energy Technology Data Exchange (ETDEWEB)

    Thomas A. Ulrich; Ronald L. Boring; Roger Lew

    2015-08-01

    The authors collaborated with a power utility to evaluate input devices for use in the human system interface (HSI) for a new digital Turbine Control System (TCS) at a nuclear power plant (NPP) undergoing a TCS upgrade. A standalone dynamic software simulation of the new digital TCS and a mobile kiosk were developed to conduct an input device study to evaluate operator preference and input device effectiveness. The TCS software presented the anticipated HSI for the TCS and mimicked (i.e., simulated) the turbine systems’ responses to operator commands. Twenty-four licensed operators from the two nuclear power units participated in the study. Three input devices were tested: a trackpad, mouse, and touchscreen. The subjective feedback from the survey indicates the operators preferred the touchscreen interface. The operators subjectively rated the touchscreen as the fastest and most comfortable input device given the range of tasks they performed during the study, but also noted a lack of accuracy for selecting small targets. The empirical data suggest the mouse input device provides the most consistent performance for screen navigation and manipulating on screen controls. The trackpad input device was both empirically and subjectively found to be the least effective and least desired input device.

  12. Fabrication and Microassembly of a mm-Sized Floating Probe for a Distributed Wireless Neural Interface

    Directory of Open Access Journals (Sweden)

    Pyungwoo Yeon

    2016-09-01

    Full Text Available A new class of wireless neural interfaces is under development in the form of tens to hundreds of mm-sized untethered implants, distributed across the target brain region(s. Unlike traditional interfaces that are tethered to a centralized control unit and suffer from micromotions that may damage the surrounding neural tissue, the new free-floating wireless implantable neural recording (FF-WINeR probes will be stand-alone, directly communicating with an external interrogator. Towards development of the FF-WINeR, in this paper we describe the micromachining, microassembly, and hermetic packaging of 1-mm3 passive probes, each of which consists of a thinned micromachined silicon die with a centered Ø(diameter 130 μm through-hole, an Ø81 μm sharpened tungsten electrode, a 7-turn gold wire-wound coil wrapped around the die, two 0201 surface mount capacitors on the die, and parylene-C/Polydimethylsiloxane (PDMS coating. The fabricated passive probe is tested under a 3-coil inductive link to evaluate power transfer efficiency (PTE and power delivered to a load (PDL for feasibility assessment. The minimum PTE/PDL at 137 MHz were 0.76%/240 μW and 0.6%/191 μW in the air and lamb head medium, respectively, with coil separation of 2.8 cm and 9 kΩ receiver (Rx loading. Six hermetically sealed probes went through wireless hermeticity testing, using a 2-coil inductive link under accelerated lifetime testing condition of 85 °C, 1 atm, and 100%RH. The mean-time-to-failure (MTTF of the probes at 37 °C is extrapolated to be 28.7 years, which is over their lifetime.

  13. An easy-to-use microfluidic interconnection system to create quick and reversibly interfaced simple microfluidic devices

    DEFF Research Database (Denmark)

    Pfreundt, Andrea; Andersen, Karsten Brandt; Dimaki, Maria

    2015-01-01

    The presented microfluidic interconnection system provides an alternative for the individual interfacing of simple microfluidic devices fabricated in polymers such as polymethylmethacrylate, polycarbonate and cyclic olefin polymer. A modification of the device inlet enables the direct attachment...

  14. Fostering learners' interaction with content: A learner-centered mobile device interface

    Science.gov (United States)

    Abdous, M.

    2015-12-01

    With the ever-increasing omnipresence of mobile devices in student life, leveraging smart devices to foster students' interaction with course content is critical. Following a learner-centered design iterative approach, we designed a mobile interface that may enable learners to access and interact with online course content efficiently and intuitively. Our design process leveraged recent technologies, such as bootstrap, Google's Material Design, HTML5, and JavaScript to design an intuitive, efficient, and portable mobile interface with a variety of built-in features, including context sensitive bookmarking, searching, progress tracking, captioning, and transcript display. The mobile interface also offers students the ability to ask context-related questions and to complete self-checks as they watch audio/video presentations. Our design process involved ongoing iterative feedback from learners, allowing us to refine and tweak the interface to provide learners with a unified experience across platforms and devices. The innovative combination of technologies built around well-structured and well-designed content seems to provide an effective learning experience to mobile learners. Early feedback indicates a high level of satisfaction with the interface's efficiency, intuitiveness, and robustness from both students and faculty.

  15. Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems

    Directory of Open Access Journals (Sweden)

    Sun-Il Chang

    2018-01-01

    Full Text Available This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM module. The core integrated circuit (IC consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm2 and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µVrms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW.

  16. Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems.

    Science.gov (United States)

    Chang, Sun-Il; Park, Sung-Yun; Yoon, Euisik

    2018-01-17

    This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG) recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM) module. The core integrated circuit (IC) consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC) with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm² and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µVrms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW.

  17. A game for emotional regulation in adolescents : The (body) interface device matters

    NARCIS (Netherlands)

    Dolores Vara, M.; Baños, R.M.; Rasal, P.; Rodríguez, A.; Rey, B.; Wrzesien, M.; Alcañiz, M.

    The aim of this study is to evaluate the role of the type of interface device in the efficacy of a serious game that teaches emotional regulation (ER) strategies in a non-clinical sample of adolescents. We conducted a between-participants experiment in which participants (N = 61) played a

  18. Influence of interface recombination in light emission from lateral Si-based light emitting devices

    NARCIS (Netherlands)

    Le Minh, P.; Hoang, T.; Holleman, J.; Schmitz, Jurriaan

    2006-01-01

    The influence of interface recombination on the electroluminescence profile of a lateral p+/p/n+ light emitting diode fabricated on Silicon On Insulator (SOI) materials has been experimentally investigated. Our device resembles a MOSFET fabricated on SOI, except that the source region has opposite

  19. LONG-TERM RELIABILITY OF AL2O3 AND PARYLENE C BILAYER ENCAPSULATED UTAH ELECTRODE ARRAY BASED NEURAL INTERFACES FOR CHRONIC IMPLANTATION

    Science.gov (United States)

    Xie, Xianzong; Rieth, Loren; Williams, Layne; Negi, Sandeep; Bhandari, Rajmohan; Caldwell, Ryan; Sharma, Rohit; Tathireddy, Prashant; Solzbacher, Florian

    2014-01-01

    Objective We focus on improving the long-term stability and functionality of neural interfaces for chronic implantation by using bilayer encapsulation. Approach We evaluated the long-term reliability of Utah electrode array (UEA) based neural interfaces encapsulated by 52 nm of atomic layer deposited (ALD) Al2O3 and 6 μm of Parylene C bilayer, and compared these to devices with the baseline Parylene-only encapsulation. Three variants of arrays including wired, wireless, and active UEAs were used to evaluate this bilayer encapsulation scheme, and were immersed in phosphate buffered saline (PBS) at 57 °C for accelerated lifetime testing. Main results The median tip impedance of the bilayer encapsulated wired UEAs increased from 60 kΩ to 160 kΩ during the 960 days of equivalent soak testing at 37 °C, the opposite trend as typically observed for Parylene encapsulated devices. The loss of the iridium oxide tip metallization and etching of the silicon tip in PBS solution contributed to the increase of impedance. The lifetime of fully integrated wireless UEAs was also tested using accelerated lifetime measurement techniques. The bilayer coated devices had stable power-up frequencies at ~910 MHz and constant RF signal strength of -50 dBm during up to 1044 days (still under testing) of equivalent soaking time at 37 °C. This is a significant improvement over the lifetime of ~ 100 days achieved with Parylene-only encapsulation at 37 °C. The preliminary samples of bilayer coated active UEAs with a flip-chip bonded ASIC chip had a steady current draw of ~ 3 mA during 228 days of soak testing at 37 °C. An increase in current draw has been consistently correlated to device failures, so is a sensitive metric for their lifetime. Significance The trends of increasing electrode impedance of wired devices and performance stability of wireless and active devices support the significantly greater encapsulation performance of this bilayer encapsulation compared with Parylene

  20. A bio-inspired memory device based on interfacing Physarum polycephalum with an organic semiconductor

    Energy Technology Data Exchange (ETDEWEB)

    Romeo, Agostino; Dimonte, Alice; Tarabella, Giuseppe; D’Angelo, Pasquale, E-mail: dangelo@imem.cnr.it, E-mail: iannotta@imem.cnr.it; Erokhin, Victor; Iannotta, Salvatore, E-mail: dangelo@imem.cnr.it, E-mail: iannotta@imem.cnr.it [IMEM-CNR, Institute of Materials for Electronics and Magnetism-National Research Council, Parma 43124 (Italy)

    2015-01-01

    The development of devices able to detect and record ion fluxes is a crucial point in order to understand the mechanisms that regulate communication and life of organisms. Here, we take advantage of the combined electronic and ionic conduction properties of a conducting polymer to develop a hybrid organic/living device with a three-terminal configuration, using the Physarum polycephalum Cell (PPC) slime mould as a living bio-electrolyte. An over-oxidation process induces a conductivity switch in the polymer, due to the ionic flux taking place at the PPC/polymer interface. This behaviour endows a current-depending memory effect to the device.

  1. Neural substrates for semantic memory of familiar songs: is there an interface between lyrics and melodies?

    Directory of Open Access Journals (Sweden)

    Yoko Saito

    Full Text Available Findings on song perception and song production have increasingly suggested that common but partially distinct neural networks exist for processing lyrics and melody. However, the neural substrates of song recognition remain to be investigated. The purpose of this study was to examine the neural substrates involved in the accessing "song lexicon" as corresponding to a representational system that might provide links between the musical and phonological lexicons using positron emission tomography (PET. We exposed participants to auditory stimuli consisting of familiar and unfamiliar songs presented in three ways: sung lyrics (song, sung lyrics on a single pitch (lyrics, and the sung syllable 'la' on original pitches (melody. The auditory stimuli were designed to have equivalent familiarity to participants, and they were recorded at exactly the same tempo. Eleven right-handed nonmusicians participated in four conditions: three familiarity decision tasks using song, lyrics, and melody and a sound type decision task (control that was designed to engage perceptual and prelexical processing but not lexical processing. The contrasts (familiarity decision tasks versus control showed no common areas of activation between lyrics and melody. This result indicates that essentially separate neural networks exist in semantic memory for the verbal and melodic processing of familiar songs. Verbal lexical processing recruited the left fusiform gyrus and the left inferior occipital gyrus, whereas melodic lexical processing engaged the right middle temporal sulcus and the bilateral temporo-occipital cortices. Moreover, we found that song specifically activated the left posterior inferior temporal cortex, which may serve as an interface between verbal and musical representations in order to facilitate song recognition.

  2. Haptic Addition to a Visual Menu Selection Interface Controlled by an In-Vehicle Rotary Device

    Directory of Open Access Journals (Sweden)

    Camilla Grane

    2012-01-01

    Full Text Available Today, several vehicles are equipped with a visual display combined with a haptic rotary device for handling in-vehicle information system tasks while driving. This experimental study investigates whether a haptic addition to a visual interface interferes with or supports secondary task performance and whether haptic information could be used without taking eyes off road. Four interfaces were compared during simulated driving: visual only, partly corresponding visual-haptic, fully corresponding visual-haptic, and haptic only. Secondary task performance and subjective mental workload were measured. Additionally, the participants were interviewed. It was found that some haptic support improved performance. However, when more haptic information was used, the results diverged in terms of task completion time and interface comprehension. Some participants did not sense all haptics provided, some did not comprehend the correspondence between the haptic and visual interfaces, and some did. Interestingly, the participants managed to complete the tasks when using haptic-only information.

  3. A multimodal interface device for online board games designed for sight-impaired people.

    Science.gov (United States)

    Caporusso, Nicholas; Mkrtchyan, Lusine; Badia, Leonardo

    2010-03-01

    Online games between remote opponents playing over computer networks are becoming a common activity of everyday life. However, computer interfaces for board games are usually based on the visual channel. For example, they require players to check their moves on a video display and interact by using pointing devices such as a mouse. Hence, they are not suitable for visually impaired people. The present paper discusses a multipurpose system that allows especially blind and deafblind people playing chess or other board games over a network, therefore reducing their disability barrier. We describe and benchmark a prototype of a special interactive haptic device for online gaming providing a dual tactile feedback. The novel interface of this proposed device is able to guarantee not only a better game experience for everyone but also an improved quality of life for sight-impaired people.

  4. Improved Selectivity From a Wavelength Addressable Device for Wireless Stimulation of Neural Tissue

    Directory of Open Access Journals (Sweden)

    Elif Ç. Seymour

    2014-02-01

    Full Text Available Electrical neural stimulation with micro electrodes is a promising technique for restoring lost functions in the central nervous system as a result of injury or disease. One of the problems related to current neural stimulators is the tissue response due to the connecting wires and the presence of a rigid electrode inside soft neural tissue. We have developed a novel, optically activated, microscale photovoltaic neurostimulator based on a custom layered compound semiconductor heterostructure that is both wireless and has a comparatively small volume. Optical activation provides a wireless means of energy transfer to the neurostimulator, eliminating wires and the associated complications. This neurostimulator was shown to evoke action potentials and a functional motor response in the rat spinal cord. In this work, we extend our design to include wavelength selectivity and thus allowing independent activation of devices. As a proof of concept, we fabricated two different microscale devices with different spectral responsivities in the near-infrared region. We assessed the improved addressability of individual devices via wavelength selectivity as compared to spatial selectivity alone through on-bench optical measurements of the devices in combination with an in vivo light intensity profile in the rat cortex obtained in a previous study. We show that wavelength selectivity improves the individual addressability of the floating stimulators, thus increasing the number of devices that can be implanted in close proximity to each other.

  5. Chitosan to Connect Biology to Electronics: Fabricating the Bio-Device Interface and Communicating Across This Interface

    Directory of Open Access Journals (Sweden)

    Eunkyoung Kim

    2014-12-01

    Full Text Available Individually, advances in microelectronics and biology transformed the way we live our lives. However, there remain few examples in which biology and electronics have been interfaced to create synergistic capabilities. We believe there are two major challenges to the integration of biological components into microelectronic systems: (i assembly of the biological components at an electrode address, and (ii communication between the assembled biological components and the underlying electrode. Chitosan possesses a unique combination of properties to meet these challenges and serve as an effective bio-device interface material. For assembly, chitosan’s pH-responsive film-forming properties allow it to “recognize” electrode-imposed signals and respond by self-assembling as a stable hydrogel film through a cathodic electrodeposition mechanism. A separate anodic electrodeposition mechanism was recently reported and this also allows chitosan hydrogel films to be assembled at an electrode address. Protein-based biofunctionality can be conferred to electrodeposited films through a variety of physical, chemical and biological methods. For communication, we are investigating redox-active catechol-modified chitosan films as an interface to bridge redox-based communication between biology and an electrode. Despite significant progress over the last decade, many questions still remain which warrants even deeper study of chitosan’s structure, properties, and functions.

  6. Improvement of design of a surgical interface using an eye tracking device.

    Science.gov (United States)

    Erol Barkana, Duygun; Açık, Alper; Duru, Dilek Goksel; Duru, Adil Deniz

    2014-05-07

    Surgical interfaces are used for helping surgeons in interpretation and quantification of the patient information, and for the presentation of an integrated workflow where all available data are combined to enable optimal treatments. Human factors research provides a systematic approach to design user interfaces with safety, accuracy, satisfaction and comfort. One of the human factors research called user-centered design approach is used to develop a surgical interface for kidney tumor cryoablation. An eye tracking device is used to obtain the best configuration of the developed surgical interface. Surgical interface for kidney tumor cryoablation has been developed considering the four phases of user-centered design approach, which are analysis, design, implementation and deployment. Possible configurations of the surgical interface, which comprise various combinations of menu-based command controls, visual display of multi-modal medical images, 2D and 3D models of the surgical environment, graphical or tabulated information, visual alerts, etc., has been developed. Experiments of a simulated cryoablation of a tumor task have been performed with surgeons to evaluate the proposed surgical interface. Fixation durations and number of fixations at informative regions of the surgical interface have been analyzed, and these data are used to modify the surgical interface. Eye movement data has shown that participants concentrated their attention on informative regions more when the number of displayed Computer Tomography (CT) images has been reduced. Additionally, the time required to complete the kidney tumor cryoablation task by the participants had been decreased with the reduced number of CT images. Furthermore, the fixation durations obtained after the revision of the surgical interface are very close to what is observed in visual search and natural scene perception studies suggesting more efficient and comfortable interaction with the surgical interface. The

  7. Neural prostheses for vision: designing a functional interface with retinal neurons.

    Science.gov (United States)

    Hetling, John R; Baig-Silva, Monica S

    2004-01-01

    A number of prevalent eye diseases exist which may lead to partial or total blindness, and for which there are currently no cures or means by which to restore lost sight. Based on recent progress, it has become apparent that artificial prosthetic devices, which would use electrical stimulation of neurons in the visual pathway to elicit visual percepts, are likely to some day become a viable treatment for patients blinded by these diseases. A number of recent scientific reviews have summarized general functional electrical stimulation (FES) approaches related to the visual system, and many of the technical considerations regarding fabrication, biocompatibility, stimulation thresholds and electrotoxicity. This review will address a principal outstanding question in retinal prosthesis development: the design and implementation of a functional interface with the retina. A functional interface between electrodes and retinal neurons will be stable, biocompatible, and will convey useful information to the visual system. Several parameters related to both the artificial and biological aspects of the interface must be considered; this paper will emphasize electrode design. Additional issues central to the development of prosthesis interface design, including retinal physiology, eye diseases, and existing animal models of retinal degeneration, are also summarized.

  8. Studying the glial cell response to biomaterials and surface topography for improving the neural electrode interface

    Science.gov (United States)

    Ereifej, Evon S.

    Neural electrode devices hold great promise to help people with the restoration of lost functions, however, research is lacking in the biomaterial design of a stable, long-term device. Current devices lack long term functionality, most have been found unable to record neural activity within weeks after implantation due to the development of glial scar tissue (Polikov et al., 2006; Zhong and Bellamkonda, 2008). The long-term effect of chronically implanted electrodes is the formation of a glial scar made up of reactive astrocytes and the matrix proteins they generate (Polikov et al., 2005; Seil and Webster, 2008). Scarring is initiated when a device is inserted into brain tissue and is associated with an inflammatory response. Activated astrocytes are hypertrophic, hyperplastic, have an upregulation of intermediate filaments GFAP and vimentin expression, and filament formation (Buffo et al., 2010; Gervasi et al., 2008). Current approaches towards inhibiting the initiation of glial scarring range from altering the geometry, roughness, size, shape and materials of the device (Grill et al., 2009; Kotov et al., 2009; Kotzar et al., 2002; Szarowski et al., 2003). Literature has shown that surface topography modifications can alter cell alignment, adhesion, proliferation, migration, and gene expression (Agnew et al., 1983; Cogan et al., 2005; Cogan et al., 2006; Merrill et al., 2005). Thus, the goals of the presented work are to study the cellular response to biomaterials used in neural electrode fabrication and assess surface topography effects on minimizing astrogliosis. Initially, to examine astrocyte response to various materials used in neural electrode fabrication, astrocytes were cultured on platinum, silicon, PMMA, and SU-8 surfaces, with polystyrene as the control surface. Cell proliferation, viability, morphology and gene expression was measured for seven days in vitro. Results determined the cellular characteristics, reactions and growth rates of astrocytes

  9. Implications of the Dependence of Neuronal Activity on Neural Network States for the Design of Brain-Machine Interfaces.

    Science.gov (United States)

    Panzeri, Stefano; Safaai, Houman; De Feo, Vito; Vato, Alessandro

    2016-01-01

    Brain-machine interfaces (BMIs) can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state) that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brain. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

  10. Implications of the dependence of neuronal activity on neural network states for the design of brain-machine interfaces

    Directory of Open Access Journals (Sweden)

    Stefano ePanzeri

    2016-04-01

    Full Text Available Brain-machine interfaces (BMIs can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brains. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

  11. Convolutional neural networks for P300 detection with application to brain-computer interfaces.

    Science.gov (United States)

    Cecotti, Hubert; Gräser, Axel

    2011-03-01

    A Brain-Computer Interface (BCI) is a specific type of human-computer interface that enables the direct communication between human and computers by analyzing brain measurements. Oddball paradigms are used in BCI to generate event-related potentials (ERPs), like the P300 wave, on targets selected by the user. A P300 speller is based on this principle, where the detection of P300 waves allows the user to write characters. The P300 speller is composed of two classification problems. The first classification is to detect the presence of a P300 in the electroencephalogram (EEG). The second one corresponds to the combination of different P300 responses for determining the right character to spell. A new method for the detection of P300 waves is presented. This model is based on a convolutional neural network (CNN). The topology of the network is adapted to the detection of P300 waves in the time domain. Seven classifiers based on the CNN are proposed: four single classifiers with different features set and three multiclassifiers. These models are tested and compared on the Data set II of the third BCI competition. The best result is obtained with a multiclassifier solution with a recognition rate of 95.5 percent, without channel selection before the classification. The proposed approach provides also a new way for analyzing brain activities due to the receptive field of the CNN models.

  12. Characterization of Organic Solar Cell Devices and their Interfaces under Degradation: Imaging, Electrical and Mechanical Methods

    DEFF Research Database (Denmark)

    Corazza, Michael

    the natural ecosystem and maybe even the destiny of Earth. Human evolution does not mean only advanced technological development, but also deeper consciousness and responsibility for the next generations to come. Everything on Earth exists because of the Sun: heat, wind, life... everything. Therefore, solar...... techniques were also employed in order to study the effect of degradation on the device structure and its interfaces. This was done by exploiting different techniques that measured different properties of the device: mechanical, imaging, and electrical. Mechanical characterization of roll-to-roll processed...

  13. Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices

    Directory of Open Access Journals (Sweden)

    Tayfun Gokmen

    2017-10-01

    Full Text Available In a previous work we have detailed the requirements for obtaining maximal deep learning performance benefit by implementing fully connected deep neural networks (DNN in the form of arrays of resistive devices. Here we extend the concept of Resistive Processing Unit (RPU devices to convolutional neural networks (CNNs. We show how to map the convolutional layers to fully connected RPU arrays such that the parallelism of the hardware can be fully utilized in all three cycles of the backpropagation algorithm. We find that the noise and bound limitations imposed by the analog nature of the computations performed on the arrays significantly affect the training accuracy of the CNNs. Noise and bound management techniques are presented that mitigate these problems without introducing any additional complexity in the analog circuits and that can be addressed by the digital circuits. In addition, we discuss digitally programmable update management and device variability reduction techniques that can be used selectively for some of the layers in a CNN. We show that a combination of all those techniques enables a successful application of the RPU concept for training CNNs. The techniques discussed here are more general and can be applied beyond CNN architectures and therefore enables applicability of the RPU approach to a large class of neural network architectures.

  14. Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices

    Science.gov (United States)

    Gokmen, Tayfun; Onen, Murat; Haensch, Wilfried

    2017-01-01

    In a previous work we have detailed the requirements for obtaining maximal deep learning performance benefit by implementing fully connected deep neural networks (DNN) in the form of arrays of resistive devices. Here we extend the concept of Resistive Processing Unit (RPU) devices to convolutional neural networks (CNNs). We show how to map the convolutional layers to fully connected RPU arrays such that the parallelism of the hardware can be fully utilized in all three cycles of the backpropagation algorithm. We find that the noise and bound limitations imposed by the analog nature of the computations performed on the arrays significantly affect the training accuracy of the CNNs. Noise and bound management techniques are presented that mitigate these problems without introducing any additional complexity in the analog circuits and that can be addressed by the digital circuits. In addition, we discuss digitally programmable update management and device variability reduction techniques that can be used selectively for some of the layers in a CNN. We show that a combination of all those techniques enables a successful application of the RPU concept for training CNNs. The techniques discussed here are more general and can be applied beyond CNN architectures and therefore enables applicability of the RPU approach to a large class of neural network architectures.

  15. Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices.

    Science.gov (United States)

    Gokmen, Tayfun; Onen, Murat; Haensch, Wilfried

    2017-01-01

    In a previous work we have detailed the requirements for obtaining maximal deep learning performance benefit by implementing fully connected deep neural networks (DNN) in the form of arrays of resistive devices. Here we extend the concept of Resistive Processing Unit (RPU) devices to convolutional neural networks (CNNs). We show how to map the convolutional layers to fully connected RPU arrays such that the parallelism of the hardware can be fully utilized in all three cycles of the backpropagation algorithm. We find that the noise and bound limitations imposed by the analog nature of the computations performed on the arrays significantly affect the training accuracy of the CNNs. Noise and bound management techniques are presented that mitigate these problems without introducing any additional complexity in the analog circuits and that can be addressed by the digital circuits. In addition, we discuss digitally programmable update management and device variability reduction techniques that can be used selectively for some of the layers in a CNN. We show that a combination of all those techniques enables a successful application of the RPU concept for training CNNs. The techniques discussed here are more general and can be applied beyond CNN architectures and therefore enables applicability of the RPU approach to a large class of neural network architectures.

  16. 25th anniversary article: organic electronics marries photochromism: generation of multifunctional interfaces, materials, and devices.

    Science.gov (United States)

    Orgiu, Emanuele; Samorì, Paolo

    2014-03-26

    Organic semiconductors have garnered significant interest as key components for flexible, low-cost, and large-area electronics. Hitherto, both materials and processing thereof seems to head towards a mature technology which shall ultimately meet expectations and efforts built up over the past years. However, by its own organic electronics cannot compete or complement the silicon-based electronics in integrating multiple functions in a small area unless novel solutions are brought into play. Photochromic molecules are small organic molecules able to undergo reversible photochemical isomerization between (at least) two (meta)stable states which exhibit markedly different properties. They can be embedded as additional component in organic-based materials ready to be exploited in devices such as OLEDs, OFETs, and OLETs. The structurally controlled incorporation of photochromic molecules can be done at various interfaces of a device, including the electrode/semiconductor or dielectric/semiconductor interface, or even as a binary mixture in the active layer, in order to impart a light responsive nature to the device. This can be accomplished by modulating via a light stimulus fundamental physico-chemical properties such as charge injection and transport in the device. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Wireless sEMG-Based Body-Machine Interface for Assistive Technology Devices.

    Science.gov (United States)

    Fall, Cheikh Latyr; Gagnon-Turcotte, Gabriel; Dube, Jean-Francois; Gagne, Jean Simon; Delisle, Yanick; Campeau-Lecours, Alexandre; Gosselin, Clement; Gosselin, Benoit

    2017-07-01

    Assistive technology (AT) tools and appliances are being more and more widely used and developed worldwide to improve the autonomy of people living with disabilities and ease the interaction with their environment. This paper describes an intuitive and wireless surface electromyography (sEMG) based body-machine interface for AT tools. Spinal cord injuries at C5-C8 levels affect patients' arms, forearms, hands, and fingers control. Thus, using classical AT control interfaces (keypads, joysticks, etc.) is often difficult or impossible. The proposed system reads the AT users' residual functional capacities through their sEMG activity, and converts them into appropriate commands using a threshold-based control algorithm. It has proven to be suitable as a control alternative for assistive devices and has been tested with the JACO arm, an articulated assistive device of which the vocation is to help people living with upper-body disabilities in their daily life activities. The wireless prototype, the architecture of which is based on a 3-channel sEMG measurement system and a 915-MHz wireless transceiver built around a low-power microcontroller, uses low-cost off-the-shelf commercial components. The embedded controller is compared with JACO's regular joystick-based interface, using combinations of forearm, pectoral, masseter, and trapeze muscles. The measured index of performance values is 0.88, 0.51, and 0.41 bits/s, respectively, for correlation coefficients with the Fitt's model of 0.75, 0.85, and 0.67. These results demonstrate that the proposed controller offers an attractive alternative to conventional interfaces, such as joystick devices, for upper-body disabled people using ATs such as JACO.

  18. Producing 3D neuronal networks in hydrogels for living bionic device interfaces.

    Science.gov (United States)

    Aregueta-Robles, Ulises A; Lim, Khoon S; Martens, Penny J; Lovell, Nigel H; Poole-Warren, Laura A; Green, Rylie

    2015-01-01

    Hydrogels hold significant promise for supporting cell based therapies in the field of bioelectrodes. It has been proposed that tissue engineering principles can be used to improve the integration of neural interfacing electrodes. Degradable hydrogels based on poly (vinyl alcohol) functionalised with tyramine (PVA-Tyr) have been shown to support covalent incorporation of non-modified tyrosine rich proteins within synthetic hydrogels. PVA-Tyr crosslinked with such proteins, were explored as a scaffold for supporting development of neural tissue in a three dimensional (3D) environment. In this study a model neural cell line (PC12) and glial accessory cell line, Schwann cell (SC) were encapsulated in PVA-Tyr crosslinked with gelatin and sericin. Specifically, this study aimed to examine the growth and function of SC and PC12 co-cultures when translated from a two dimensional (2D) environment to a 3D environment. PC12 differentiation was successfully promoted in both 2D and 3D at 25 days post-culture. SC encapsulated as a single cell line and in co-culture were able to produce both laminin and collagen-IV which are required to support neuronal development. Neurite outgrowth in the 3D environment was confirmed by immunocytochemical staining. PVA-Tyr/sericin/gelatin hydrogel showed mechanical properties similar to nerve tissue elastic modulus. It is suggested that the mechanical properties of the PVA-Tyr hydrogels with native protein components are providing with a compliant substrate that can be used to support the survival and differentiation of neural networks.

  19. Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces

    Directory of Open Access Journals (Sweden)

    Hossein Bashashati

    2017-07-01

    Full Text Available Classification of EEG signals in self-paced Brain Computer Interfaces (BCI is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing the mental task, the user’s brain goes through several well-defined internal state changes. Applying appropriate classifiers that can capture these state changes and exploit the temporal correlation in EEG data can enhance the performance of the BCI. In this paper, we propose an ensemble learning approach for self-paced BCIs. We use Bayesian optimization to train several different classifiers on different parts of the BCI hyper- parameter space. We call each of these classifiers Neural Network Conditional Random Field (NNCRF. NNCRF is a combination of a neural network and conditional random field (CRF. As in the standard CRF, NNCRF is able to model the correlation between adjacent EEG samples. However, NNCRF can also model the nonlinear dependencies between the input and the output, which makes it more powerful than the standard CRF. We compare the performance of our algorithm to those of three popular sequence labeling algorithms (Hidden Markov Models, Hidden Markov Support Vector Machines and CRF, and to two classical classifiers (Logistic Regression and Support Vector Machines. The classifiers are compared for the two cases: when the ensemble learning approach is not used and when it is. The data used in our studies are those from the BCI competition IV and the SM2 dataset. We show that our algorithm is considerably superior to the other approaches in terms of the Area Under the Curve (AUC of the BCI system.

  20. DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

    Science.gov (United States)

    Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

    2014-01-01

    Objective Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than three, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance DataHigh was developed to fulfill a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity. PMID:24216250

  1. Is Neural Activity Detected by ERP-Based Brain-Computer Interfaces Task Specific?

    Directory of Open Access Journals (Sweden)

    Markus A Wenzel

    Full Text Available Brain-computer interfaces (BCIs that are based on event-related potentials (ERPs can estimate to which stimulus a user pays particular attention. In typical BCIs, the user silently counts the selected stimulus (which is repeatedly presented among other stimuli in order to focus the attention. The stimulus of interest is then inferred from the electroencephalogram (EEG. Detecting attention allocation implicitly could be also beneficial for human-computer interaction (HCI, because it would allow software to adapt to the user's interest. However, a counting task would be inappropriate for the envisaged implicit application in HCI. Therefore, the question was addressed if the detectable neural activity is specific for silent counting, or if it can be evoked also by other tasks that direct the attention to certain stimuli.Thirteen people performed a silent counting, an arithmetic and a memory task. The tasks required the subjects to pay particular attention to target stimuli of a random color. The stimulus presentation was the same in all three tasks, which allowed a direct comparison of the experimental conditions.Classifiers that were trained to detect the targets in one task, according to patterns present in the EEG signal, could detect targets in all other tasks (irrespective of some task-related differences in the EEG.The neural activity detected by the classifiers is not strictly task specific but can be generalized over tasks and is presumably a result of the attention allocation or of the augmented workload. The results may hold promise for the transfer of classification algorithms from BCI research to implicit relevance detection in HCI.

  2. DLTS Analysis and Interface Engineering of Solution Route Fabricated Zirconia Based MIS Devices Using Plasma Treatment

    Science.gov (United States)

    Kumar, Arvind; Mondal, Sandip; Koteswara Rao, K. S. R.

    2018-02-01

    In this work, we have fabricated low-temperature sol-gel spin-coated and oxygen (O2) plasma treated ZrO2 thin film-based metal-insulator-semiconductor devices. To understand the impact of plasma treatment on the Si/ZrO2 interface, deep level transient spectroscopy measurements were performed. It is reported that the interface state density ( D it) comes down to 7.1 × 1010 eV-1 cm-2 from 4 × 1011 eV-1 cm-2, after plasma treatment. The reduction in D it is around five times and can be attributed to the passivation of oxygen vacancies near the Si/ZrO2 interface, as they try to relocate near the interface. The energy level position ( E T) of interfacial traps is estimated to be 0.36 eV below the conduction band edge. The untreated ZrO2 film displayed poor leakage behavior due to the presence of several traps within the film and at the interface; O2 plasma treated films show improved leakage current density as they have been reduced from 5.4 × 10-8 A/cm2 to 1.98 × 10-9 A/cm2 for gate injection mode and 6.4 × 10-8 A/cm2 to 6.3 × 10-10 A/cm2 for substrate injection mode at 1 V. Hence, we suggest that plasma treatment might be useful in future device fabrication technology.

  3. DLTS Analysis and Interface Engineering of Solution Route Fabricated Zirconia Based MIS Devices Using Plasma Treatment

    Science.gov (United States)

    Kumar, Arvind; Mondal, Sandip; Koteswara Rao, K. S. R.

    2017-11-01

    In this work, we have fabricated low-temperature sol-gel spin-coated and oxygen (O2) plasma treated ZrO2 thin film-based metal-insulator-semiconductor devices. To understand the impact of plasma treatment on the Si/ZrO2 interface, deep level transient spectroscopy measurements were performed. It is reported that the interface state density (D it) comes down to 7.1 × 1010 eV-1 cm-2 from 4 × 1011 eV-1 cm-2, after plasma treatment. The reduction in D it is around five times and can be attributed to the passivation of oxygen vacancies near the Si/ZrO2 interface, as they try to relocate near the interface. The energy level position (E T) of interfacial traps is estimated to be 0.36 eV below the conduction band edge. The untreated ZrO2 film displayed poor leakage behavior due to the presence of several traps within the film and at the interface; O2 plasma treated films show improved leakage current density as they have been reduced from 5.4 × 10-8 A/cm2 to 1.98 × 10-9 A/cm2 for gate injection mode and 6.4 × 10-8 A/cm2 to 6.3 × 10-10 A/cm2 for substrate injection mode at 1 V. Hence, we suggest that plasma treatment might be useful in future device fabrication technology.

  4. Pedestrian dead reckoning using a novel sensor module that interfaces with modern smart devices

    Science.gov (United States)

    Stimac, Philip J.; Demar, Richard W.; Hewitt, Gregory F. S.; McKenna, Mark J.; Jordan, Eric M.; Fordham, Matthew; Haas, John W.

    2015-05-01

    Tracking individuals in areas such as dense urban environments and building interiors is desirable for numerous critical applications, but has been problematic mainly because of the unreliability or unavailability of GPS in many locations of interest. To date, tracking applications that utilize inertial sensors within smart devices have had varied degrees of success: accuracy typically dips below that of standard GPS within minutes and depends strongly on the quality of the sensors in the device, as well as the location that the device is carried on the body. In this paper we present a sensor module that interfaces with modern smart devices and which utilizes a low-cost, commercial-off-the-shelf, 9-axis IMU and pressure sensor to provide an advanced pedestrian dead reckoning solution. The sensor module is designed to communicate with the smart device (e.g., iOS, Android or Windows) via the audio jack and is intended for use as a beltmounted pedestrian tracker. In addition to describing the device hardware and functionality, we present our approach to processing the sensor module data streams to determine a user's position. Results using the prototype sensor module in operationally relevant scenarios is presented and discussed.

  5. Modeling and simulation of electronic structure, material interface and random doping in nano electronic devices

    Science.gov (United States)

    Chen, Duan; Wei, Guo-Wei

    2010-01-01

    The miniaturization of nano-scale electronic devices, such as metal oxide semiconductor field effect transistors (MOSFETs), has given rise to a pressing demand in the new theoretical understanding and practical tactic for dealing with quantum mechanical effects in integrated circuits. Modeling and simulation of this class of problems have emerged as an important topic in applied and computational mathematics. This work presents mathematical models and computational algorithms for the simulation of nano-scale MOSFETs. We introduce a unified two-scale energy functional to describe the electrons and the continuum electrostatic potential of the nano-electronic device. This framework enables us to put microscopic and macroscopic descriptions in an equal footing at nano scale. By optimization of the energy functional, we derive consistently-coupled Poisson-Kohn-Sham equations. Additionally, layered structures are crucial to the electrostatic and transport properties of nano transistors. A material interface model is proposed for more accurate description of the electrostatics governed by the Poisson equation. Finally, a new individual dopant model that utilizes the Dirac delta function is proposed to understand the random doping effect in nano electronic devices. Two mathematical algorithms, the matched interface and boundary (MIB) method and the Dirichlet-to-Neumann mapping (DNM) technique, are introduced to improve the computational efficiency of nano-device simulations. Electronic structures are computed via subband decomposition and the transport properties, such as the I-V curves and electron density, are evaluated via the non-equilibrium Green's functions (NEGF) formalism. Two distinct device configurations, a double-gate MOSFET and a four-gate MOSFET, are considered in our three-dimensional numerical simulations. For these devices, the current fluctuation and voltage threshold lowering effect induced by the discrete dopant model are explored. Numerical convergence

  6. A device to facilitate preparation of high-density neural cell cultures in MEAs.

    Science.gov (United States)

    Mok, S Y; Lim, Y M; Goh, S Y

    2009-05-15

    A device to facilitate high-density seeding of dissociated neural cells on planar multi-electrode arrays (MEAs) is presented in this paper. The device comprises a metal cover with two concentric cylinders-the outer cylinder fits tightly on to the external diameter of a MEA to hold it in place and an inner cylinder holds a central glass tube for introducing a cell suspension over the electrode area of the MEA. An O-ring is placed at the bottom of the inner cylinder and the glass tube to provide a fluid-tight seal between the glass tube and the MEA electrode surface. The volume of cell suspension in the glass tube is varied according to the desired plating density. After plating, the device can be lifted from the MEA without leaving any residue on the contact surface. The device has enabled us to increase and control the plating density of neural cell suspension with low viability, and to prepare successful primary cultures from cryopreserved neurons and glia. The cultures of cryopreserved dissociated cortical neurons that we have grown in this manner remained spontaneously active over months, exhibited stable development and similar network characteristics as reported by other researchers.

  7. Flow field effect transistors with polarisable interface for EOF tunable microfluidic separation devices.

    Science.gov (United States)

    Plecis, A; Tazid, J; Pallandre, A; Martinhon, P; Deslouis, C; Chen, Y; Haghiri-Gosnet, A M

    2010-05-21

    A method is proposed to control the zeta potential in microchannels using electrically polarisable interfaces in direct contact with the electrolyte. The approach is based on the use of conducting layers exhibiting minimal electrochemical reactions with aqueous electrolytes but a large potential window (typically from -2 V to +2 V) enabling tuning their zeta potential without detrimental faradic reactions. SiC, Al and CN(x) interfaces were deposited on glass surfaces and then integrated into glass-PDMS-glass devices. The effect of the zeta potential control was monitored by measuring the electro-osmotic flow using a microfluidic Wheatstone Bridge. The experimental results are in good agreement with theoretical predictions based on a one dimensional modeling. The electro-osmotic flow control obtained at high pH values suggests that it should be possible to use such devices as Polarisable Interface Flow-Field Effect Transistors (PI-FFETs) to overcome the difficulties met with conventional metal-isolator-electrolyte systems (MIE-FFETs) for electrokinetic separation applications.

  8. Brain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Rahib H. Abiyev

    2016-01-01

    Full Text Available The design of brain-computer interface for the wheelchair for physically disabled people is presented. The design of the proposed system is based on receiving, processing, and classification of the electroencephalographic (EEG signals and then performing the control of the wheelchair. The number of experimental measurements of brain activity has been done using human control commands of the wheelchair. Based on the mental activity of the user and the control commands of the wheelchair, the design of classification system based on fuzzy neural networks (FNN is considered. The design of FNN based algorithm is used for brain-actuated control. The training data is used to design the system and then test data is applied to measure the performance of the control system. The control of the wheelchair is performed under real conditions using direction and speed control commands of the wheelchair. The approach used in the paper allows reducing the probability of misclassification and improving the control accuracy of the wheelchair.

  9. Brain Computer Interface-Controlling Devices Utilizing The Alpha Brain Waves

    Directory of Open Access Journals (Sweden)

    Rohan Hundia

    2015-01-01

    Full Text Available Abstract This paper describes the development and testing of an interface system whereby one can control external devices by voluntarily controlling alpha waves that is through eye movement. Such a system may be used for the control of prosthetics robotic arms and external devices like wheelchairs using the alpha brain waves and the Mu rhythm. The response generated through the movement of the eye detecting and controlling the amplitude of the alpha brain waves is interfaced and processed to control Robotic systems and smart home control. In order to measure the response of alpha waves over different lobes of the brain initially I measured these signals over 32 regions using silver chloride plated electrodes. By the opening and the closure of the eyes and the movement in the up-down left-right directions and processing these movements measuring them over the occipital region I was able to differentiate the amplitude of the alpha waves generated due to these several movements. In the First session testing period subjects were asked to close and open their eyes and they were able to control limited movements of a Robot and a prosthetic arm. In the Second 2session the movement of the eyes was also considered left-right up-down along with the opening and closure during this time span they were able to control more dimensions of the robot several devices at the same time using different eye movements.

  10. A device for long-term perfusion, imaging, and electrical interfacing of brain tissue in vitro

    Directory of Open Access Journals (Sweden)

    Nathaniel J Killian

    2016-03-01

    Full Text Available Distributed microelectrode array (MEA recordings from consistent, viable, ≥ 500 µm thick tissue preparations over time periods from days to weeks may aid in studying a wide range of problems in neurobiology that require in vivo-like organotypic morphology. Existing tools for electrically interfacing with organotypic slices do not address necrosis that inevitably occurs within thick slices with limited diffusion of nutrients and gas, and limited removal of waste. We developed an integrated device that enables long-term maintenance of thick, functionally active, brain tissue models using interstitial perfusion and distributed recordings from thick sections of explanted tissue on a perforated multi-electrode array. This novel device allows for automated culturing, in situ imaging, and extracellular multi-electrode interfacing with brain slices, 3 D cell cultures, and potentially other tissue culture models. The device is economical, easy to assemble, and integrable with standard electrophysiology tools. We found that convective perfusion through the culture thickness provided a functional benefit to the preparations as firing rates were generally higher in perfused cultures compared to their respective unperfused controls. This work is a step towards the development of integrated tools for days-long experiments with more consistent, healthier, thicker, and functionally more active tissue cultures with built-in distributed electrophysiological recording and stimulation functionality. The results may be useful for the study of normal processes, pathological conditions, and drug screening strategies currently hindered by the limitations of acute (a few hours long brain slice preparations.

  11. Characterizing Graphene-modified Electrodes for Interfacing with Arduino®-based Devices.

    Science.gov (United States)

    Arris, Farrah Aida; Ithnin, Mohamad Hafiz; Salim, Wan Wardatul Amani Wan

    2016-08-01

    Portable low-cost platform and sensing systems for identification and quantitative measurement are in high demand for various environmental monitoring applications, especially in field work. Quantifying parameters in the field requires both minimal sample handling and a device capable of performing measurements with high sensitivity and stability. Furthermore, the one-device-fits-all concept is useful for continuous monitoring of multiple parameters. Miniaturization of devices can be achieved by introducing graphene as part of the transducer in an electrochemical sensor. In this project, we characterize graphene deposition methods on glassy-carbon electrodes (GCEs) with the goal of interfacing with an Arduino-based user-friendly microcontroller. We found that a galvanostatic electrochemical method yields the highest peak current of 10 mA, promising a highly sensitive electrochemical sensor. An Atlas Scientific™ printed circuit board (PCB) was connected to an Arduino® microcontroller using a multi-circuit connection that can be interfaced with graphene-based electrochemical sensors for environmental monitoring.

  12. Investigation of the GaN-on-GaAs interface for vertical power device applications

    Energy Technology Data Exchange (ETDEWEB)

    Möreke, Janina, E-mail: janina.moereke@bristol.ac.uk; Uren, Michael J.; Kuball, Martin [H.H. Wills Physics Laboratory, Tyndall Avenue, Bristol BS8 1TL (United Kingdom); Novikov, Sergei V.; Foxon, C. Thomas [Department of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD (United Kingdom); Hosseini Vajargah, Shahrzad; Wallis, David J.; Humphreys, Colin J. [Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS (United Kingdom); Haigh, Sarah J. [Super STEM Laboratory, STFC Daresbury Campus, Keckwick Lane, Daresbury WA4 4AD (United Kingdom); School of Materials, University of Manchester, Manchester M13 9PL (United Kingdom); Al-Khalidi, Abdullah; Wasige, Edward; Thayne, Iain [School of Engineering, University of Glasgow, Rankine Bldg, Oakfield Avenue, Glasgow G12 8LT (United Kingdom)

    2014-07-07

    GaN layers were grown onto (111) GaAs by molecular beam epitaxy. Minimal band offset between the conduction bands for GaN and GaAs materials has been suggested in the literature raising the possibility of using GaN-on-GaAs for vertical power device applications. I-V and C-V measurements of the GaN/GaAs heterostructures however yielded a rectifying junction, even when both sides of the junction were heavily doped with an n-type dopant. Transmission electron microscopy analysis further confirmed the challenge in creating a GaN/GaAs Ohmic interface by showing a large density of dislocations in the GaN layer and suggesting roughening of the GaN/GaAs interface due to etching of the GaAs by the nitrogen plasma, diffusion of nitrogen or melting of Ga into the GaAs substrate.

  13. Structure of the Buried Metal-Molecule Interface in Organic Thin Film Devices

    DEFF Research Database (Denmark)

    Hansen, Christian Rein; Sørensen, Thomas Just; Glyvradal, Magni

    2009-01-01

    By use of specular X-ray reflectivity (XR) the structure of a metal-covered organic thin film device is measured with angstrom resolution. The model system is a Langmuir-Blodgett (LB) film, sandwiched between a silicon substrate and a top electrode consisting of 25 Å titanium and 100 Å aluminum....... By comparison of XR data for the five-layer Pb2+ arachidate LB film before and after vapor deposition of the Ti/Al top electrode, a detailed account of the structural damage to the organic film at the buried metal-molecule interface is obtained. We find that the organized structure of the two topmost LB layers...

  14. Method for reading sensors and controlling actuators using audio interfaces of mobile devices.

    Science.gov (United States)

    Aroca, Rafael V; Burlamaqui, Aquiles F; Gonçalves, Luiz M G

    2012-01-01

    This article presents a novel closed loop control architecture based on audio channels of several types of computing devices, such as mobile phones and tablet computers, but not restricted to them. The communication is based on an audio interface that relies on the exchange of audio tones, allowing sensors to be read and actuators to be controlled. As an application example, the presented technique is used to build a low cost mobile robot, but the system can also be used in a variety of mechatronics applications and sensor networks, where smartphones are the basic building blocks.

  15. Controlling selective stimulations below a spinal cord hemisection using brain recordings with a neural interface system approach

    Science.gov (United States)

    Panetsos, Fivos; Sanchez-Jimenez, Abel; Torets, Carlos; Largo, Carla; Micera, Silvestro

    2011-08-01

    In this work we address the use of realtime cortical recordings for the generation of coherent, reliable and robust motor activity in spinal-lesioned animals through selective intraspinal microstimulation (ISMS). The spinal cord of adult rats was hemisectioned and groups of multielectrodes were implanted in both the central nervous system (CNS) and the spinal cord below the lesion level to establish a neural system interface (NSI). To test the reliability of this new NSI connection, highly repeatable neural responses recorded from the CNS were used as a pattern generator of an open-loop control strategy for selective ISMS of the spinal motoneurons. Our experimental procedure avoided the spontaneous non-controlled and non-repeatable neural activity that could have generated spurious ISMS and the consequent undesired muscle contractions. Combinations of complex CNS patterns generated precisely coordinated, reliable and robust motor actions.

  16. Autotuning of PID controller by means of human machine interface device

    Directory of Open Access Journals (Sweden)

    Michał Awtoniuk

    2017-06-01

    Full Text Available More and more control systems are based on industry microprocessors like PLC controllers (Programmable Logic Controller. The most commonly used control algorithm is PID (Proportional-Integral-Derivative algorithm. Autotuning procedure is not available in every PLC. These controllers are typically used in cooperation with HMI (Human Machine Interface devices. In the study two procedures of autotuning of the PID controller were implemented in the HMI device: step method and relay method. Six tuning rules for step methods and one for relay method were chosen. The autotuning procedures on simulated controlled object and PLC controller without build-in autotuning were tested. The object of control was first order system plus time delay.

  17. Design Program in Graphic User Interface Environment for Automobile ER Devices

    Science.gov (United States)

    Lim, S. C.; Park, J. S.; Sohn, J. W.; Choi, S. B.

    This work presents a design and analysis program for vehicle devices utilizing an electrorheological (ER) fluid. The program is operated in graphic user interface (GUI) environment and the initial window is consisted of four subprogram modules which are related to ER shock absorber, ER seat damper, ER engine mount, and ER anti-lock brake system (ABS), respectively. In order to execute each module, both material properties and design parameters are to be chosen by the user. Then, the output display window shows the field-dependent performance characteristics to be considered as design criteria. In addition, control performances of the vehicle system equipped with ER devices are displayed in time and frequency domain. In order to demonstrate the effectiveness of the proposed program, ER shock absorber and ER ABS are designed and manufactured and their performance characteristics are evaluated.

  18. In vitro verification of a 3-D regenerative neural interface design: examination of neurite growth and electrical properties within a bifurcating microchannel structure

    NARCIS (Netherlands)

    Wieringa, P.A.; Wiertz, Remy; de Weerd, Eddy L; Rutten, Wim

    2010-01-01

    Toward the development of neuroprosthesis, we propose a 3-D regenerative neural interface design for connecting with the peripheral nervous system. This approach relies on bifurcating microstructures to achieve defasciculated ingrowth patterns and, consequently, high selectivity. In vitro studies

  19. Novel conjugates of peptides and conjugated polymers for optoelectronics and neural interfaces

    Science.gov (United States)

    Bhagwat, Nandita

    Peptide-polymer conjugates are a novel class of hybrid materials that take advantage of each individual component giving the opportunity to generate materials with unique physical, chemical, mechanical, optical, and electronic properties. In this dissertation peptide-polymer conjugates for two different applications are discussed. The first set of peptide-polymer conjugates were developed as templates to study the intermolecular interactions between electroactive molecules by manipulating the intermolecular distances at nano-scale level. A PEGylated, alpha-helical peptide template was employed to effectively display an array of organic chromophores (oxadiazole containing phenylenevinylene oligomers, Oxa-PPV). Three Oxa-PPV chromophores were strategically positioned on each template, at distances ranging from 6 to 17 A from each other, as dictated by the chemical and structural properties of the peptide. The Oxa-PPV modified PEGylated helical peptides (produced via Heck coupling strategies) were characterized by a variety of spectroscopic methods. Electronic contributions from multiple pairs of chromophores on a scaffold were detectable; the number and relative positioning of the chromophores dictated the absorbance and emission maxima, thus confirming the utility of these polymer--peptide templates for complex presentation of organic chromophores. The rest of the thesis is focused on using poly(3,4-alkylenedioxythiophene) based conjugated polymers as coatings for neural electrodes. This thiophene derivative is of considerable current interest for functionalizing the surfaces of a wide variety of devices including implantable biomedical electronics, specifically neural bio-electrodes. Toward these ends, copolymer films of 3,4-ethylenedioxythiophene (EDOT) with a carboxylic acid functional EDOT (EDOTacid) were electrochemically deposited and characterized as a systematic function of the EDOTacid content (0, 25, 50, 75, and 100%). The chemical surface characterization

  20. Finger tracking for hand-held device interface using profile-matching stereo vision

    Science.gov (United States)

    Chang, Yung-Ping; Lee, Dah-Jye; Moore, Jason; Desai, Alok; Tippetts, Beau

    2013-01-01

    Hundreds of millions of people use hand-held devices frequently and control them by touching the screen with their fingers. If this method of operation is being used by people who are driving, the probability of deaths and accidents occurring substantially increases. With a non-contact control interface, people do not need to touch the screen. As a result, people will not need to pay as much attention to their phones and thus drive more safely than they would otherwise. This interface can be achieved with real-time stereovision. A novel Intensity Profile Shape-Matching Algorithm is able to obtain 3-D information from a pair of stereo images in real time. While this algorithm does have a trade-off between accuracy and processing speed, the result of this algorithm proves the accuracy is sufficient for the practical use of recognizing human poses and finger movement tracking. By choosing an interval of disparity, an object at a certain distance range can be segmented. In other words, we detect the object by its distance to the cameras. The advantage of this profile shape-matching algorithm is that detection of correspondences relies on the shape of profile and not on intensity values, which are subjected to lighting variations. Based on the resulting 3-D information, the movement of fingers in space from a specific distance can be determined. Finger location and movement can then be analyzed for non-contact control of hand-held devices.

  1. sBCI-Headset—Wearable and Modular Device for Hybrid Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Tatsiana Malechka

    2015-02-01

    Full Text Available Severely disabled people, like completely paralyzed persons either with tetraplegia or similar disabilities who cannot use their arms and hands, are often considered as a user group of Brain Computer Interfaces (BCI. In order to achieve high acceptance of the BCI by this user group and their supporters, the BCI system has to be integrated into their support infrastructure. Critical disadvantages of a BCI are the time consuming preparation of the user for the electroencephalography (EEG measurements and the low information transfer rate of EEG based BCI. These disadvantages become apparent if a BCI is used to control complex devices. In this paper, a hybrid BCI is described that enables research for a Human Machine Interface (HMI that is optimally adapted to requirements of the user and the tasks to be carried out. The solution is based on the integration of a Steady-state visual evoked potential (SSVEP-BCI, an Event-related (de-synchronization (ERD/ERS-BCI, an eye tracker, an environmental observation camera, and a new EEG head cap for wearing comfort and easy preparation. The design of the new fast multimodal BCI (called sBCI system is described and first test results, obtained in experiments with six healthy subjects, are presented. The sBCI concept may also become useful for healthy people in cases where a “hands-free” handling of devices is necessary.

  2. Enhanced thermal stability of RuO2/polyimide interface for flexible device applications

    Science.gov (United States)

    Music, Denis; Schmidt, Paul; Chang, Keke

    2017-09-01

    We have studied the thermal stability of RuO2/polyimide (Kapton) interface using experimental and theoretical methods. Based on calorimetric and spectroscopic analyses, this inorganic-organic system does not exhibit any enthalpic peaks as well as all bonds in RuO2 and Kapton are preserved up to 500 °C. In addition, large-scale density functional theory based molecular dynamics, carried out in the same temperature range, validates the electronic structure and points out that numerous Ru-C and a few Ru-O covalent/ionic bonds form across the RuO2/Kapton interface. This indicates strong adhesion, but there is no evidence of Kapton degradation upon thermal excitation. Furthermore, RuO2 does not exhibit any interfacial bonds with N and H in Kapton, providing additional evidence for the thermal stability notion. It is suggested that the RuO2/Kapton interface is stable due to aromatic architecture of Kapton. This enhanced thermal stability renders Kapton an appropriate polymeric substrate for RuO2 containing systems in various applications, especially for flexible microelectronic and energy devices.

  3. Graphene Quantum Dots Interfaced with Single Bacterial Spore for Bio-Electromechanical Devices: A Graphene Cytobot

    Science.gov (United States)

    Sreeprasad, T. S.; Nguyen, Phong; Alshogeathri, Ahmed; Hibbeler, Luke; Martinez, Fabian; McNeil, Nolan; Berry, Vikas

    2015-01-01

    The nanoarchitecture and micromachinery of a cell can be leveraged to fabricate sophisticated cell-driven devices. This requires a coherent strategy to derive cell's mechanistic abilities, microconstruct, and chemical-texture towards such microtechnologies. For example, a microorganism's hydrophobic membrane encapsulating hygroscopic constituents allows it to sustainably withhold a high aquatic pressure. Further, it provides a rich surface chemistry available for nano-interfacing and a strong mechanical response to humidity. Here we demonstrate a route to incorporate a complex cellular structure into microelectromechanics by interfacing compatible graphene quantum dots (GQDs) with a highly responsive single spore microstructure. A sensitive and reproducible electron-tunneling width modulation of 1.63 nm within a network of GQDs chemically-secured on a spore was achieved via sporal hydraulics with a driving force of 299.75 Torrs (21.7% water at GQD junctions). The electron-transport activation energy and the Coulomb blockade threshold for the GQD network were 35 meV and 31 meV, respectively; while the inter-GQD capacitance increased by 1.12 folds at maximum hydraulic force. This is the first example of nano/bio interfacing with spores and will lead to the evolution of next-generation bio-derived microarchitectures, probes for cellular/biochemical processes, biomicrorobotic-mechanisms, and membranes for micromechanical actuation. PMID:25774962

  4. Single-crystal charge transfer interfaces for efficient photonic devices (Conference Presentation)

    Science.gov (United States)

    Alves, Helena; Pinto, Rui M.; Maçôas, Ermelinda M. S.; Baleizão, Carlos; Santos, Isabel C.

    2016-09-01

    Organic semiconductors have unique optical, mechanical and electronic properties that can be combined with customized chemical functionality. In the crystalline form, determinant features for electronic applications such as molecular purity, the charge mobility or the exciton diffusion length, reveal a superior performance when compared with materials in a more disordered form. Combining crystals of two different conjugated materials as even enable a new 2D electronic system. However, the use of organic single crystals in devices is still limited to a few applications, such as field-effect transistors. In 2013, we presented the first system composed of single-crystal charge transfer interfaces presenting photoconductivity behaviour. The system composed of rubrene and TCNQ has a responsivity reaching 1 A/W, corresponding to an external quantum efficiency of nearly 100%. A similar approach, with a hybrid structure of a PCBM film and rubrene single crystal also presents high responsivity and the possibility to extract excitons generated in acceptor materials. This strategy led to an extended action towards the near IR. By adequate material design and structural organisation of perylediimides, we demonstrate that is possible to improve exciton diffusion efficiency. More recently, we have successfully used the concept of charge transfer interfaces in phototransistors. These results open the possibility of using organic single-crystal interfaces in photonic applications.

  5. A low-noise low-power amplifier for implantable device for neural signal acquisition.

    Science.gov (United States)

    Li, Ming-Ze; Tang, Kea-Tiong

    2009-01-01

    This paper presents a low-noise low-power amplifier for implantable device for neural signal acquisition. By operating MOS transistors in the subthreshold region, smaller low-frequency noise and lower power consumption can be achieved. A low power, low-noise common-drain buffer and a low-noise, high-linearity, low pass filter are used for high frequency noise filtering. Post-layout simulation shows the input referred noise of the system is 2.19microVrms from 10Hz to 10 KHz, power consumption is 55.8microW, and the NEF is 2.53. The amplifier was fabricated using a TSMC 0.18microm 1P6M CMOS process. Simulation results show that this low-noise, low-power amplifier is suitable for implantable device applications.

  6. Neural Control of a Tracking Task via Attention-Gated Reinforcement Learning for Brain-Machine Interfaces.

    Science.gov (United States)

    Wang, Yiwen; Wang, Fang; Xu, Kai; Zhang, Qiaosheng; Zhang, Shaomin; Zheng, Xiaoxiang

    2015-05-01

    Reinforcement learning (RL)-based brain machine interfaces (BMIs) enable the user to learn from the environment through interactions to complete the task without desired signals, which is promising for clinical applications. Previous studies exploited Q-learning techniques to discriminate neural states into simple directional actions providing the trial initial timing. However, the movements in BMI applications can be quite complicated, and the action timing explicitly shows the intention when to move. The rich actions and the corresponding neural states form a large state-action space, imposing generalization difficulty on Q-learning. In this paper, we propose to adopt attention-gated reinforcement learning (AGREL) as a new learning scheme for BMIs to adaptively decode high-dimensional neural activities into seven distinct movements (directional moves, holdings and resting) due to the efficient weight-updating. We apply AGREL on neural data recorded from M1 of a monkey to directly predict a seven-action set in a time sequence to reconstruct the trajectory of a center-out task. Compared to Q-learning techniques, AGREL could improve the target acquisition rate to 90.16% in average with faster convergence and more stability to follow neural activity over multiple days, indicating the potential to achieve better online decoding performance for more complicated BMI tasks.

  7. Augmenting intracortical brain-machine interface with neurally driven error detectors

    Science.gov (United States)

    Even-Chen, Nir; Stavisky, Sergey D.; Kao, Jonathan C.; Ryu, Stephen I.; Shenoy, Krishna V.

    2017-12-01

    Objective. Making mistakes is inevitable, but identifying them allows us to correct or adapt our behavior to improve future performance. Current brain–machine interfaces (BMIs) make errors that need to be explicitly corrected by the user, thereby consuming time and thus hindering performance. We hypothesized that neural correlates of the user perceiving the mistake could be used by the BMI to automatically correct errors. However, it was unknown whether intracortical outcome error signals were present in the premotor and primary motor cortices, brain regions successfully used for intracortical BMIs. Approach. We report here for the first time a putative outcome error signal in spiking activity within these cortices when rhesus macaques performed an intracortical BMI computer cursor task. Main results. We decoded BMI trial outcomes shortly after and even before a trial ended with 96% and 84% accuracy, respectively. This led us to develop and implement in real-time a first-of-its-kind intracortical BMI error ‘detect-and-act’ system that attempts to automatically ‘undo’ or ‘prevent’ mistakes. The detect-and-act system works independently and in parallel to a kinematic BMI decoder. In a challenging task that resulted in substantial errors, this approach improved the performance of a BMI employing two variants of the ubiquitous Kalman velocity filter, including a state-of-the-art decoder (ReFIT-KF). Significance. Detecting errors in real-time from the same brain regions that are commonly used to control BMIs should improve the clinical viability of BMIs aimed at restoring motor function to people with paralysis.

  8. DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity.

    Science.gov (United States)

    Cowley, Benjamin R; Kaufman, Matthew T; Churchland, Mark M; Ryu, Stephen I; Shenoy, Krishna V; Yu, Byron M

    2012-01-01

    The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data) is typically greater than 3. However, direct plotting can only provide a 2D or 3D view. To address this limitation, we developed a Matlab graphical user interface (GUI) that allows the user to quickly navigate through a continuum of different 2D projections of the reduced-dimensional space. To demonstrate the utility and versatility of this GUI, we applied it to visualize population activity recorded in premotor and motor cortices during reaching tasks. Examples include single-trial population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded sequentially using single electrodes. Because any single 2D projection may provide a misleading impression of the data, being able to see a large number of 2D projections is critical for intuition-and hypothesis-building during exploratory data analysis. The GUI includes a suite of additional interactive tools, including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses. The use of visualization tools like the GUI developed here, in tandem with dimensionality reduction methods, has the potential to further our understanding of neural population activity.

  9. Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces

    Directory of Open Access Journals (Sweden)

    Cipriani Christian

    2011-09-01

    Full Text Available Abstract Background The restoration of complex hand functions by creating a novel bidirectional link between the nervous system and a dexterous hand prosthesis is currently pursued by several research groups. This connection must be fast, intuitive, with a high success rate and quite natural to allow an effective bidirectional flow of information between the user's nervous system and the smart artificial device. This goal can be achieved with several approaches and among them, the use of implantable interfaces connected with the peripheral nervous system, namely intrafascicular electrodes, is considered particularly interesting. Methods Thin-film longitudinal intra-fascicular electrodes were implanted in the median and ulnar nerves of an amputee's stump during a four-week trial. The possibility of decoding motor commands suitable to control a dexterous hand prosthesis was investigated for the first time in this research field by implementing a spike sorting and classification algorithm. Results The results showed that motor information (e.g., grip types and single finger movements could be extracted with classification accuracy around 85% (for three classes plus rest and that the user could improve his ability to govern motor commands over time as shown by the improved discrimination ability of our classification algorithm. Conclusions These results open up new and promising possibilities for the development of a neuro-controlled hand prosthesis.

  10. Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

    2017-08-01

    This paper presents a bidirectional brain machine interface (BMI) microsystem designed for closed-loop neuroscience research, especially experiments in freely behaving animals. The system-on-chip (SoC) consists of 16-channel neural recording front-ends, neural feature extraction units, 16-channel programmable neural stimulator back-ends, in-channel programmable closed-loop controllers, global analog-digital converters (ADC), and peripheral circuits. The proposed neural feature extraction units includes 1) an ultra low-power neural energy extraction unit enabling a 64-step natural logarithmic domain frequency tuning, and 2) a current-mode action potential (AP) detection unit with time-amplitude window discriminator. A programmable proportional-integral-derivative (PID) controller has been integrated in each channel enabling a various of closed-loop operations. The implemented ADCs include a 10-bit voltage-mode successive approximation register (SAR) ADC for the digitization of the neural feature outputs and/or local field potential (LFP) outputs, and an 8-bit current-mode SAR ADC for the digitization of the action potential outputs. The multi-mode stimulator can be programmed to perform monopolar or bipolar, symmetrical or asymmetrical charge balanced stimulation with a maximum current of 4 mA in an arbitrary channel configuration. The chip has been fabricated in 0.18 μ m CMOS technology, occupying a silicon area of 3.7 mm 2 . The chip dissipates 56 μW/ch on average. General purpose low-power microcontroller with Bluetooth module are integrated in the system to provide wireless link and SoC configuration. Methods, circuit techniques and system topology proposed in this work can be used in a wide range of relevant neurophysiology research, especially closed-loop BMI experiments.

  11. Implantable Graphene-based Neural Electrode Interfaces for Electrophysiology and Neurochemistry in In Vivo Hyperacute Stroke Model.

    Science.gov (United States)

    Liu, Ta-Chung; Chuang, Min-Chieh; Chu, Chao-Yi; Huang, Wei-Chen; Lai, Hsin-Yi; Wang, Chao-Ting; Chu, Wei-Lin; Chen, San-Yuan; Chen, You-Yin

    2016-01-13

    Implantable microelectrode arrays have attracted considerable interest due to their high temporal and spatial resolution recording of neuronal activity in tissues. We herein presented an implantable multichannel neural probe with multiple real-time monitoring of neural-chemical and neural-electrical signals by a nonenzymatic neural-chemical interface, which was designed by creating the newly developed reduced graphene oxide-gold oxide (rGO/Au2O3) nanocomposite electrode. The modified electrode on the neural probe was prepared by a facile one-step cyclic voltammetry (CV) electrochemical method with simultaneous occurrence of gold oxidation and GOs reduction to induce the intimate attachment by electrostatic interaction using chloride ions (Cl(-)). The rGO/Au2O3-modified electrode at a low deposition scan rate of 10 mVs(-1) displayed significantly improved electrocatalytic activity due to large active areas and well-dispersive attached rGO sheets. The in vitro amperometric response to H2O2 demonstrated a fast response of less than 5 s and a very low detection limit of 0.63 μM. In in vivo hyperacute stroke model, the concentration of H2O2 was measured as 100.48 ± 4.52 μM for rGO/Au2O3 electrode within 1 h photothrombotic stroke, which was much higher than that (71.92 μM ± 2.52 μM) for noncoated electrode via in vitro calibration. Simultaneously, the somatosensory-evoked potentials (SSEPs) test provided reliable and precise validation for detecting functional changes of neuronal activities. This newly developed implantable probe with localized rGO/Au2O3 nanocomposite electrode can serve as a rapid and reliable sensing platform for practical H2O2 detection in the brain or for other neural-chemical molecules in vivo.

  12. Alternative design of inductive pointing device for oral interface for computers and wheelchairs.

    Science.gov (United States)

    Lontis, Eugen R; Andreasen Struijk, Lotte N S

    2012-01-01

    An inductive pointing device was designed and implemented successfully in a tongue controlled oral interface. Sensors were manufactured as an assembly of multilayer coils in the printed circuit board technology on two pads. The sensor pads were encapsulated together with electronics and battery in a mouthpiece, placed in the upper palate of the oral cavity. The PCB technology allowed surface activation of one or more sensors by gliding over the surface of the coils assembly of a small cylindrical unit attached to the tongue. The model consisted of 8 sensors and allowed real time proportional control of both speed and direction similar to a joystick. However, the size of the oral cavity, the number and geometry of the coil loops and characteristics of the activation unit impose limits in designing the sensors and call for an alternative layout design. Two alternative sensor designs are proposed in this paper, aiming to reduce the size of the sensor pad by one third, extending the target group, including children, and increasing the easiness of wear of the oral interface.

  13. A 128-Channel FPGA-Based Real-Time Spike-Sorting Bidirectional Closed-Loop Neural Interface System.

    Science.gov (United States)

    Park, Jongkil; Kim, Gookhwa; Jung, Sang-Don

    2017-12-01

    A multichannel neural interface system is an important tool for various types of neuroscientific studies. For the electrical interface with a biological system, high-precision high-speed data recording and various types of stimulation capability are required. In addition, real-time signal processing is an important feature in the implementation of a real-time closed-loop system without unwanted substantial delay for feedback stimulation. Online spike sorting, the process of assigning neural spikes to an identified group of neurons or clusters, is a necessary step to make a closed-loop path in real time, but massive memory-space requirements commonly limit hardware implementations. Here, we present a 128-channel field-programmable gate array (FPGA)-based real-time closed-loop bidirectional neural interface system. The system supports 128 channels for simultaneous signal recording and eight selectable channels for stimulation. A modular 64-channel analog front-end (AFE) provides scalability and a parameterized specification of the AFE supports the recording of various electrophysiological signal types with 1.59 ± 0.76 root-mean-square noise. The stimulator supports both voltage-controlled and current-controlled arbitrarily shaped waveforms with the programmable amplitude and duration of pulse. An empirical algorithm for online real-time spike sorting is implemented in an FPGA. The spike-sorting is performed by template matching, and templates are created by an online real-time unsupervised learning process. A memory saving technique, called dynamic cache organizing, is proposed to reduce the memory requirement down to 6 kbit per channel and modular implementation improves the scalability for further extensions.

  14. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  15. Transport and metabolism at blood-brain interfaces and in neural cells: relevance to bilirubin-induced encephalopathy

    Directory of Open Access Journals (Sweden)

    Silvia eGazzin

    2012-05-01

    Full Text Available Bilirubin, the end-product of heme catabolism, circulates in non pathological plasma mostly as a protein-bound species. When bilirubin concentration builds up, the free fraction of the molecule increases. Unbound bilirubin then diffuses across blood-brain interfaces into the brain, where it accumulates and exerts neurotoxic effects. In this classical view of bilirubin neurotoxicity, blood-brain interfaces act merely as structural barriers impeding the penetration of the pigment-bound carrier protein, and neural cells are considered as passive targets of its toxicity. Yet, the role of blood-brain interfaces in the occurrence of bilirubin encephalopathy appears more complex than being simple barriers to the diffusion of bilirubin, and neural cells such as astrocytes and neurons can play an active role in controlling the balance between the neuroprotective and neurotoxic effects of bilirubin. This article reviews the emerging in vivo and in vitro data showing that transport and metabolic detoxification mechanisms at the blood-brain and blood-CSF barriers may modulate bilirubin flux across both cellular interfaces, and that these protective functions can be affected in chronic hyperbilirubinemia. Then the in vivo and in vitro arguments in favor of the physiological antioxidant function of intracerebral bilirubin are presented, as well as with the potential role of transporters such as ABCC-1 and metabolizing enzymes such as cytochromes P-450 in setting the cerebral cell- and structure-specific toxicity of bilirubin following hyperbilirubinemia. The relevance of these data to the pathophysiology of bilirubin-induced neurological diseases is discussed.

  16. Two-dimensional neural field simulator with parameter interface and 3D visualization

    OpenAIRE

    Nichols, Eric; Hutt, Axel

    2014-01-01

    International audience; A simulator calculating two-dimensional dynamic neural fields with multiple order derivatives is presented in this work. The simulated neural fields are of the type ... where I, L and S are respectively a field's input, spatial delay kernel with axonal transmission speed c and nonlinear firing rate function S = S0 / (1 + exp(-α(V-Θ)). A Fast Fourier Transform in space is used to accelerate the integral calculation. The stochastic differential equation is useful for stu...

  17. Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design Considerations

    Directory of Open Access Journals (Sweden)

    Tayfun Gokmen

    2016-07-01

    Full Text Available In recent years, deep neural networks (DNN have demonstrated significant business impact in large scale analysis and classification tasks such as speech recognition, visual object detection, pattern extraction, etc. Training of large DNNs, however, is universally considered as time consuming and computationally intensive task that demands datacenter-scale computational resources recruited for many days. Here we propose a concept of resistive processing unit (RPU devices that can potentially accelerate DNN training by orders of magnitude while using much less power. The proposed RPU device can store and update the weight values locally thus minimizing data movement during training and allowing to fully exploit the locality and the parallelism of the training algorithm. We evaluate the effect of various RPU device features/non-idealities and system parameters on performance in order to derive the device and system level specifications for implementation of an accelerator chip for DNN training in a realistic CMOS-compatible technology. For large DNNs with about 1 billion weights this massively parallel RPU architecture can achieve acceleration factors of 30,000X compared to state-of-the-art microprocessors while providing power efficiency of 84,000 GigaOps/s/W. Problems that currently require days of training on a datacenter-size cluster with thousands of machines can be addressed within hours on a single RPU accelerator. A system consisting of a cluster of RPU accelerators will be able to tackle Big Data problems with trillions of parameters that is impossible to address today like, for example, natural speech recognition and translation between all world languages, real-time analytics on large streams of business and scientific data, integration and analysis of multimodal sensory data flows from a massive number of IoT (Internet of Things sensors.

  18. Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design Considerations.

    Science.gov (United States)

    Gokmen, Tayfun; Vlasov, Yurii

    2016-01-01

    In recent years, deep neural networks (DNN) have demonstrated significant business impact in large scale analysis and classification tasks such as speech recognition, visual object detection, pattern extraction, etc. Training of large DNNs, however, is universally considered as time consuming and computationally intensive task that demands datacenter-scale computational resources recruited for many days. Here we propose a concept of resistive processing unit (RPU) devices that can potentially accelerate DNN training by orders of magnitude while using much less power. The proposed RPU device can store and update the weight values locally thus minimizing data movement during training and allowing to fully exploit the locality and the parallelism of the training algorithm. We evaluate the effect of various RPU device features/non-idealities and system parameters on performance in order to derive the device and system level specifications for implementation of an accelerator chip for DNN training in a realistic CMOS-compatible technology. For large DNNs with about 1 billion weights this massively parallel RPU architecture can achieve acceleration factors of 30, 000 × compared to state-of-the-art microprocessors while providing power efficiency of 84, 000 GigaOps∕s∕W. Problems that currently require days of training on a datacenter-size cluster with thousands of machines can be addressed within hours on a single RPU accelerator. A system consisting of a cluster of RPU accelerators will be able to tackle Big Data problems with trillions of parameters that is impossible to address today like, for example, natural speech recognition and translation between all world languages, real-time analytics on large streams of business and scientific data, integration, and analysis of multimodal sensory data flows from a massive number of IoT (Internet of Things) sensors.

  19. Three-terminal ferroelectric synapse device with concurrent learning function for artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Nishitani, Y.; Kaneko, Y.; Ueda, M.; Fujii, E. [Advanced Technology Research Laboratories, Panasonic Corporation, Seika, Kyoto 619-0237 (Japan); Morie, T. [Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Wakamatsu-ku, Kitakyushu 808-0196 (Japan)

    2012-06-15

    Spike-timing-dependent synaptic plasticity (STDP) is demonstrated in a synapse device based on a ferroelectric-gate field-effect transistor (FeFET). STDP is a key of the learning functions observed in human brains, where the synaptic weight changes only depending on the spike timing of the pre- and post-neurons. The FeFET is composed of the stacked oxide materials with ZnO/Pr(Zr,Ti)O{sub 3} (PZT)/SrRuO{sub 3}. In the FeFET, the channel conductance can be altered depending on the density of electrons induced by the polarization of PZT film, which can be controlled by applying the gate voltage in a non-volatile manner. Applying a pulse gate voltage enables the multi-valued modulation of the conductance, which is expected to be caused by a change in PZT polarization. This variation depends on the height and the duration of the pulse gate voltage. Utilizing these characteristics, symmetric and asymmetric STDP learning functions are successfully implemented in the FeFET-based synapse device by applying the non-linear pulse gate voltage generated from a set of two pulses in a sampling circuit, in which the two pulses correspond to the spikes from the pre- and post-neurons. The three-terminal structure of the synapse device enables the concurrent learning, in which the weight update can be performed without canceling signal transmission among neurons, while the neural networks using the previously reported two-terminal synapse devices need to stop signal transmission for learning.

  20. An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology

    Science.gov (United States)

    Aravanis, Alexander M.; Wang, Li-Ping; Zhang, Feng; Meltzer, Leslie A.; Mogri, Murtaza Z.; Schneider, M. Bret; Deisseroth, Karl

    2007-09-01

    Neural interface technology has made enormous strides in recent years but stimulating electrodes remain incapable of reliably targeting specific cell types (e.g. excitatory or inhibitory neurons) within neural tissue. This obstacle has major scientific and clinical implications. For example, there is intense debate among physicians, neuroengineers and neuroscientists regarding the relevant cell types recruited during deep brain stimulation (DBS); moreover, many debilitating side effects of DBS likely result from lack of cell-type specificity. We describe here a novel optical neural interface technology that will allow neuroengineers to optically address specific cell types in vivo with millisecond temporal precision. Channelrhodopsin-2 (ChR2), an algal light-activated ion channel we developed for use in mammals, can give rise to safe, light-driven stimulation of CNS neurons on a timescale of milliseconds. Because ChR2 is genetically targetable, specific populations of neurons even sparsely embedded within intact circuitry can be stimulated with high temporal precision. Here we report the first in vivo behavioral demonstration of a functional optical neural interface (ONI) in intact animals, involving integrated fiberoptic and optogenetic technology. We developed a solid-state laser diode system that can be pulsed with millisecond precision, outputs 20 mW of power at 473 nm, and is coupled to a lightweight, flexible multimode optical fiber, ~200 µm in diameter. To capitalize on the unique advantages of this system, we specifically targeted ChR2 to excitatory cells in vivo with the CaMKIIα promoter. Under these conditions, the intensity of light exiting the fiber (~380 mW mm-2) was sufficient to drive excitatory neurons in vivo and control motor cortex function with behavioral output in intact rodents. No exogenous chemical cofactor was needed at any point, a crucial finding for in vivo work in large mammals. Achieving modulation of behavior with optical control of

  1. A Hardware-Efficient Scalable Spike Sorting Neural Signal Processor Module for Implantable High-Channel-Count Brain Machine Interfaces.

    Science.gov (United States)

    Yang, Yuning; Boling, Sam; Mason, Andrew J

    2017-08-01

    Next-generation brain machine interfaces demand a high-channel-count neural recording system to wirelessly monitor activities of thousands of neurons. A hardware efficient neural signal processor (NSP) is greatly desirable to ease the data bandwidth bottleneck for a fully implantable wireless neural recording system. This paper demonstrates a complete multichannel spike sorting NSP module that incorporates all of the necessary spike detector, feature extractor, and spike classifier blocks. To meet high-channel-count and implantability demands, each block was designed to be highly hardware efficient and scalable while sharing resources efficiently among multiple channels. To process multiple channels in parallel, scalability analysis was performed, and the utilization of each block was optimized according to its input data statistics and the power, area and/or speed of each block. Based on this analysis, a prototype 32-channel spike sorting NSP scalable module was designed and tested on an FPGA using synthesized datasets over a wide range of signal to noise ratios. The design was mapped to 130 nm CMOS to achieve 0.75 μW power and 0.023 mm2 area consumptions per channel based on post synthesis simulation results, which permits scalability of digital processing to 690 channels on a 4×4 mm2 electrode array.

  2. Characterization of interface traps in stable and efficient Tb-implanted SiO{sub 2} light-emitting devices

    Energy Technology Data Exchange (ETDEWEB)

    Seeger, Michael; Rebohle, Lars; Lehmann, Jan; Skorupa, Wolfgang; Helm, Manfred; Schmidt, Heidemarie [Forschungszentrum Dresden-Rossendorf e.V., Dresden (Germany)

    2010-07-01

    The strong green electroluminescence from the Tb{sup 3+} ions in SiO{sub 2} is excited by hot electrons from the conduction band of the SiO{sub 2} matrix in metal oxide semiconductor light emitting devices (MOSLED). Charge trapping in the oxide layers and at the oxide layer-semiconductor interface cause a short lifetime of the MOSLED. This has been investigated by means of frequency dependent admittance-voltage measurements to determine if the MOSLED will perform satisfactorily for different annealing times. Our results on unimplanted MOSLEDs reveal the largest interface trap density of 10{sup 13} eV{sup -1} cm{sup -2} for 60 s rapid thermal annealing at 1000 C. Also the effect of Tb{sup +} implantation on interface trap properties in MOSLEDs containing double-stacked dielectric layers has been investigated. Quasistatic charge-voltage (QV) measurements have been used to probe the interface trap occupancy versus voltage.

  3. From Growth Surface to Device Interface: Preserving Metallic Fe under Monolayer Hexagonal Boron Nitride.

    Science.gov (United States)

    Caneva, Sabina; Martin, Marie-Blandine; D'Arsié, Lorenzo; Aria, Adrianus I; Sezen, Hikmet; Amati, Matteo; Gregoratti, Luca; Sugime, Hisashi; Esconjauregui, Santiago; Robertson, John; Hofmann, Stephan; Weatherup, Robert S

    2017-09-06

    We investigate the interfacial chemistry between Fe catalyst foils and monolayer hexagonal boron nitride (h-BN) following chemical vapor deposition and during subsequent atmospheric exposure, using scanning electron microscopy, X-ray photoemission spectroscopy, and scanning photoelectron microscopy. We show that regions of the Fe surface covered by h-BN remain in a metallic state during exposure to moist air for ∼40 h at room temperature. This protection is attributed to the strong interfacial interaction between h-BN and Fe, which prevents the rapid intercalation of oxidizing species. Local Fe oxidation is observed on bare Fe regions and close to defects in the h-BN film (e.g., domain boundaries, wrinkles, and edges), which over the longer-term provide pathways for slow bulk oxidation of Fe. We further confirm that the interface between h-BN and metallic Fe can be recovered by vacuum annealing at ∼600 °C, although this is accompanied by the creation of defects within the h-BN film. We discuss the importance of these findings in the context of integrated manufacturing and transfer-free device integration of h-BN, particularly for technologically important applications where h-BN has potential as a tunnel barrier such as magnetic tunnel junctions.

  4. Concentration-Polarization, Electro-Convection and Colloid Dynamics in Microchannel-Nanochannel Interface Devices

    Science.gov (United States)

    Yossifon, Gilad; Leibowitz, Neta; Green, Yoav; Liel, Uri; Schiffbauer, Jarrod; Park, Sinwook

    2014-11-01

    Understanding concentration-polarization (CP) and electroconvection processes along with colloid dynamics in microchannel-nanochannel/membrane interface devices are of particular interest in the field of micro- and nano-fluidics. Our design consists of a nano-slot/permselective membrane bounded by two micro-chambers, wherein we introduce dispersed colloids. Here we report various curios phenomena occurring in these systems. Among them: dielectrophoretic trapping of colloids at the nanoslot entrance in conjunction with the formation of electro-convective instability induced vortices; accumulation of colloids due field-focusing gradient effects within the diffusion layers; depression of the slope in the Warburg branch of the electrochemical impedance spectrum with increasing dc bias voltage as a result of nanochannel net electro-osmotic flow; suppression of the diffusion layer length via AC electrokinetics and its effect on ion transport; anomalous resistance minimum and unique chronopotentiometric signatures due to non-ideal nanochannel permselectivity. All of these stand as examples that highlight the essential differences between fabricated straight nanoslot and permselective membrane systems.

  5. Ultra low-power integrated circuit design for wireless neural interfaces

    CERN Document Server

    Holleman, Jeremy; Otis, Brian

    2014-01-01

    Presenting results from real prototype systems, this volume provides an overview of ultra low-power integrated circuits and systems for neural signal processing and wireless communication. Topics include analog, radio, and signal processing theory and design for ultra low-power circuits.

  6. Sensitive and selective neural control using an intraneural multielectrode stimulation device in silicon technology

    NARCIS (Netherlands)

    Rutten, Wim; van Wier, H.J.; Put, J.H.M.; Meier, J.H.

    1988-01-01

    The ideal neural stimulatory information transducer must be able to activate individual neural fibers within a fascicular bundle, for example in a sensory or motor nerve. In a local approach using microelectrodes it is sufficient to apply current pulses to one neural node in order to reach the

  7. TTC Interface Module for ATLAS Read-Out Electronics Final production version based on Xilinx FPGA devices

    CERN Document Server

    Butterworth, J; Postranecky, M; Warren, M R M; 10th Workshop on Electronics for LHC and Future Experiments

    2004-01-01

    The functionality and the details of firmware, software and hardware of the Xilinx FPGA-based production version of the ATLAS-SCT TTC Interface Module ( TIM ) are described. The TIM interfaces to the ATLAS Level-1 Trigger, using the LHC-standard TTC ( Timing, Trigger and Control ) system. Twelve prototype TIM modules have been built and used since 2001, based around ten AMD/Lattice CPLD devices. Final production modules, based on two Xilinx FPGAs, are all being built this year. The details of the hardware and firmware transition from CPLD to FPGA version are described, including the use of new software tools.

  8. Ultra-low-power and robust digital-signal-processing hardware for implantable neural interface microsystems.

    Science.gov (United States)

    Narasimhan, S; Chiel, H J; Bhunia, S

    2011-04-01

    Implantable microsystems for monitoring or manipulating brain activity typically require on-chip real-time processing of multichannel neural data using ultra low-power, miniaturized electronics. In this paper, we propose an integrated-circuit/architecture-level hardware design framework for neural signal processing that exploits the nature of the signal-processing algorithm. First, we consider different power reduction techniques and compare the energy efficiency between the ultra-low frequency subthreshold and conventional superthreshold design. We show that the superthreshold design operating at a much higher frequency can achieve comparable energy dissipation by taking advantage of extensive power gating. It also provides significantly higher robustness of operation and yield under large process variations. Next, we propose an architecture level preferential design approach for further energy reduction by isolating the critical computation blocks (with respect to the quality of the output signal) and assigning them higher delay margins compared to the noncritical ones. Possible delay failures under parameter variations are confined to the noncritical components, allowing graceful degradation in quality under voltage scaling. Simulation results using prerecorded neural data from the sea-slug (Aplysia californica) show that the application of the proposed design approach can lead to significant improvement in total energy, without compromising the output signal quality under process variations, compared to conventional design approaches.

  9. Neural Correlates of Phrase Quadrature Perception in Harmonic Rhythm: An EEG Study (Using a Brain-Computer Interface).

    Science.gov (United States)

    Fernández-Sotos, Alicia; Martínez-Rodrigo, Arturo; Moncho-Bogani, José; Latorre, José Miguel; Fernández-Caballero, Antonio

    2017-11-13

    For the sake of establishing the neural correlates of phrase quadrature perception in harmonic rhythm, a musical experiment has been designed to induce music-evoked stimuli related to one important aspect of harmonic rhythm, namely the phrase quadrature. Brain activity is translated to action through electroencephalography (EEG) by using a brain-computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. The results of processing the acquired signals are in line with previous studies that use different musical parameters to induce emotions. Indeed, our experiment shows statistical differences in theta and alpha bands between the fulfillment and break of phrase quadrature, an important cue of harmonic rhythm, in two classical sonatas.

  10. Highly Sensitive Textile Strain Sensors and Wireless User-Interface Devices Using All-Polymeric Conducting Fibers.

    Science.gov (United States)

    Eom, Jimi; Jaisutti, Rawat; Lee, Hyungseok; Lee, Woobin; Heo, Jae-Sang; Lee, Jun-Young; Park, Sung Kyu; Kim, Yong-Hoon

    2017-03-22

    Emulation of diverse electronic devices on textile platform is considered as a promising approach for implementing wearable smart electronics. Of particular, the development of multifunctional polymeric fibers and their integration in common fabrics have been extensively researched for human friendly wearable platforms. Here we report a successful emulation of multifunctional body-motion sensors and user-interface (UI) devices in textile platform by using in situ polymerized poly(3,4-ethylenedioxythiophene) (PEDOT)-coated fibers. With the integration of PEDOT fibers in a fabric, via an optimization of the fiber pattern design, multifunctional textile sensors such as highly sensitive and reliable strain sensors (with maximum gauge factor of ∼1), body-motion monitoring sensors, touch sensors, and multilevel strain recognition UI devices were successfully emulated. We demonstrate the facile utilization of the textile-based multifunctional sensors and UI devices by implementing in a wireless system that is capable of expressing American Sign Language through predefined hand gestures.

  11. Differential Medical Aerosol Device and Interface Selection in Patients during Spontaneous, Conventional Mechanical and Noninvasive Ventilation.

    Science.gov (United States)

    Ari, Arzu; Fink, James B

    2016-04-01

    Many aerosol delivery devices are available on the market that have different features, characteristics, and operating requirements that need to be considered for the effective treatment of patients with pulmonary diseases. Device selection in aerosol medicine is largely patient dependent. Since there is no aerosol device that suits all patient populations, device selection and successful integration of the prescribed aerosol device to patients is essential. This article explores key issues in differential device selection in spontaneously breathing adults with or without artificial airways, as well as critically ill patients receiving invasive and noninvasive ventilation, with discussion of considerations for integration of aerosol devices to each of these patient populations.

  12. Pig dorsum model for examining impaired wound healing at the skin-implant interface of percutaneous devices.

    Science.gov (United States)

    Holt, Brian Mueller; Betz, Daniel Holod; Ford, Taylor Ann; Beck, James Peter; Bloebaum, Roy Drake; Jeyapalina, Sujee

    2013-09-01

    Percutaneous medical devices are indispensable in contemporary clinical practice, but the associated incidence of low to moderate mortality infections represents a significant economic and personal cost to patients and healthcare providers. Percutaneous osseointegrated prosthetics also suffer from a similar risk of infection, limiting their clinical acceptance and usage in patients with limb loss. We hypothesized that transepidermal water loss (TEWL) management at the skin-implant interface may improve and maintain a stable skin-to-implant interface. In this study, skin reactions in a 3-month, pig dorsum model were assessed using standard histology, immunohistochemistry, and quantitative image analysis. Immunohistochemical analysis of peri-implant tissue explants showed evidence of: continuous healing (cytokeratin 6+), hypergranulation tissue (procollagen+), hyper-vascularity (collagen 4+), and the presence of fibrocytes (CD45+ and procollagen type 1+). Importantly, the gross skin response was correlated to a previous load-bearing percutaneous osseointegrated prosthetic sheep study conducted in our lab. The skin responses of the two models indicated a potentially shared mechanism of wound healing behavior at the skin-implant interface. Although TEWL management did not reduce skin migration at the skin-implant interface, the correlation of qualitative and quantitative measures validated the pig dorsum model as a high-throughput platform for translational science based percutaneous interface investigations in the future.

  13. Smoothing effect of the thermal interface material on the temperature distribution in a stepwise varying width microchannel cooling device

    Science.gov (United States)

    Riera, Sara; Barrau, Jérôme; Rosell, Joan I.; Fréchette, Luc G.; Omri, Mohamed; Vilarrubí, Montse; Laguna, Gerard

    2017-09-01

    The impact of the thermal interface material (TIM) layer on the performance of a stepwise varying width microchannel cooling device is analysed. A numerical model shows that the TIM layer, besides its well known negative impact on the temperature, also generates a smoothing effect on the temperature distribution. In this study, an analytical model is used to define a nondimensional parameter, called Smoothing Resistance ratio, as the quotient between the origin of the temperature non uniformities and the TIM thermal resistance that flatten the temperature distribution. The relationship between the temperature uniformity of the cooled device, expressed through the temperature standard deviation, and the Smoothing Resistance ratio is shown to be linear. These results lead to the definition of a new design procedure for this kind of cooling device, which aims to reduce the Smoothing Resistance ratio. Two solutions are identified and their drawbacks are analysed.

  14. EDITORIAL: Deep brain stimulation, deontology and duty: the moral obligation of non-abandonment at the neural interface Deep brain stimulation, deontology and duty: the moral obligation of non-abandonment at the neural interface

    Science.gov (United States)

    Fins, Joseph J.; MD; FACP

    2009-10-01

    intrusions on their bodies and their selves. Previously, I suggested that stimulation parameters for the treatment of neuropsychiatric disorders might be manipulated by patients one day. I envisioned a degree of patient discretion, within a pre-set safe range determined by physicians, much like patient-controlled analgesia (PCA) pumps give patients control over the dosing of opioid analgesia [3]. I am glad that such an advance is evolving as a means to preserve batteries in the treatment of motor disorders [16]. I would encourage the neural engineers to embrace the ethical mandate to develop additional platforms that might enhance patient self-determination and foster a greater degree of functional independence. While the neuromodulation community has every reason to celebrate its accomplishments, it would be better served by appreciating that the insertion of a device into the human brain comes with, if not the penumbra of sacrilege, a moral obligation to step out of the shadows and remain clearly available to patients and families over the long haul. Although neuromodulation has liberated many patients from the shackles of disease, we need to appreciate that the hardware that has made this possible can remain tethering. The challenge for the next generation of innovators is to minimize these burdens at this neural interface. By reducing barriers to care that exist in an unprepared health care system and developing more user-friendly technology, the neuromodulation community can expand its reach and broaden the relief provided by these neuro-palliative interventions [17]. Acknowledgements and Disclosures Dr Fins is the recipient of an Investigator Award in Health Policy Research (Minds Apart: Severe Brain Injury and Health Policy) from The Robert Wood Johnson Foundation. He also gratefully acknowledges grant support from the Buster Foundation (Neuroethics and Disorders of Consciousness). He is an unfunded co-investigator of a study of deep brain stimulation in the minimally

  15. Neural correlates of learning in an electrocorticographic motor-imagery brain-computer interface

    Science.gov (United States)

    Blakely, Tim M.; Miller, Kai J.; Rao, Rajesh P. N.; Ojemann, Jeffrey G.

    2014-01-01

    Human subjects can learn to control a one-dimensional electrocorticographic (ECoG) brain-computer interface (BCI) using modulation of primary motor (M1) high-gamma activity (signal power in the 75–200 Hz range). However, the stability and dynamics of the signals over the course of new BCI skill acquisition have not been investigated. In this study, we report 3 characteristic periods in evolution of the high-gamma control signal during BCI training: initial, low task accuracy with corresponding low power modulation in the gamma spectrum, followed by a second period of improved task accuracy with increasing average power separation between activity and rest, and a final period of high task accuracy with stable (or decreasing) power separation and decreasing trial-to-trial variance. These findings may have implications in the design and implementation of BCI control algorithms. PMID:25599079

  16. In-Line Acoustic Device Inspection of Leakage in Water Distribution Pipes Based on Wavelet and Neural Network

    Directory of Open Access Journals (Sweden)

    Dileep Kumar

    2017-01-01

    Full Text Available Traditionally permanent acoustic sensors leak detection techniques have been proven to be very effective in water distribution pipes. However, these methods need long distance deployment and proper position of sensors and cannot be implemented on underground pipelines. An inline-inspection acoustic device is developed which consists of acoustic sensors. The device will travel by the flow of water through the pipes which record all noise events and detect small leaks. However, it records all the noise events regarding background noises, but the time domain noisy acoustic signal cannot manifest complete features such as the leak flow rate which does not distinguish the leak signal and environmental disturbance. This paper presents an algorithm structure with the modularity of wavelet and neural network, which combines the capability of wavelet transform analyzing leakage signals and classification capability of artificial neural networks. This study validates that the time domain is not evident to the complete features regarding noisy leak signals and significance of selection of mother wavelet to extract the noise event features in water distribution pipes. The simulation consequences have shown that an appropriate mother wavelet has been selected and localized to extract the features of the signal with leak noise and background noise, and by neural network implementation, the method improves the classification performance of extracted features.

  17. Blood-neural barrier: intercellular communication at glio-vascular interface.

    Science.gov (United States)

    Kim, Jung Hun; Kim, Jin Hyoung; Park, Joeng Ae; Lee, Sae-Won; Kim, Woo Jean; Yu, Young Suk; Kim, Kyu-Won

    2006-07-31

    The blood-neural barrier (BNB), including blood-brain barrier (BBB) and blood-retinal barrier (BRB), is an endothelial barrier constructed by an extensive network of endothelial cells, astrocytes and neurons to form functional "neurovascular units", which has an important role in maintaining a precisely regulated microenvironment for reliable neuronal activity. Although failure of the BNB may be a precipitating event or a consequence, the breakdown of BNB is closely related with the development and progression of CNS diseases. Therefore, BNB is most essential in the regulation of microenvironment of the CNS. The BNB is a selective diffusion barrier characterized by tight junctions between endothelial cells, lack of fenestrations, and specific BNB transporters. The BNB have been shown to be astrocyte dependent, for it is formed by the CNS capillary endothelial cells, surrounded by astrocytic end-foot processes. Given the anatomical associations with endothelial cells, it could be supposed that astrocytes play a role in the development, maintenance, and breakdown of the BNB. Therefore, astrocytes-endothelial cells interaction influences the BNB in both physiological and pathological conditions. If we better understand mutual interactions between astrocytes and endothelial cells, in the near future, we could provide a critical solution to the BNB problems and create new opportunities for future success of treating CNS diseases. Here, we focused astrocyte-endothelial cell interaction in the formation and function of the BNB.

  18. im4Things: An Ontology-Based Natural Language Interface for Controlling Devices in the Internet of Things

    KAUST Repository

    Noguera-Arnaldos, José Ángel

    2017-03-14

    The Internet of Things (IoT) offers opportunities for new applications and services that enable users to access and control their working and home environment from local and remote locations, aiming to perform daily life activities in an easy way. However, the IoT also introduces new challenges, some of which arise from the large range of devices currently available and the heterogeneous interfaces provided for their control. The control and management of this variety of devices and interfaces represent a new challenge for non-expert users, instead of making their life easier. Based on this understanding, in this work we present a natural language interface for the IoT, which takes advantage of Semantic Web technologies to allow non-expert users to control their home environment through an instant messaging application in an easy and intuitive way. We conducted several experiments with a group of end users aiming to evaluate the effectiveness of our approach to control home appliances by means of natural language instructions. The evaluation results proved that without the need for technicalities, the user was able to control the home appliances in an efficient way.

  19. Improved interface properties of GaN-based metal-oxide-semiconductor devices with thin Ga-oxide interlayers

    Science.gov (United States)

    Yamada, Takahiro; Ito, Joyo; Asahara, Ryohei; Watanabe, Kenta; Nozaki, Mikito; Hosoi, Takuji; Shimura, Takayoshi; Watanabe, Heiji

    2017-06-01

    The impact of thin Ga-oxide (GaOx) interlayers on the electrical properties of GaN-based metal-oxide-semiconductor (MOS) devices was systematically investigated. Thin thermal oxides formed at around 900 °C were found to be beneficial for improving the electrical properties of insulator/GaN interfaces, despite the fact that thermal oxidation of GaN surfaces at high temperatures proceeds by means of grain growth. Consequently, well-behaved capacitance-voltage characteristics of SiO2/GaOx/n-GaN stacked MOS capacitors with an interface state density (Dit) as low as 1.7 × 1011 cm-2 eV-1 were demonstrated. Moreover, the Dit value was further reduced for the SiO2/GaOx/GaN capacitor with a 2-nm-thick sputter-deposited GaOx interlayer. These results clearly indicate the intrinsically superior nature of the oxide/GaN interfaces and provide plausible guiding principles for fabricating high-performance GaN-MOS devices with thin GaOx interlayers.

  20. Aerospace Ground Equipment for model 4080 sequence programmer. A standard computer terminal is adapted to provide convenient operator to device interface

    Science.gov (United States)

    Nissley, L. E.

    1979-01-01

    The Aerospace Ground Equipment (AGE) provides an interface between a human operator and a complete spaceborne sequence timing device with a memory storage program. The AGE provides a means for composing, editing, syntax checking, and storing timing device programs. The AGE is implemented with a standard Hewlett-Packard 2649A terminal system and a minimum of special hardware. The terminal's dual tape interface is used to store timing device programs and to read in special AGE operating system software. To compose a new program for the timing device the keyboard is used to fill in a form displayed on the screen.

  1. Nano-gold assisted highly conducting and biocompatible bacterial cellulose-PEDOT:PSS films for biology-device interface applications.

    Science.gov (United States)

    Khan, Shaukat; Ul-Islam, Mazhar; Ullah, Muhammad Wajid; Israr, Muhammad; Jang, Jae Hyun; Park, Joong Kon

    2018-02-01

    This study reports the fabrication of highly conducting and biocompatible bacterial cellulose (BC)-gold nanoparticles (AuNPs)-poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) (BC-AuNPs-PEDOT:PSS) composites for biology-device interface applications. The composites were fabricated using ex situ incorporation of AuNPs and PEDOT:PSS into the BC matrix. Structural characterization, using scanning electron microscopy (SEM), atomic force microscopy (AFM), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and x-ray diffraction (XRD) analysis, confirmed the uniform nature of the synthesized BC-AuNPs and BC-AuNPs-PEDOT:PSS composites. Four-point probe analysis indicated that the BC-AuNPs and BC-AuNPs-PEDOT:PSS films had high electrical conductivity. The composites were also tested for biocompatibility with animal osteoblasts (MC3T3-E1). The composite films supported adhesion, growth, and proliferation of MC3T3-E1 cells, indicating that they are biocompatible and non-cytotoxic. AuNPs and PEDOT:PSS, imparted a voltage response, while BC imparted biocompatibility and bio-adhesion to the nanocomposites. Therefore, our BC-AuNPs-PEDOT:PSS composites are candidate materials for biology-device interfaces to produce implantable devices in regenerative medicine. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Plasma-Material Interface Development for Future Spherical Tokamak-based Devices in NSTX.

    Energy Technology Data Exchange (ETDEWEB)

    et. al, V

    2011-09-24

    The divertor plasma-material interface (PMI) must be able to withstand steady-state heat fluxes up to 10 MW/m{sup 2} (a limit imposed by the present day divertor material and engineering constraints) with minimal material erosion, as well as to provide impurity control and ion density pumping capabilities. In spherical tokamaks (STs), the compact divertor geometry and the requirement of low core electron collisionality n*{sub e} at n{sub e} < 0.5-0.7 n{sub G} (where n{sub G} is the Greenwald density) for increased neutral beam current drive efficiency impose much greater demands on divertor and first-wall particle and heat flux mitigation solutions. In NSTX, divertor heat flux mitigation and impurity control with an innovative 'snowflake' divertor configuration and ion density pumping by evaporated lithium wall and divertor coatings are studied. Lithium coatings have enabled ion density reduction up to 50% in NSTX through the reduction of wall and divertor recycling rates. The 'snowflake' divertor configuration was obtained in NSTX in 0.8-1 MA 4-6 MW NBI-heated H-mode lithium-assisted discharges using three divertor coils. The snowflake divertor formation was always accompanied by a partial detachment of the outer strike point with an up to 50% increase in divertor radiation from intrinsic carbon, the peak divertor heat flux reduction from 3-6 MW/m{sup 2} to 0.5-1 MW/m{sup 2}, and a significant increase in divertor volume recombination. High core confinement was maintained with the snowflake divertor, evidenced by the t{sub E}, W{sub MHD} and the H98(y,2) factors similar to those of the standard divertor discharges. Core carbon concentration and radiated power were reduced by 30-70%, apparently as a result of reduced divertor physical and chemical sputtering in the snowflake divertor and ELMs. In the SFD discharges, the MHD stability of the H-mode pedestal region was altered leading to the re-appearance of medium size (DW/W = 5-10%), Type I

  3. Impact of interface charge on the electrostatics of field-plate assisted RESURF devices

    NARCIS (Netherlands)

    Boksteen, B.K.; Ferrara, A.; Heringa, A.; Steeneken, P.G.; Hueting, Raymond Josephus Engelbart

    2014-01-01

    A systematic study on the effects of arbitrary parasitic charge profiles, such as trapped or fixed charge, on the 2-D potential distribution in the drain extension of reverse-biased field-plate-assisted reduced surface field (RESURF) devices is presented. Using TCAD device simulations and analytical

  4. Development of an implantable wireless ECoG 128ch recording device for clinical brain machine interface.

    Science.gov (United States)

    Matsushita, Kojiro; Hirata, Masayuki; Suzuki, Takafumi; Ando, Hiroshi; Ota, Yuki; Sato, Fumihiro; Morris, Shyne; Yoshida, Takeshi; Matsuki, Hidetoshi; Yoshimine, Toshiki

    2013-01-01

    Brain Machine Interface (BMI) is a system that assumes user's intention by analyzing user's brain activities and control devices with the assumed intention. It is considered as one of prospective tools to enhance paralyzed patients' quality of life. In our group, we especially focus on ECoG (electro-corti-gram)-BMI, which requires surgery to place electrodes on the cortex. We try to implant all the devices within the patient's head and abdomen and to transmit the data and power wirelessly. Our device consists of 5 parts: (1) High-density multi-electrodes with a 3D shaped sheet fitting to the individual brain surface to effectively record the ECoG signals; (2) A small circuit board with two integrated circuit chips functioning 128 [ch] analogue amplifiers and A/D converters for ECoG signals; (3) A Wifi data communication & control circuit with the target PC; (4) A non-contact power supply transmitting electrical power minimum 400[mW] to the device 20[mm] away. We developed those devices, integrated them, and, investigated the performance.

  5. Electronic Processes at Organic−Organic Interfaces: Insight from Modeling and Implications for Opto-electronic Devices

    KAUST Repository

    Beljonne, David

    2011-02-08

    We report on the recent progress achieved in modeling the electronic processes that take place at interfaces between π-conjugated materials in organic opto-electronic devices. First, we provide a critical overview of the current computational techniques used to assess the morphology of organic: organic heterojunctions; we highlight the compromises that are necessary to handle large systems and multiple time scales while preserving the atomistic details required for subsequent computations of the electronic and optical properties. We then review some recent theoretical advances in describing the ground-state electronic structure at heterojunctions between donor and acceptor materials and highlight the role played by charge-transfer and long-range polarization effects. Finally, we discuss the modeling of the excited-state electronic structure at organic:organic interfaces, which is a key aspect in the understanding of the dynamics of photoinduced electron-transfer processes. © 2010 American Chemical Society.

  6. Data-driven model comparing the effects of glial scarring and interface interactions on chronic neural recordings in non-human primates.

    Science.gov (United States)

    Malaga, Karlo A; Schroeder, Karen E; Patel, Paras R; Irwin, Zachary T; Thompson, David E; Nicole Bentley, J; Lempka, Scott F; Chestek, Cynthia A; Patil, Parag G

    2016-02-01

    We characterized electrode stability over twelve weeks of impedance and neural recording data from four chronically-implanted Utah arrays in two rhesus macaques, and investigated the effects of glial scarring and interface interactions at the electrode recording site on signal quality using a computational model. A finite-element model of a Utah array microelectrode in neural tissue was coupled with a multi-compartmental model of a neuron to quantify the effects of encapsulation thickness, encapsulation resistivity, and interface resistivity on electrode impedance and waveform amplitude. The coupled model was then reconciled with the in vivo data. Histology was obtained seventeen weeks post-implantation to measure gliosis. From week 1-3, mean impedance and amplitude increased at rates of 115.8 kΩ/week and 23.1 μV/week, respectively. This initial ramp up in impedance and amplitude was observed across all arrays, and is consistent with biofouling (increasing interface resistivity) and edema clearing (increasing tissue resistivity), respectively, in the model. Beyond week 3, the trends leveled out. Histology showed that thin scars formed around the electrodes. In the model, scarring could not match the in vivo data. However, a thin interface layer at the electrode tip could. Despite having a large effect on impedance, interface resistivity did not have a noticeable effect on amplitude. This study suggests that scarring does not cause an electrical problem with regard to signal quality since it does not appear to be the main contributor to increasing impedance or significantly affect amplitude unless it displaces neurons. This, in turn, suggests that neural signals can be obtained reliably despite scarring as long as the recording site has sufficiently low impedance after accumulating a thin layer of biofouling. Therefore, advancements in microelectrode technology may be expedited by focusing on improvements to the recording site-tissue interface rather than

  7. Data-driven model comparing the effects of glial scarring and interface interactions on chronic neural recordings in non-human primates

    Science.gov (United States)

    Malaga, Karlo A.; Schroeder, Karen E.; Patel, Paras R.; Irwin, Zachary T.; Thompson, David E.; Bentley, J. Nicole; Lempka, Scott F.; Chestek, Cynthia A.; Patil, Parag G.

    2016-02-01

    Objective. We characterized electrode stability over twelve weeks of impedance and neural recording data from four chronically-implanted Utah arrays in two rhesus macaques, and investigated the effects of glial scarring and interface interactions at the electrode recording site on signal quality using a computational model. Approach. A finite-element model of a Utah array microelectrode in neural tissue was coupled with a multi-compartmental model of a neuron to quantify the effects of encapsulation thickness, encapsulation resistivity, and interface resistivity on electrode impedance and waveform amplitude. The coupled model was then reconciled with the in vivo data. Histology was obtained seventeen weeks post-implantation to measure gliosis. Main results. From week 1-3, mean impedance and amplitude increased at rates of 115.8 kΩ/week and 23.1 μV/week, respectively. This initial ramp up in impedance and amplitude was observed across all arrays, and is consistent with biofouling (increasing interface resistivity) and edema clearing (increasing tissue resistivity), respectively, in the model. Beyond week 3, the trends leveled out. Histology showed that thin scars formed around the electrodes. In the model, scarring could not match the in vivo data. However, a thin interface layer at the electrode tip could. Despite having a large effect on impedance, interface resistivity did not have a noticeable effect on amplitude. Significance. This study suggests that scarring does not cause an electrical problem with regard to signal quality since it does not appear to be the main contributor to increasing impedance or significantly affect amplitude unless it displaces neurons. This, in turn, suggests that neural signals can be obtained reliably despite scarring as long as the recording site has sufficiently low impedance after accumulating a thin layer of biofouling. Therefore, advancements in microelectrode technology may be expedited by focusing on improvements to the

  8. A WEARABLE NEURAL INTERFACE FOR REAL TIME TRANSLATION OF SPANISH DEAF SIGN LANGUAGE TO VOICE AND WRITING

    Directory of Open Access Journals (Sweden)

    H. Hidalgo-Silva

    2005-12-01

    Full Text Available This paper describes a work related to the design and implementation of a communication tool for persons withspeech and hearing disabilities. This tool provides to the user a Human-Computer interface capable of the captureand recognition of gestures belonging to the Mexican Spanish Sign Alphabet. To capture the manual expressions, adata-glove constructed to sense the position of fifteen articulations of one of the user’s hand is described. Alocation system that detects the position and movements of the hand with respect to the user’s body is alsoconstructed. The data-glove and location system signals are processed by a pair of programmable automatons. Theautomaton’s outputs are sent to a personal computer that realizes the gesture recognition and interpretation tasks.Artificial neural network techniques are utilized to implement the mappings of the space of information generatedby the instruments to the interpretation space, where the representation of the gestures are found. Once a gestureis captured and interpreted, it is presented in written form through a screen mounted in the clothes of the user,and in verbal form by a speaker.

  9. Neural correlates of user-initiated motor success and failure - A brain-computer interface perspective.

    Science.gov (United States)

    Yazmir, Boris; Reiner, Miriam

    2016-11-02

    Any motor action is, by nature, potentially accompanied by human errors. In order to facilitate development of error-tailored Brain-Computer Interface (BCI) correction systems, we focused on internal, human-initiated errors, and investigated EEG correlates of user outcome successes and errors during a continuous 3D virtual tennis game against a computer player. We used a multisensory, 3D, highly immersive environment. Missing and repelling the tennis ball were considered, as 'error' (miss) and 'success' (repel). Unlike most previous studies, where the environment "encouraged" the participant to perform a mistake, here errors happened naturally, resulting from motor-perceptual-cognitive processes of incorrect estimation of the ball kinematics, and can be regarded as user internal, self-initiated errors. Results show distinct and well-defined Event-Related Potentials (ERPs), embedded in the ongoing EEG, that differ across conditions by waveforms, scalp signal distribution maps, source estimation results (sLORETA) and time-frequency patterns, establishing a series of typical features that allow valid discrimination between user internal outcome success and error. The significant delay in latency between positive peaks of error- and success-related ERPs, suggests a cross-talk between top-down and bottom-up processing, represented by an outcome recognition process, in the context of the game world. Success-related ERPs had a central scalp distribution, while error-related ERPs were centro-parietal. The unique characteristics and sharp differences between EEG correlates of error/success provide the crucial components for an improved BCI system. The features of the EEG waveform can be used to detect user action outcome, to be fed into the BCI correction system. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  10. Motor-related brain activity during action observation: a neural substrate for electrocorticographic brain-computer interfaces after spinal cord injury

    Directory of Open Access Journals (Sweden)

    Jennifer L Collinger

    2014-02-01

    Full Text Available After spinal cord injury (SCI, motor commands from the brain are unable to reach peripheral nerves and muscles below the level of the lesion. Action observation, in which a person observes someone else performing an action, has been used to augment traditional rehabilitation paradigms. Similarly, action observation can be used to derive the relationship between brain activity and movement kinematics for a motor-based brain-computer interface (BCI even when the user cannot generate overt movements. BCIs use brain signals to control external devices to replace functions that have been lost due to SCI or other motor impairment. Previous studies have reported congruent motor cortical activity during observed and overt movements using magnetoencephalography (MEG and functional magnetic resonance imaging (fMRI. Recent single-unit studies using intracortical microelectrodes also demonstrated that a large number of motor cortical neurons had similar firing rate patterns between overt and observed movements. Given the increasing interest in electrocorticography (ECoG-based BCIs, our goal was to identify whether action observation-related cortical activity could be recorded using ECoG during grasping tasks. Specifically, we aimed to identify congruent neural activity during observed and executed movements in both the sensorimotor rhythm (10-40 Hz and the high-gamma band (65-115 Hz which contains significant movement-related information. We observed significant motor-related high-gamma band activity during action observation in both able-bodied individuals and one participant with a complete C4 SCI. Furthermore, in able-bodied participants, both the low and high frequency bands demonstrated congruent activity between action execution and observation. Our results suggest that action observation could be an effective and critical procedure for deriving the mapping from ECoG signals to intended movement for an ECoG-based BCI system for individuals with

  11. Multi-objective optimization of pulsatile ventricular assist device hemocompatibility based on neural networks and a genetic algorithm.

    Science.gov (United States)

    Xu, Zihao; Yang, Ming; Wang, Xianghui; Wang, Zhong

    2015-08-04

    Given the benefit of pulsatile blood flow for perfusion of coronary arteries and end organs, pulsatile ventricular assist devices (VADs) are still widely used as paracorporeal mechanical circulatory support devices in clinical applications. However, poor hemocompatibility limits the service period of the VADs. Most previous improvements on VAD hemocompatibility were conducted by trial-and-error CFD analysis, which does not easily arrive at the best solution. In this paper, a multi-objective optimization method integrating neural networks and NSGA-II (Non-dominated Sorted Genetic Algorithm-II) based on FSI simulation was developed and applied to a pulsatile VAD to optimize its hemocompatibility. First, the VAD blood chamber was parameterized with the principal geometrical parameters. Three hemocompatibility indices including hemolysis, platelet activation, and platelet deposition were chosen as goal functions. The neural networks were built to fit the nonlinear relationship between goal functions and geometrical parameters. Next, a multi-objective optimization algorithm (NSGA-II) was used to search out the Pareto optimal solutions in the built neural networks. Finally, the best compromise solution was selected from the Pareto optimal solutions by a fuzzy membership approach and validated by FSI simulation. The best compromise solution simultaneously possesses an acceptable hemolysis index, platelet activation index, and platelet deposition index, and the corresponding relative errors between the indices predicted by optimization algorithm and the one calculated by FSI simulations are all less than 5%. The results suggest that the proposed multi-objective optimization method has the potential for application in optimizing pulsatile VAD hemocompatibility, and may also be applied to other blood-wetted devices.

  12. Brain-machine interface control of a manipulator using small-world neural network and shared control strategy.

    Science.gov (United States)

    Li, Ting; Hong, Jun; Zhang, Jinhua; Guo, Feng

    2014-03-15

    The improvement of the resolution of brain signal and the ability to control external device has been the most important goal in BMI research field. This paper describes a non-invasive brain-actuated manipulator experiment, which defined a paradigm for the motion control of a serial manipulator based on motor imagery and shared control. The techniques of component selection, spatial filtering and classification of motor imagery were involved. Small-world neural network (SWNN) was used to classify five brain states. To verify the effectiveness of the proposed classifier, we replace the SWNN classifier by a radial basis function (RBF) networks neural network, a standard multi-layered feed-forward backpropagation network (SMN) and a multi-SVM classifier, with the same features for the classification. The results also indicate that the proposed classifier achieves a 3.83% improvement over the best results of other classifiers. We proposed a shared control method consisting of two control patterns to expand the control of BMI from the software angle. The job of path building for reaching the 'end' point was designated as an assessment task. We recorded all paths contributed by subjects and picked up relevant parameters as evaluation coefficients. With the assistance of two control patterns and series of machine learning algorithms, the proposed BMI originally achieved the motion control of a manipulator in the whole workspace. According to experimental results, we confirmed the feasibility of the proposed BMI method for 3D motion control of a manipulator using EEG during motor imagery. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. CISSY: A station for preparation and surface/interface analysis of thin film materials and devices

    Directory of Open Access Journals (Sweden)

    Iver Lauermann

    2016-04-01

    Full Text Available The CISSY end station combines thin film deposition (sputtering, molecular beam epitaxy ambient-pressure methods with surface and bulk-sensitive analysis (photo emission, x-ray emission, x-ray absorption in the same UHV system, allowing fast and contamination–free transfer between deposition and analysis. It is mainly used for the fabrication and characterization of thin film devices and their components like thin film photovoltaic cells, water-splitting devices and other functional thin film materials.

  14. ER fluid applications to vibration control devices and an adaptive neural-net controller

    Science.gov (United States)

    Morishita, Shin; Ura, Tamaki

    1993-07-01

    Four applications of electrorheological (ER) fluid to vibration control actuators and an adaptive neural-net control system suitable for the controller of ER actuators are described: a shock absorber system for automobiles, a squeeze film damper bearing for rotational machines, a dynamic damper for multidegree-of-freedom structures, and a vibration isolator. An adaptive neural-net control system composed of a forward model network for structural identification and a controller network is introduced for the control system of these ER actuators. As an example study of intelligent vibration control systems, an experiment was performed in which the ER dynamic damper was attached to a beam structure and controlled by the present neural-net controller so that the vibration in several modes of the beam was reduced with a single dynamic damper.

  15. Smartphone-interfaced lab-on-a-chip devices for field-deployable enzyme-linked immunosorbent assay.

    Science.gov (United States)

    Chen, Arnold; Wang, Royal; Bever, Candace R S; Xing, Siyuan; Hammock, Bruce D; Pan, Tingrui

    2014-11-01

    The emerging technologies on mobile-based diagnosis and bioanalytical detection have enabled powerful laboratory assays such as enzyme-linked immunosorbent assay (ELISA) to be conducted in field-use lab-on-a-chip devices. In this paper, we present a low-cost universal serial bus (USB)-interfaced mobile platform to perform microfluidic ELISA operations in detecting the presence and concentrations of BDE-47 (2,2',4,4'-tetrabromodiphenyl ether), an environmental contaminant found in our food supply with adverse health impact. Our point-of-care diagnostic device utilizes flexible interdigitated carbon black electrodes to convert electric current into a microfluidic pump via gas bubble expansion during electrolytic reaction. The micropump receives power from a mobile phone and transports BDE-47 analytes through the microfluidic device conducting competitive ELISA. Using variable domain of heavy chain antibodies (commonly referred to as single domain antibodies or Nanobodies), the proposed device is sensitive for a BDE-47 concentration range of 10(-3)-10(4 ) μg/l, with a comparable performance to that uses a standard competitive ELISA protocol. It is anticipated that the potential impact in mobile detection of health and environmental contaminants will prove beneficial to our community and low-resource environments.

  16. Chemistry of green encapsulating molding compounds at interfaces with other materials in electronic devices

    Energy Technology Data Exchange (ETDEWEB)

    Scandurra, A.; Zafarana, R.; Tenya, Y.; Pignataro, S

    2004-07-31

    The interface chemistry between encapsulating epoxy phenolic molding compound (EMC) containing phosphorous based organic flame retardant (the so called 'green materials') and copper oxide-hydroxide and aluminum oxide-hydroxide surfaces have been studied in comparison with 'conventional' EMC containing bromine and antimony as flame retardant. These green materials are designed to reduce the presence of toxic elements in the electronic packages and, consequently, in the environment. For the study were used a Scanning Acoustic Microscopy for delamination measurements, a dynamometer for the pull strength measurements and an ESCA spectrometer for chemical analysis of the interface. The general behavior of the green compound in terms of delamination, adhesion, and corrosion is found better or at least comparable than that of the conventional EMC.

  17. Methods for studying medical device technology and practitioner cognition: the case of user-interface issues with infusion pumps.

    Science.gov (United States)

    Schraagen, Jan Maarten; Verhoeven, Fenne

    2013-02-01

    The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Starting from a Cognitive Systems Engineering perspective, we developed an Impact Flow Diagram showing the relationship of computer technology, cognition, practitioner behavior, and system failure in the area of medical infusion devices. We subsequently conducted a systematic literature review on user-interface issues with infusion pumps, categorized the studies in terms of methods employed, and noted the usability problems found with particular methods. Next, we assigned usability problems and related methods to the levels in the Impact Flow Diagram. Most study methods used to find user interface issues with infusion pumps focused on observable behavior rather than on how artifacts shape cognition and collaboration. A concerted and theory-driven application of these methods when testing infusion pumps is lacking in the literature. Detailed analysis of one case study provided an illustration of how to apply the Impact Flow Diagram, as well as how the scope of analysis may be broadened to include organizational and regulatory factors. Research methods to uncover use problems with technology may be used in many ways, with many different foci. We advocate the adoption of an Impact Flow Diagram perspective rather than merely focusing on usability issues in isolation. Truly advancing patient safety requires the systematic adoption of a systems perspective viewing people and technology as an ensemble, also in the design of medical device technology. Copyright © 2012 Elsevier Inc. All rights reserved.

  18. A serial sample loading system: interfacing multiwell plates with microfluidic devices.

    Science.gov (United States)

    Rane, Tushar D; Zec, Helena C; Wang, Tza-Huei

    2012-10-01

    There is an increasing demand for novel high-throughput screening (HTS) technologies in the pharmaceutical and biotechnological industries. The robotic sample-handling techniques currently used in these industries, although fast, are still limited to operating in multiwell plates with the sample volumes per reaction in the microliter regime. Digital microfluidics offers an alternative for reduction in sample volume consumption for HTS but lacks a reliable technique for transporting a large number of samples to the microfluidic device. In this report, we develop a technique for serial delivery of sample arrays to a microfluidic device from multiwell plates, through a single sample inlet. Under this approach, a serial array of sample plugs, separated by an immiscible carrier fluid, is loaded into a capillary and delivered to a microfluidic device. Similar approaches have been attempted in the past, however, either with a slower sample loading device such as a syringe pump or vacuum-based sample loading with limited driving pressure. We demonstrated the application of our positive-pressure-based serial sample loading (SSL) system to load a series of sample plugs into a capillary. The adaptability of the SSL system to generate sample plugs with a variety of volumes in a predictable manner was also demonstrated.

  19. The California Connection: Interfacing a Telecommunication Device for the Deaf (TDD) and an Apple Computer.

    Science.gov (United States)

    Pflaum, Michael E.

    1982-01-01

    California's legislation mandating free telecommunication devices for the deaf (TDDs) to hearing and/or speech impaired persons is discussed, as are approaches used in San Diego to distribute them. The TDD's capabilities of communicating with other computer systems are described and an example of an electronic mail system is given. (CL)

  20. Electric field and interface charge extraction in field-plate assisted RESURF devices

    NARCIS (Netherlands)

    Boksteen, B.K.; Heringa, Anco; Ferrara, A.; Steeneken, Peter G.; Schmitz, Jurriaan; Hueting, Raymond Josephus Engelbart

    2015-01-01

    A methodology for extracting the lateral electric field (Ex) in the drain extension of thin silicon-on-insulator high-voltage field-plate assisted reduced surface field (RESURF) devices is detailed including its limits and its accuracy. Analytical calculations and technology computer-aided design

  1. A P300-based brain-computer interface aimed at operating electronic devices at home for severely disabled people.

    Science.gov (United States)

    Corralejo, Rebeca; Nicolás-Alonso, Luis F; Alvarez, Daniel; Hornero, Roberto

    2014-10-01

    The present study aims at developing and assessing an assistive tool for operating electronic devices at home by means of a P300-based brain-computer interface (BCI). Fifteen severely impaired subjects participated in the study. The developed tool allows users to interact with their usual environment fulfilling their main needs. It allows for navigation through ten menus and to manage up to 113 control commands from eight electronic devices. Ten out of the fifteen subjects were able to operate the proposed tool with accuracy above 77 %. Eight out of them reached accuracies higher than 95 %. Moreover, bitrates up to 20.1 bit/min were achieved. The novelty of this study lies in the use of an environment control application in a real scenario: real devices managed by potential BCI end-users. Although impaired users might not be able to set up this system without aid of others, this study takes a significant step to evaluate the degree to which such populations could eventually operate a stand-alone system. Our results suggest that neither the type nor the degree of disability is a relevant issue to suitably operate a P300-based BCI. Hence, it could be useful to assist disabled people at home improving their personal autonomy.

  2. Coherent vertical electron transport and interface roughness effects in AlGaN/GaN intersubband devices

    Science.gov (United States)

    Grier, A.; Valavanis, A.; Edmunds, C.; Shao, J.; Cooper, J. D.; Gardner, G.; Manfra, M. J.; Malis, O.; Indjin, D.; Ikonić, Z.; Harrison, P.

    2015-12-01

    We investigate electron transport in epitaxially grown nitride-based resonant tunneling diodes (RTDs) and superlattice sequential tunneling devices. A density-matrix model is developed, and shown to reproduce the experimentally measured features of the current-voltage curves, with its dephasing terms calculated from semi-classical scattering rates. Lifetime broadening effects are shown to have a significant influence in the experimental data. Additionally, it is shown that the interface roughness geometry has a large effect on current magnitude, peak-to-valley ratios and misalignment features; in some cases eliminating negative differential resistance entirely in RTDs. Sequential tunneling device characteristics are dominated by a parasitic current that is most likely to be caused by dislocations; however, excellent agreement between the simulated and experimentally measured tunneling current magnitude and alignment bias is demonstrated. This analysis of the effects of scattering lifetimes, contact doping and growth quality on electron transport highlights critical optimization parameters for the development of III-nitride unipolar electronic and optoelectronic devices.

  3. Robots and therapeutic play: evaluation of a wireless interface device for interaction with a robot playmate.

    Science.gov (United States)

    Roberts, Luke; Park, Hae Won; Howard, Ayanna M

    2012-01-01

    Rehabilitation robots in home environments has the potential to dramatically improve quality of life for individuals who experience disabling circumstances due to injury or chronic health conditions. Unfortunately, although classes of robotic systems for rehabilitation exist, these devices are typically not designed for children. And since over 150 million children in the world live with a disability, this causes a unique challenge for deploying such robotics for this target demographic. To overcome this barrier, we discuss a system that uses a wireless arm glove input device to enable interaction with a robotic playmate during various play scenarios. Results from testing the system with 20 human subjects shows that the system has potential, but certain aspects need to be improved before deployment with children.

  4. Three-dimensional extracellular matrix-mediated neural stem cell differentiation in a microfluidic device.

    Science.gov (United States)

    Han, Sewoon; Yang, Kisuk; Shin, Yoojin; Lee, Jung Seung; Kamm, Roger D; Chung, Seok; Cho, Seung-Woo

    2012-07-07

    Here, we report a unique method to quantify the effects of in vivo-like extracellular matrix (ECM) for guiding differentiation of neural stem cells (NSCs) in three-dimensional (3D) microenvironments using quantitative real-time polymerase chain reaction (qRT-PCR). We successfully monitored and quantified differentiation of NSCs in small volume ECMs and found that differentiation of NSCs, especially those differentiating towards neuronal and oligodendrocytic lineages, is significantly enhanced by 3D microenvironments reconstituted in the microfluidic channels.

  5. Application of Artificial Neural Networks in Modeling Direction Wheelchairs Using Neurosky Mindset Mobile (EEG Device

    Directory of Open Access Journals (Sweden)

    Agus Siswoyo

    2017-07-01

    Full Text Available The implementation of Artificial Neural Network in prediction the direction of electric wheelchair from brain signal input for physical mobility impairment.. The control of the wheelchair as an effort in improving disabled person life quality. The interaction from disabled person is helping in relation to social life with others. Because of the mobility impairment, the wheelchair with brain signal input is made. This wheel chair is purposed to help the disabled person and elderly for their daily activity. ANN helps to develop the mapping from input to target. ANN is developed in 3 level: input level, one hidden level, and output level (6-2-1. There are 6 signal from Neurosky Mindset sensor output, Alpha1, Alpha2, Raw signal, Total time signal, Attention Signal, and Meditation signal. The purpose of this research is to find out the output value from ANN: value in turning right, turning left, and forward. From those outputs, we can prove the relevance to the target. One of the main problem that interfering with success is the problem of proper neural network training. Arduino uno is chosen to implement the learning program algorithm because it is a popular microcontroller that is economic and efficient. The training of artificial neural network in this research uses 21 data package from raw data, Alpha1, Aplha2, Meditation data, Attention data, total time data. At the time of the test there is a value of Mean square Error(MSE at the end of training amounted to 0.92495 at epoch 9958, value a correlation coefficient of 0.92804 shows that accuracy the results of the training process good.     Keywords: Navigation, Neural network, Real-time training, Arduino

  6. Interface Engineering and Morphology Study of Thin Film Organic-Inorganic Halide Perovskite Optoelectronic Devices

    Science.gov (United States)

    Meng, Lei

    Solar energy harvesting through photovoltaic conversion has gained great attention as a sustainable and environmentally friendly solution to meet the rapidly increasing global energy demand. Currently, the high cost of solar-cell technology limits its widespread use. This situation has generated considerable interest in developing alternative solar-cell technologies that reduce cost through the use of less expensive materials and processes. Perovskite solar cells provide a promising low-cost technology for harnessing this energy source. In Chapter two, a moisture-assist method is introduced and studied to facilitate grain growth of solution processed perovskite films. As an approach to achieve high-quality perovskite films, I anneal the precursor film in a humid environment (ambient air) to dramatically increase grain size, carrier mobility, and charge carrier lifetime, thus improving electrical and optical properties and enhancing photovoltaic performance. It is revealed that mild moisture has a positive effect on perovskite film formation, demonstrating perovskite solar cells with 17.1% power conversion efficiency. Later on, in Chapter four, an ultrathin flexible device delivering a PCE of 14.0% is introduced. The device is based on silver-mesh substrates exhibiting superior durability against mechanical bending. Due to their low energy of formation, organic lead iodide perovskites are also susceptible to degradation in moisture and air. The charge transport layer therefore plays a key role in protecting the perovskite photoactive layer from exposure to such environments, thus achieving highly stable perovskite-based photovoltaic cells. Although incorporating organic charge transport layers can provide high efficiencies and reduced hysteresis, concerns remain regarding device stability and the cost of fabrication. In this work, perovskite solar cells that have all solution-processed metal oxide charge transport layers were demonstrated. Stability has been

  7. Myoelectric neural interface enables accurate control of a virtual multiple degree-of-freedom foot-ankle prosthesis.

    Science.gov (United States)

    Tkach, D C; Lipschutz, R D; Finucane, S B; Hargrove, L J

    2013-06-01

    Technological advances have enabled clinical use of powered foot-ankle prostheses. Although the fundamental purposes of such devices are to restore natural gait and reduce energy expenditure by amputees during walking, these powered prostheses enable further restoration of ankle function through possible voluntary control of the powered joints. Such control would greatly assist amputees in daily tasks such as reaching, dressing, or simple limb repositioning for comfort. A myoelectric interface between an amputee and the powered foot-ankle prostheses may provide the required control signals for accurate control of multiple degrees of freedom of the ankle joint. Using a pattern recognition classifier we compared the error rates of predicting up to 7 different ankle-joint movements using electromyographic (EMG) signals collected from below-knee, as well as below-knee combined with above-knee muscles of 12 trans-tibial amputee and 5 control subjects. Our findings suggest very accurate (5.3 ± 0.5%SE mean error) real-time control of a 1 degree of freedom (DOF) of ankle joint can be achieved by amputees using EMG from as few as 4 below-knee muscles. Reliable control (9.8 ± 0.7%SE mean error) of 3 DOFs can be achieved using EMG from 8 below-knee and above-knee muscles.

  8. Relaxation Effects in MOS Devices due to Tunnel Exchange with Near-Interface Oxide Traps.

    Science.gov (United States)

    Tewksbury, Theodore L., III

    Transistors and capacitors in many types of analog MOS circuits such as charge-redistribution A/D converters, switched-capacitor filters and sample-and-holds, are routinely subjected to momentary large-signal stress conditions during the course of their normal operation. During these transients, charge can be captured by oxide traps close to the Si-SiO _2 interface by tunneling. When the stress is removed, the emission of this trapped charge persists for periods which greatly exceed the capture time, leading to dielectric relaxation in capacitors and transient threshold voltage shifts in MOSFETs. While the amount of trapped charge is too small to be of interest in most digital circuits where the resulting threshold voltage shifts fall comfortably within noise margins, in analog circuits it can lead to hysteresis effects, charge redistribution errors and long-tail components in the settling time of comparators and operational amplifiers with MOS input stages. As analog integrated circuits are pushed towards higher levels of speed and accuracy, these trapping-induced relaxation effects will impose increasingly important performance limitations. Previous experimental studies of charge trapping by near-interface oxide traps have neglected the voltage and time ranges relevant to analog circuits, while existing theories do not provide a complete description of the various mechanisms by which traps can be charged and discharged. This thesis undertakes a detailed characterization of trapping -induced relaxation effects in MOSFETs and capacitors as a function of bias, time, temperature and geometry, under conditions relevant to analog circuit operation. A theoretical description of various relaxation mechanisms is presented and it is shown that the dominant charging/discharging mechanism under the bias conditions of interest is by the elastic tunneling of charge carriers to and from oxide traps. Tunneling occurs directly between the silicon band edges and an oxide trap, or

  9. Interface Characterization of Cobalt Contacts on Bismuth Selenium Telluride for Thermoelectric Devices

    KAUST Repository

    Gupta, R. P.

    2009-08-13

    Sputtered Co is investigated as a suitable contact metal for bulk Bi2 (Te,Se) 3, and the results are compared to sputtered Ni. The coefficient of thermal expansion of Co matches that of bulk Bi 2 (Te,Se) 3 used in our study, and the compatible interface favors the selection of Co as a contact metal. Significant Ni diffusion into Bi2 (Te,Se) 3 was observed. In contrast, Co on Bi2 (Te,Se) 3 shows significantly less diffusion, even at anneal temperatures as high as 200°C. CoTe2 is the preferred phase that is formed. First principles calculations for Bi2 Te 3 support the experimental observation. © 2009 The Electrochemical Society.

  10. Between the devices lines: challenges of contemporary practices in occupational therapy and culture interface

    Directory of Open Access Journals (Sweden)

    Isabela Umbuzeiro Valent

    2016-10-01

    Full Text Available This work discusses the challenge of establishing practices on the interface of occupational therapy and culture. It is based on studies on the problematic field defined by biopolitcs as a regime of hegemonic power composed by the domains of both these areas. It points out topics for the construction of social and cultural participation strategies for people who, for several reasons, live in vulnerable situations. These populations, traditionally received in the field of occupational therapy, circulate differently in the city and challenge the creation of innovative and transversal actions that affirm collective encounters and projects. The artistic practices engendered in certain critical perspective, appear as alternatives to activate experiments that make possible the production of subjectivities from heterogenesis. They are contributions to the set of interdisciplinary studies supporting complex and intersectorial actions which produce autonomy and cultural policies.

  11. Semiconductor heterojunctions at the Conference on the Physics and Chemistry of Semiconductor Interfaces: A device physicist`s perspective

    Energy Technology Data Exchange (ETDEWEB)

    Kroemer, H. [Univ. of California, Santa Barbara, CA (United States)

    1993-07-01

    After a very slow start, heterojunctions have emerged as one of the central topics of the Conference on the Physics and Chemistry of Semiconductor Interfaces. The presentation describes this emergence, starting from such items as the electron affinity rule of conduction band offsets, Dingle`s first determination of the GaAs-(Al,Ga)As band lineups, and the first lineup theories. Some of the blind alleys in this development (85:15 Rule, Common-Anion Rule, and others) are retold by one of the participants. The treatment then turns to a few of the most recent developments, such as the emerging role of ab initio computations as a quasiexperimental tool, plus a few developments this writer finds worth speculating about. The treatment is from the perspective of a device physicist, rather than a surface scientist, and some thoughts are offered on why there is not more commonality between heterojunctions and Schottky barriers. 28 refs., 3 figs.

  12. An investigation on effects of amputee's physiological parameters on maximum pressure developed at the prosthetic socket interface using artificial neural network.

    Science.gov (United States)

    Nayak, Chitresh; Singh, Amit; Chaudhary, Himanshu; Unune, Deepak Rajendra

    2017-10-23

    Technological advances in prosthetics have attracted the curiosity of researchers in monitoring design and developments of the sockets to sustain maximum pressure without any soft tissue damage, skin breakdown, and painful sores. Numerous studies have been reported in the area of pressure measurement at the limb/socket interface, though, the relation between amputee's physiological parameters and the pressure developed at the limb/socket interface is still not studied. Therefore, the purpose of this work is to investigate the effects of patient-specific physiological parameters viz. height, weight, and stump length on the pressure development at the transtibial prosthetic limb/socket interface. Initially, the pressure values at the limb/socket interface were clinically measured during stance and walking conditions for different patients using strain gauges placed at critical locations of the stump. The measured maximum pressure data related to patient's physiological parameters was used to develop an artificial neural network (ANN) model. The effects of physiological parameters on the pressure development at the limb/socket interface were examined using the ANN model. The analyzed results indicated that the weight and stump length significantly affects the maximum pressure values. The outcomes of this work could be an important platform for the design and development of patient-specific prosthetic socket which can endure the maximum pressure conditions at stance and ambulation conditions.

  13. Control of a powered prosthetic device via a pinch gesture interface

    Science.gov (United States)

    Yetkin, Oguz; Wallace, Kristi; Sanford, Joseph D.; Popa, Dan O.

    2015-06-01

    A novel system is presented to control a powered prosthetic device using a gesture tracking system worn on a user's sound hand in order to detect different grasp patterns. Experiments are presented with two different gesture tracking systems: one comprised of Conductive Thimbles worn on each finger (Conductive Thimble system), and another comprised of a glove which leaves the fingers free (Conductive Glove system). Timing tests were performed on the selection and execution of two grasp patterns using the Conductive Thimble system and the iPhone app provided by the manufacturer. A modified Box and Blocks test was performed using Conductive Glove system and the iPhone app provided by Touch Bionics. The best prosthetic device performance is reported with the developed Conductive Glove system in this test. Results show that these low encumbrance gesture-based wearable systems for selecting grasp patterns may provide a viable alternative to EMG and other prosthetic control modalities, especially for new prosthetic users who are not trained in using EMG signals.

  14. Adding tactile realism to a virtual reality laparoscopic surgical simulator with a cost-effective human interface device

    Science.gov (United States)

    Mack, Ian W.; Potts, Stephen; McMenemy, Karen R.; Ferguson, R. S.

    2006-02-01

    The laparoscopic technique for performing abdominal surgery requires a very high degree of skill in the medical practitioner. Much interest has been focused on using computer graphics to provide simulators for training surgeons. Unfortunately, these tend to be complex and have a very high cost, which limits availability and restricts the length of time over which individuals can practice their skills. With computer game technology able to provide the graphics required for a surgical simulator, the cost does not have to be high. However, graphics alone cannot serve as a training simulator. Human interface hardware, the equivalent of the force feedback joystick for a flight simulator game, is required to complete the system. This paper presents a design for a very low cost device to address this vital issue. The design encompasses: the mechanical construction, the electronic interfaces and the software protocols to mimic a laparoscopic surgical set-up. Thus the surgeon has the capability of practicing two-handed procedures with the possibility of force feedback. The force feedback and collision detection algorithms allow surgeons to practice realistic operating theatre procedures with a good degree of authenticity.

  15. A versatile microcomputer interface and peripheral devices: An application in deuterium lamp background correction graphite furnace atomic absorption spectrometry

    Science.gov (United States)

    Gökmen, A.; Yalcin, S.

    1992-01-01

    A versatile interface card for Apple IIe computer and various peripheral devices are designed to control instruments which generates transient signals like in graphite furnace atomic spectrometer. The interface card consists of a multiplexed analog-to-digital converter, a digital-to-analog converter, and a timer/counter chip. The timer/counter chip with 16 built-in registers can be programmed in many modes which provides a time base for real-time measurements. A stepper motor runs under the control of timer/counter chip independent of computer. A light chopper connected to the stepper motor is controlled easily by computer. A dual high-voltage switch can modulate dc light sources under computer control. This system is applied to D2-lamp background correction graphite furnace atomic absorption spectrometer. The D2 lamp is chopped by a mechanical chopper driven by a stepper motor and a hollow cathode lamp is modulated electronically. The data acquisition program is written in machine language and synchronization between light sources and computer is provided by chopper position signal through the interrupts. A sampling rate of 16 during a signal period at 50-Hz chopping frequency is found to be the optimum value. A large number of data collected during atomization period is compressed in machine code. This saved storage space and analysis time.

  16. Tuning the Seebeck effect in C60-based hybrid thermoelectric devices through temperature-dependent surface polarization and thermally-modulated interface dipoles.

    Science.gov (United States)

    Liu, Yuchun; Xu, Ling; Zhao, Chen; Shao, Ming; Hu, Bin

    2017-06-07

    Fullerene (C60) is an important n-type organic semiconductor with high electron mobility and low thermal conductivity. In this work, we report the experimental results on the tunable Seebeck effect of C60 hybrid thin-film devices by adopting different oxide layers. After inserting n-type high-dielectric constant titanium oxide (TiOx) and zinc oxide (ZnO) layers, we observed a significantly enhanced n-type Seebeck effect in oxide/C60 hybrid devices with Seebeck coefficients of -5.8 mV K-1 for TiOx/C60 and -2.08 mV K-1 for ZnO/C60 devices at 100 °C, compared with the value of -400 μV K-1 for the pristine C60 device. However, when a p-type nickel oxide (NiO) layer is inserted, the C60 hybrid devices show a p-type to n-type Seebeck effect transition when the temperature increases. The remarkable Seebeck effect and change in Seebeck coefficient in different oxide/C60 hybrid devices can be attributed to two reasons: the temperature-dependent surface polarization difference and thermally-dependent interface dipoles. Firstly, the surface polarization difference due to temperature-dependent electron-phonon coupling can be enhanced by inserting an oxide layer and functions as an additional driving force for the Seebeck effect development. Secondly, thermally-dependent interface dipoles formed at the electrode/oxide interface play an important role in modifying the density of interface states and affecting the charge diffusion in hybrid devices. The surface polarization difference and interface dipoles function in the same direction in hybrid devices with TiOx and ZnO dielectric layers, leading to enhanced n-type Seebeck effect, while the surface polarization difference and interface dipoles generate the opposite impact on electron diffusion in ITO/NiO/C60/Al, leading to a p-type to n-type transition in the Seebeck effect. Therefore, inserting different oxide layers could effectively modulate the Seebeck effect of C60-based hybrid devices through the surface polarization

  17. Development of a multi-classification neural network model to determine the microbial growth/no growth interface.

    Science.gov (United States)

    Fernández-Navarro, Francisco; Valero, Antonio; Hervás-Martínez, César; Gutiérrez, Pedro A; García-Gimeno, Rosa M; Zurera-Cosano, Gonzalo

    2010-07-15

    Boundary models have been recognized as useful tools to predict the ability of microorganisms to grow at limiting conditions. However, at these conditions, microbial behaviour can vary, being difficult to distinguish between growth or no growth. In this paper, the data from the study of Valero et al. [Valero, A., Pérez-Rodríguez, F., Carrasco, E., Fuentes-Alventosa, J.M., García-Gimeno, R.M., Zurera, G., 2009. Modelling the growth boundaries of Staphylococcus aureus: Effect of temperature, pH and water activity. International Journal of Food Microbiology 133 (1-2), 186-194] belonging to growth/no growth conditions of Staphylococcus aureus against temperature, pH and a(w) were divided into three categorical classes: growth (G), growth transition (GT) and no growth (NG). Subsequently, they were modelled by using a Radial Basis Function Neural Network (RBFNN) in order to create a multi-classification model that was able to predict the probability of belonging at one of the three mentioned classes. The model was developed through an over sampling procedure using a memetic algorithm (MA) in order to balance in part the size of the classes and to improve the accuracy of the classifier. The multi-classification model, named Smote Memetic Radial Basis Function (SMRBF) provided a quite good adjustment to data observed, being able to correctly classify the 86.30% of training data and the 82.26% of generalization data for the three observed classes in the best model. Besides, the high number of replicates per condition tested (n=30) produced a smooth transition between growth and no growth. At the most stringent conditions, the probability of belonging to class GT was higher, thus justifying the inclusion of the class in the new model. The SMRBF model presented in this study can be used to better define microbial growth/no growth interface and the variability associated to these conditions so as to apply this knowledge to a food safety in a decision-making process. 2010

  18. Device preview: Touch-user interface books for overcoming reading difficulty.

    Science.gov (United States)

    Mott, Michael S

    2010-01-01

    To provide a rationale for the newly developed paper-to-digital book product, touch-user-interface (TUI) technology for improving reading comprehension for students with disabilities and developmental constraints. TUI technology, enabling students to touch portions of the pages to actualise corresponding digital files, was theoretically and practically analysed by the author, a content-area expert in (a) reading fluency and comprehension and (b) learning disabilities, for judgment of product utility. Product function was juxtaposed with current reading research depicting learner challenges to fluency and comprehension. TUI technology provides design solutions in-line with meeting student challenges with reading difficulty, namely that traditional paper book pages with 'too much' text block reading comprehension due to low fluency (reading rate is too slow for the brain to make sense of text causing a 'bottleneck' effect) inhibiting understanding. It is proposed that with a TUI book, with media-rich paper, less text can be used and informational equivalence achieved with the digital material activated via touch points on paper pages tethered to a computer. The audio, video and graphics meaning-based symbols systems can replace some text. TUI technology function needs to be evaluated in applied research in classroom settings across exceptionality and development.

  19. A High Performance LIA-Based Interface for Battery Powered Sensing Devices

    Directory of Open Access Journals (Sweden)

    Daniel García-Romeo

    2015-09-01

    Full Text Available This paper proposes a battery-compatible electronic interface based on a general purpose lock-in amplifier (LIA capable of recovering input signals up to the MHz range. The core is a novel ASIC fabricated in 1.8 V 0.18 µm CMOS technology, which contains a dual-phase analog lock-in amplifier consisting of carefully designed building blocks to allow configurability over a wide frequency range while maintaining low power consumption. It operates using square input signals. Hence, for battery-operated microcontrolled systems, where square reference and exciting signals can be generated by the embedded microcontroller, the system benefits from intrinsic advantages such as simplicity, versatility and reduction in power and size. Experimental results confirm the signal recovery capability with signal-to-noise power ratios down to −39 dB with relative errors below 0.07% up to 1 MHz. Furthermore, the system has been successfully tested measuring the response of a microcantilever-based resonant sensor, achieving similar results with better power-bandwidth trade-off compared to other LIAs based on commercial off-the-shelf (COTS components and commercial LIA equipment.

  20. Autologous Cell Delivery to the Skin-Implant Interface via the Lumen of Percutaneous Devices in vitro

    Directory of Open Access Journals (Sweden)

    Antonio Peramo

    2010-11-01

    Full Text Available Induced tissue regeneration around percutaneous medical implants could be a useful method to prevent the failure of the medical device, especially when the epidermal seal around the implant is disrupted and the implant must be maintained over a long period of time. In this manuscript, a novel concept and technique is introduced in which autologous keratinocytes were delivered to the interfacial area of a skin-implant using the hollow interior of a fixator pin as a conduit. Full thickness human skin explants discarded from surgeries were cultured at the air-liquid interface and were punctured to fit at the bottom of hollow cylindrical stainless steel fixator pins. Autologous keratinocytes, previously extracted from the same piece of skin and cultured separately, were delivered to the specimens thorough the interior of the hollow pins. The delivered cells survived the process and resembled undifferentiated epithelium, with variations in size and shape. Viability was demonstrated by the lack of morphologic evidence of necrosis or apoptosis. Although the cells did not form organized epithelial structures, differentiation toward a keratinocyte phenotype was evident immunohistochemically. These results suggest that an adaptation of this technique could be useful for the treatment of complications arising from the contact between skin and percutaneous devices in vivo.

  1. Increasing Trustworthiness of Face Authentication in Mobile Devices by Modeling Gesture Behavior and Location Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Blerim Rexha

    2018-02-01

    Full Text Available Personal mobile devices currently have access to a significant portion of their user’s private sensitive data and are increasingly used for processing mobile payments. Consequently, securing access to these mobile devices is a requirement for securing access to the sensitive data and potentially costly services. Face authentication is one of the promising biometrics-based user authentication mechanisms that has been widely available in this era of mobile computing. With a built-in camera capability on smartphones, tablets, and laptops, face authentication provides an attractive alternative of legacy passwords for its memory-less authentication process, which is so sophisticated that it can unlock the device faster than a fingerprint. Nevertheless, face authentication in the context of smartphones has proven to be vulnerable to attacks. In most current implementations, a sufficiently high-resolution face image displayed on another mobile device will be enough to circumvent security measures and bypass the authentication process. In order to prevent such bypass attacks, gesture recognition together with location is proposed to be additionally modeled. Gestures provide a faster and more convenient method of authentication compared to a complex password. The focus of this paper is to build a secure authentication system with face, location and gesture recognition as components. User gestures and location data are a sequence of time series; therefore, in this paper we propose to use unsupervised learning in the long short-term memory recurrent neural network to actively learn to recognize, group and discriminate user gestures and location. Moreover, a clustering-based technique is also implemented for recognizing gestures and location.

  2. Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network

    NARCIS (Netherlands)

    Chen, Junwen; Liu, Zhigang; Wang, H.; Nunez Vicencio, Alfredo; Han, Zhiwei

    2017-01-01

    The excitation and vibration triggered by the long-term operation of railway vehicles inevitably result in defective states of catenary support devices. With the massive construction of high-speed electrified railways, automatic defect detection of diverse and plentiful fasteners on the catenary

  3. Prediction of Operating Characteristics of Electrotechnical Devices using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    PASCA Alexandra

    2014-05-01

    Full Text Available The paper purpose is to emphasize the possibilities and the advantages to use the artificial intelligence techniques for operating mode prediction of electrotechnical devices. The considered application consists of the analysis of behavior of an inductive proximity sensor at variation of design parameters.

  4. Micro sequential injection system as the interfacing device for process analytical applications.

    Science.gov (United States)

    Wu, Chao-Hsiang Richard; Wee, Siowfong

    2015-01-01

    It is an important and desirable capability to be able to control the quality and quantity of biological product by maintaining and adjusting bioreactor performance throughout its production duration. Amino acids are the building blocks of proteins. Scientists will need to ensure sufficient supply of amino acids as the substrates in the bioreactors as well as to control the excess level of undesirable free amino acid byproducts to maintain an optimum growth environment for cell culture. We have developed a compact and robust sample preparation platform capable of interfacing with analytical instruments to achieve bioreactor amino acids monitoring. We demonstrated the feasibility of this concept by incorporating an automatic amino acid sample preparation protocol to a micro sequential injection (μSI) system connected to an ultra-performance liquid chromatography system for real-time, at-line amino acid separation, and quantitation. The μSI system was configured into a "platform-like" sample preparation system that is able to accommodate future wet chemistry-type sample preparations. Its real-time amino acid results can be readily available to bioprocess scientists for quick decision making and design of their next experiment. Potential automatic feedback control mechanisms can be established through trigger events based on predetermined analytical signal thresholds so the system can communicate with facility infrastructure to control bioreactors in near real-time fashion. The proposed μSI system described in this paper can be widely used as an automatic sample preparation system connected to the front-end of analytical instruments to enable process analytical technology applications. © 2015 American Institute of Chemical Engineers.

  5. Bottle-neck type of neural network as a mapping device towards food specifications.

    Science.gov (United States)

    Novic, Marjana; Groselj, Neva

    2009-09-01

    A novel methodology is proposed for food specifications associated with the origin of food. The methodology was tested on honey samples collected within the TRACE EU project. The data were sampled in various regions in Europe and analysed for the trace elements content. The sampling sites were characterized by different geological origins, such as limestone, shale, or magmatic. We have chosen 14 elements, B, Na, Mg, A, K, Ca, Mn, Co, Ni, Cu, Zn, Rb, Sr, and Ba, due to their influence on the separation of samples regarding the geology of the sampling sites. A special architecture of an error back-propagation neural network, so called bottle-neck type of neural network was used to project the data into a 2D plane. The data were fed into the 14-nodes input layer and then transferred through the 2-nodes hidden layer (compared to a bottle-neck) to the 14-nodes output layer. The two hidden nodes representing the two coordinates of the projection plane enable us to map the samples used for training of the bottle-neck network. With the knowledge about the classes of individual samples we determine the clusters in the projection plane and consequently obtain the coordinates of the centroid (gravity point) of a particular cluster. The clusters are characterized with an ellipse shape borders spanning the length of up to 3sigma in each dimension. Since the data were classified as regard to the geology, three main clusters were sought: (i) limestone, (ii) shale/mudstone/clay/loess, and (iii) acid-magmatic origin of honey samples. The novel methodology proposed for food specifications was demonstrated on a reduced set of samples, which shows good clustering of all three classes in the projection plane, and on the third class of the original data set.

  6. CHAIRMEN'S FOREWORD: The Seventh International Conference on New Phenomena in Mesoscopic Structures & The Fifth International Conference on Surfaces and Interfaces of Mesoscopic Devices

    Science.gov (United States)

    Aoyagi, Yoshinobu; Goodnick, Stephen M.

    2006-05-01

    This special issue of the Journal of Physics: Conference Series contains the proceedings of the joint Seventh International Conference on New Phenomena in Mesoscopic Structures and Fifth International Conference on Surfaces and Interfaces of Mesoscopic Devices, which was held from November 27th - December 2nd, 2005, at the Ritz Carlton Kapalua, Maui, Hawaii. The string of these conferences dates back to the first one in 1989. Of special importance is that this year's conference was dedicated to Professor Gottfried Landwehr, in recognition of his many outstanding contributions to semiconductor physics. A personal tribute to Prof Landwehr by Dr K von Klitzing leads off this issue. The scope of NPMS-7/SIMD-5 spans nano-fabrication through complex phase coherent mesoscopic systems including nano-transistors and nano-scale characterization. Topics of interest include: •Nanoscale fabrication: high-resolution electron lithography, FIB nano-patterning, scanning- force-microscopy (SFM) lithography, SFM-stimulated growth, novel patterning, nano-imprint lithography, special etching, and self-assembled monolayers •Nanocharacterization: SFM characterization, ballistic-electron emission microscopy (BEEM), optical studies of nanostructures, tunneling, properties of discrete impurities, phase coherence, noise, THz studies, and electro-luminescence in small structures •Nanodevices: ultra-scaled FETs, quantum single-electron transistors (SETS), resonant tunneling diodes, ferromagnetic and spin devices, superlattice arrays, IR detectors with quantum dots and wires, quantum point contacts, non-equilibrium transport, simulation, ballistic transport, molecular electronic devices, carbon nanotubes, spin selection devices, spin-coupled quantum dots, and nanomagnetics •Quantum-coherent transport: the quantum Hall effect, ballistic quantum systems, quantum-computing implementations and theory, and magnetic spin systems •Mesoscopic structures: quantum wires and dots, quantum chaos

  7. Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Yongjia Zhao

    2017-02-01

    Full Text Available The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However, it is still a challenging task to reliably extract discriminative features for gait recognition with noisy and complex data sequences collected from casually worn wearable devices like smartphones. To cope with this problem, we propose a novel image-based gait recognition approach using the Convolutional Neural Network (CNN without the need to manually extract discriminative features. The CNN’s input image, which is encoded straightforwardly from the inertial sensor data sequences, is called Angle Embedded Gait Dynamic Image (AE-GDI. AE-GDI is a new two-dimensional representation of gait dynamics, which is invariant to rotation and translation. The performance of the proposed approach in gait authentication and gait labeling is evaluated using two datasets: (1 the McGill University dataset, which is collected under realistic conditions; and (2 the Osaka University dataset with the largest number of subjects. Experimental results show that the proposed approach achieves competitive recognition accuracy over existing approaches and provides an effective parametric solution for identification among a large number of subjects by gait patterns.

  8. Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network.

    Science.gov (United States)

    Zhao, Yongjia; Zhou, Suiping

    2017-02-28

    The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However, it is still a challenging task to reliably extract discriminative features for gait recognition with noisy and complex data sequences collected from casually worn wearable devices like smartphones. To cope with this problem, we propose a novel image-based gait recognition approach using the Convolutional Neural Network (CNN) without the need to manually extract discriminative features. The CNN's input image, which is encoded straightforwardly from the inertial sensor data sequences, is called Angle Embedded Gait Dynamic Image (AE-GDI). AE-GDI is a new two-dimensional representation of gait dynamics, which is invariant to rotation and translation. The performance of the proposed approach in gait authentication and gait labeling is evaluated using two datasets: (1) the McGill University dataset, which is collected under realistic conditions; and (2) the Osaka University dataset with the largest number of subjects. Experimental results show that the proposed approach achieves competitive recognition accuracy over existing approaches and provides an effective parametric solution for identification among a large number of subjects by gait patterns.

  9. A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface

    OpenAIRE

    Su, Yi; Routhu, Sudhamayee; Moon, Kee S.; Lee, Sung Q.; Youm, WooSub; Ozturk, Yusuf

    2016-01-01

    All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in ...

  10. Quantitative Analysis Of User Interfaces For Large Electronic Home Appliances And Mobile Devices Based On Lifestyle Categorization Of Older Users.

    Science.gov (United States)

    Shin, Wonkyoung; Park, Minyong

    2017-01-01

    Background/Study Context: The increasing longevity and health of older users as well as aging populations has created the need to develop senior-oriented product interfaces. This study aims to find user interface (UI) priorities according to older user groups based on their lifestyle and develop quality of UI (QUI) models for large electronic home appliances and mobile products. A segmentation table designed to show how older users can be categorized was created through a review of the literature to survey 252 subjects with a questionnaire. Factor analysis was performed to extract six preliminary lifestyle factors, which were then used for subsequent cluster analysis. The analysis resulted in four groups. Cross-analysis was carried out to investigate which characteristics were included in the groups. Analysis of variance was then applied to investigate the differences in the UI priorities among the user groups for various electronic devices. Finally, QUI models were developed and applied to those electronic devices. Differences in UI priorities were found according to the four lifestyles ("money-oriented," "innovation-oriented," "stability- and simplicity-oriented," and "innovation- and intellectual-oriented"). Twelve QUI models were developed for four different lifestyle groups associated with different products. Three washers and three smartphones were used as an example for testing the QUI models. The UI differences of the older user groups by the segmentation in this study using several key (i.e., demographic, socioeconomic, and physical-cognitive) variables are distinct from earlier studies made by a single variable. The differences in responses clearly indicate the benefits of integrating various factors of older users, rather than single variable, in order to design and develop more innovative and better consumer products in the future. The results of this study showed that older users with a potentially high buying power in the future are likely to have

  11. Poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate)-poly(vinyl alcohol)/poly(acrylic acid) interpenetrating polymer networks for improving optrode-neural tissue interface in optogenetics.

    Science.gov (United States)

    Lu, Yi; Li, Yanling; Pan, Jianqing; Wei, Pengfei; Liu, Nan; Wu, Bifeng; Cheng, Jinbo; Lu, Caiyi; Wang, Liping

    2012-01-01

    The field of optogenetics has been successfully used to understand the mechanisms of neuropsychiatric diseases through the precise spatial and temporal control of specific groups of neurons in a neural circuitry. However, it remains a great challenge to integrate optogenetic modulation with electrophysiological and behavioral read out methods as a means to explore the causal, temporally precise, and behaviorally relevant interactions of neurons in the specific circuits of freely behaving animals. In this study, an eight-channel chronically implantable optrode array was fabricated and modified with poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate)-poly(vinyl alcohol)/poly(acrylic acid) interpenetrating polymer networks (PEDOT/PSS-PVA/PAA IPNs) for improving the optrode-neural tissue interface. The conducting polymer-hydrogel IPN films exhibited a significantly higher capacitance and lower electrochemical impedance at 1 kHz as compared to unmodified optrode sites and showed significantly improved mechanical and electrochemical stability as compared to pure conducting polymer films. The cell attachment and neurite outgrowth of rat pheochromocytoma (PC12) cells on the IPN films were clearly observed through calcein-AM staining. Furthermore, the optrode arrays were chronically implanted into the hippocampus of SD rats after the lentiviral expression of synapsin-ChR2-EYFP, and light-evoked, frequency-dependant action potentials were obtained in freely moving animals. The electrical recording results suggested that the modified optrode arrays showed significantly reduced impedance and RMS noise and an improved SNR as compared to unmodified sites, which may have benefited from the improved electrochemical performance and biocompatibility of the deposited IPN films. All these characteristics are greatly desired in optogenetic applications, and the fabrication method of conducting polymer-hydrogel IPNs can be easily integrated with other modification methods to build a

  12. Engineering the magnetic coupling and anisotropy at the molecule-magnetic surface interface in molecular spintronic devices

    Science.gov (United States)

    Campbell, Victoria E.; Tonelli, Monica; Cimatti, Irene; Moussy, Jean-Baptiste; Tortech, Ludovic; Dappe, Yannick J.; Rivière, Eric; Guillot, Régis; Delprat, Sophie; Mattana, Richard; Seneor, Pierre; Ohresser, Philippe; Choueikani, Fadi; Otero, Edwige; Koprowiak, Florian; Chilkuri, Vijay Gopal; Suaud, Nicolas; Guihéry, Nathalie; Galtayries, Anouk; Miserque, Frederic; Arrio, Marie-Anne; Sainctavit, Philippe; Mallah, Talal

    2016-12-01

    A challenge in molecular spintronics is to control the magnetic coupling between magnetic molecules and magnetic electrodes to build efficient devices. Here we show that the nature of the magnetic ion of anchored metal complexes highly impacts the exchange coupling of the molecules with magnetic substrates. Surface anchoring alters the magnetic anisotropy of the cobalt(II)-containing complex (Co(Pyipa)2), and results in blocking of its magnetization due to the presence of a magnetic hysteresis loop. In contrast, no hysteresis loop is observed in the isostructural nickel(II)-containing complex (Ni(Pyipa)2). Through XMCD experiments and theoretical calculations we find that Co(Pyipa)2 is strongly ferromagnetically coupled to the surface, while Ni(Pyipa)2 is either not coupled or weakly antiferromagnetically coupled to the substrate. These results highlight the importance of the synergistic effect that the electronic structure of a metal ion and the organic ligands has on the exchange interaction and anisotropy occurring at the molecule-electrode interface.

  13. Owgis 2.0: Open Source Java Application that Builds Web GIS Interfaces for Desktop Andmobile Devices

    Science.gov (United States)

    Zavala Romero, O.; Chassignet, E.; Zavala-Hidalgo, J.; Pandav, H.; Velissariou, P.; Meyer-Baese, A.

    2016-12-01

    OWGIS is an open source Java and JavaScript application that builds easily configurable Web GIS sites for desktop and mobile devices. The current version of OWGIS generates mobile interfaces based on HTML5 technology and can be used to create mobile applications. The style of the generated websites can be modified using COMPASS, a well known CSS Authoring Framework. In addition, OWGIS uses several Open Geospatial Consortium standards to request datafrom the most common map servers, such as GeoServer. It is also able to request data from ncWMS servers, allowing the websites to display 4D data from NetCDF files. This application is configured by XML files that define which layers, geographic datasets, are displayed on the Web GIS sites. Among other features, OWGIS allows for animations; streamlines from vector data; virtual globe display; vertical profiles and vertical transects; different color palettes; the ability to download data; and display text in multiple languages. OWGIS users are mainly scientists in the oceanography, meteorology and climate fields.

  14. Integrated control of wind farms, FACTS devices and the power network using neural networks and adaptive critic designs

    Science.gov (United States)

    Qiao, Wei

    Worldwide concern about the environmental problems and a possible energy crisis has led to increasing interest in clean and renewable energy generation. Among various renewable energy sources, wind power is the most rapidly growing one. Therefore, how to provide efficient, reliable, and high-performance wind power generation and distribution has become an important and practical issue in the power industry. In addition, because of the new constraints placed by the environmental and economical factors, the trend of power system planning and operation is toward maximum utilization of the existing infrastructure with tight system operating and stability margins. This trend, together with the increased penetration of renewable energy sources, will bring new challenges to power system operation, control, stability and reliability which require innovative solutions. Flexible ac transmission system (FACTS) devices, through their fast, flexible, and effective control capability, provide one possible solution to these challenges. To fully utilize the capability of individual power system components, e.g., wind turbine generators (WTGs) and FACTS devices, their control systems must be suitably designed with high reliability. Moreover, in order to optimize local as well as system-wide performance and stability of the power system, real-time local and wide-area coordinated control is becoming an important issue. Power systems containing conventional synchronous generators, WTGs, and FACTS devices are large-scale, nonlinear, nonstationary, stochastic and complex systems distributed over large geographic areas. Traditional mathematical tools and system control techniques have limitations to control such complex systems to achieve an optimal performance. Intelligent and bio-inspired techniques, such as swarm intelligence, neural networks, and adaptive critic designs, are emerging as promising alternative technologies for power system control and performance optimization. This

  15. Toward More Versatile and Intuitive Cortical Brain–Machine Interfaces

    OpenAIRE

    Andersen, Richard A.; Kellis, Spencer; Klaes, Christian; Aflalo, Tyson

    2014-01-01

    Brain–machine interfaces have great potential for the development of neuroprosthetic applications to assist patients suffering from brain injury or neurodegenerative disease. One type of brain–machine interface is a cortical motor prosthetic, which is used to assist paralyzed subjects. Motor prosthetics to date have typically used the motor cortex as a source of neural signals for controlling external devices. The review will focus on several new topics in the arena of cortical prosthetics. T...

  16. Examining the electro-neural interface of cochlear implant users using psychophysics, CT scans, and speech understanding.

    Science.gov (United States)

    Long, Christopher J; Holden, Timothy A; McClelland, Gary H; Parkinson, Wendy S; Shelton, Clough; Kelsall, David C; Smith, Zachary M

    2014-04-01

    This study examines the relationship between focused-stimulation thresholds, electrode positions, and speech understanding in deaf subjects treated with a cochlear implant (CI). Focused stimulation is more selective than monopolar stimulation, which excites broad regions of the cochlea, so may be more sensitive as a probe of neural survival patterns. Focused thresholds are on average higher and more variable across electrodes than monopolar thresholds. We presume that relatively high focused thresholds are the result of larger distances between the electrodes and the neurons. Two factors are likely to contribute to this distance: (1) the physical position of electrodes relative to the modiolus, where the excitable auditory neurons are normally located, and (2) the pattern of neural survival along the length of the cochlea, since local holes in the neural population will increase the distance between an electrode and the nearest neurons. Electrode-to-modiolus distance was measured from high-resolution CT scans of the cochleae of CI users whose focused-stimulation thresholds were also measured. A hierarchical set of linear models of electrode-to-modiolus distance versus threshold showed a significant increase in threshold with electrode-to-modiolus distance (average slope = 11 dB/mm). The residual of these models was hypothesized to reflect neural survival in each subject. Consonant-Nucleus-Consonant (CNC) word scores were significantly correlated with the within-subject variance of threshold (r(2) = 0.82), but not with within-subject variance of electrode distance (r(2) = 0.03). Speech understanding also significantly correlated with how well distance explained each subject's threshold data (r(2) = 0.63). That is, subjects with focused thresholds that were well described by electrode position had better speech scores. Our results suggest that speech understanding is highly impacted by individual patterns of neural survival and that these patterns manifest themselves

  17. Conductive nanogel-interfaced neural microelectrode arrays with electrically controlled in-situ delivery of manganese ions enabling high-resolution MEMRI for synchronous neural tracing with deep brain stimulation.

    Science.gov (United States)

    Huang, Wei-Chen; Lo, Yu-Chih; Chu, Chao-Yi; Lai, Hsin-Yi; Chen, You-Yin; Chen, San-Yuan

    2017-04-01

    Chronic brain stimulation has become a promising physical therapy with increased efficacy and efficiency in the treatment of neurodegenerative diseases. The application of deep brain electrical stimulation (DBS) combined with manganese-enhanced magnetic resonance imaging (MEMRI) provides an unbiased representation of the functional anatomy, which shows the communication between areas of the brain responding to the therapy. However, it is challenging for the current system to provide a real-time high-resolution image because the incorporated MnCl2 solution through microinjection usually results in image blurring or toxicity due to the uncontrollable diffusion of Mn2+. In this study, we developed a new type of conductive nanogel-based neural interface composed of amphiphilic chitosan-modified poly(3,4 -ethylenedioxythiophene) (PMSDT) that can exhibit biomimic structural/mechanical properties and ionic/electrical conductivity comparable to that of Au. More importantly, the PMSDT enables metal-ligand bonding with Mn2+ ions, so that the system can release Mn2+ ions rather than MnCl2 solution directly and precisely controlled by electrical stimulation (ES) to achieve real-time high-resolution MEMRI. With the integration of PMSDT nanogel-based coating in polyimide-based microelectrode arrays, the post-implantation DBS enables frequency-dependent MR imaging in vivo, as well as small focal imaging in response to channel site-specific stimulation on the implant. The MR imaging of the implanted brain treated with 5-min electrical stimulation showed a thalamocortical neuronal pathway after 36 h, confirming the effective activation of a downstream neuronal circuit following DBS. By eliminating the susceptibility to artifact and toxicity, this system, in combination with a MR-compatible implant and a bio-compliant neural interface, provides a harmless and synchronic functional anatomy for DBS. The study demonstrates a model of MEMRI-functionalized DBS based on functional

  18. Desien, ConstruThe design, fabrication and evaluation of egg weighing device using capacitive sensor and neural networksction and Evaluation of Egg Weighing Device Using Capacitive Sensor and Neural Networks

    Directory of Open Access Journals (Sweden)

    S Khalili

    2015-09-01

    Full Text Available Introduction: Grading agricultural products always has a particular important position for submission to domestic and overseas markets. The grading causes more profitable product ranges and customer satisfaction. Grading treatment is carried out based on various parameters such as color, ripeness level, dimensions and weight. Product weight is one of the most effective parameters in grading operation. Egg weight is directly related to the smallness and coarseness of eggs. In egg grading, the largeness value is very important in marketing. This research aimed to design, fabricate and evaluate the egg weighing system based on its dielectric properties. Materials and Methods: To perform this research, the stages of work are divided into several sections including, design and construction of the hardware section, writing code for the software section to collect data, conducting nondestructive tests and data collection, analysis of obtained data using artificial intelligence, and giving the results of analysis for device calibration of the system as the software code. The large eggs as dielectric substances cause more increase in the capacity of the capacitive sensor. Furthermore, by derivation of a relation between capacity of capacitive sensor and egg weight, one can predict the weight of the sample. A prototype unit of weighing system was designed and fabricated. The designed unit was composed of a chassis, a voltage source, a sinusoidal signal generator, a voltage measurement unit, an AVR micro controller, a COM port, a capacitive sensor, and an LCD and a keyboard. Neural network technique was used for egg weight prediction. The designed net receives 16 voltage values at different frequencies as inputs and its output is the egg weight. In order to calibrate and evaluate the weighing unit, 150 fresh egg samples were provided on egg laying day from a local poultry farm. Experiments were divided into three groups. The experiments were carried out on

  19. Real-time ocular artifact suppression using recurrent neural network for electro-encephalogram based brain-computer interface.

    Science.gov (United States)

    Erfanian, A; Mahmoudi, B

    2005-03-01

    The paper presents an adaptive noise canceller (ANC) filter using an artificial neural network for real-time removal of electro-oculogram (EOG) interference from electro-encephalogram (EEG) signals. Conventional ANC filters are based on linear models of interference. Such linear models provide poorer prediction for biomedical signals. In this work, a recurrent neural network was employed for modelling the interference signals. The eye movement and eye blink artifacts were recorded by the placing of an electrode on the forehead above the left eye and an electrode on the left temple. The reference signal was then generated by the data collected from the forehead electrode being added to data recorded from the temple electrode. The reference signal was also contaminated by the EEG. To reduce the EEG interference, the reference signal was first low-pass filtered by a moving averaged filter and then applied to the ANC. Matlab Simulink was used for real-time data acquisition, filtering and ocular artifact suppression. Simulation results show the validity and effectiveness of the technique with different signal-to-noise ratios (SNRs) of the primary signal. On average, a significant improvement in SNR up to 27 dB was achieved with the recurrent neural network. The results from real data demonstrate that the proposed scheme removes ocular artifacts from contaminated EEG signals and is suitable for real-time and short-time EEG recordings.

  20. What do spinal cord injury consumers want? A review of spinal cord injury consumer priorities and neuroprosthesis from the 2008 neural interfaces conference.

    Science.gov (United States)

    French, Jennifer S; Anderson-Erisman, Kim D; Sutter, Maria

    2010-07-01

      To summarize research to understand the priorities of consumers with spinal cord injury (SCI) as related to neuroprosthesis.   This review is generated from results presented during a session at the 2008 Neural Interfaces Conference held in Cleveland, OH including presentations of research, observation of a panel discussion, and a case study.   Understanding priorities of consumers living with SCI may help guide development of technology to potentially increase quality of life, confidence, and independence. Those living with quadriplegia desire arm and hand function while persons with paraplegia wish to regain sexual function. Shared priorities in the SCI population are the restoration of bladder and bowel function and the importance of exercise for functional recovery.   Understanding the consumer is the cornerstone to successful delivery of a neuroprosthesis. Translational research by multidisciplinary teams is needed to understand these issues and move technology for people living with SCI from the bench to the bedside. © 2010 International Neuromodulation Society.

  1. Convolutional neural network architecture and input volume matrix design for ERP classifications in a tactile P300-based Brain-Computer Interface.

    Science.gov (United States)

    Kodama, Takumi; Makino, Shoji

    2017-07-01

    In the presented study we conduct the off-line ERP classification using the convolutional neural network (CNN) classifier for somatosensory ERP intervals acquired in the full- body tactile P300-based Brain-Computer Interface paradigm (fbBCI). The main objective of the study is to enhance fbBCI stimulus pattern classification accuracies by applying the CNN classifier. A 60 × 60 squared input volume transformed by one-dimensional somatosensory ERP intervals in each electrode channel is input to the convolutional architecture for a filter training. The flattened activation maps are evaluated by a multilayer perceptron with one-hidden-layer in order to calculate classification accuracy results. The proposed method reveals that the CNN classifier model can achieve a non-personal- training ERP classification with the fbBCI paradigm, scoring 100 % classification accuracy results for all the participated ten users.

  2. Neural prostheses in clinical practice: biomedical microsystems in neurological rehabilitation.

    Science.gov (United States)

    Stieglitz, T

    2007-01-01

    Technical devices have supported physicians in diagnosis, therapy, and rehabilitation since ancient times. Neural prostheses interface parts of the nervous system with technical (micro-) systems to partially restore sensory and motor functions that have been lost due to trauma or diseases. Electrodes act as transducers to record neural signals or to excite neural cells by means of electrical stimulation. The field of neural prostheses has grown over the last decades. An overview of neural prostheses illustrates the opportunities and limitations of the implants and performance in their current size and complexity. The implementation of microsystem technology with integrated microelectronics in neural implants 20 years ago opened new fields of application, but also new design paradigms and approaches with respect to the biostability of passivation and housing concepts and electrode interfaces. Microsystem specific applications in the peripheral nervous system, vision prostheses and brain-machine interfaces show the variety of applications and the challenges in biomedical microsystems for chronic nerve interfaces in new and emerging research fields that bridge neuroscientific disciplines with material science and engineering. Different scenarios are discussed where system complexity strongly depends on the rehabilitation objective and the amount of information that is necessary for the chosen neuro-technical interface.

  3. Brain-Machine Interface Control Algorithms.

    Science.gov (United States)

    Shanechi, Maryam M

    2016-12-14

    Motor brain-machine interfaces (BMI) allow subjects to control external devices by modulating their neural activity. BMIs record the neural activity, use a mathematical algorithm to estimate the subject's intended movement, actuate an external device, and provide visual feedback of the generated movement to the subject. A critical component of a BMI system is the control algorithm, termed decoder. Significant progress has been made in the design of BMI decoders in recent years resulting in proficient control in non-human primates and humans. In this review article, we discuss the decoding algorithms developed in the BMI field, with particular focus on recent designs that are informed by closed-loop control ideas. A motor BMI can be modeled as a closed-loop control system, where the controller is the brain, the plant is the prosthetic, the feedback is the biofeedback, and the control command is the neural activity. Additionally, compared to other closed-loop systems, BMIs have various unique properties. Neural activity is noisy and stochastic, and often consists of a sequence of spike trains. Neural representations of movement could be non-stationary and change over time, for example as a result of learning. We review recent decoder designs that take these unique properties into account. We also discuss the opportunities that exist at the interface of control theory, statistical inference, and neuroscience to devise a control-theoretic framework for BMI design and help develop the next-generation BMI control algorithms.

  4. A comparative study: use of a Brain-computer Interface (BCI) device by people with cerebral palsy in interaction with computers

    OpenAIRE

    Heidrich, Regina O.; Emely Jensen; Francisco Rebelo; Tiago Oliveira

    2015-01-01

    ABSTRACT This article presents a comparative study among people with cerebral palsy and healthy controls, of various ages, using a Brain-computer Interface (BCI) device. The research is qualitative in its approach. Researchers worked with Observational Case Studies. People with cerebral palsy and healthy controls were evaluated in Portugal and in Brazil. The study aimed to develop a study for product evaluation in order to perceive whether people with cerebral palsy could interact with the co...

  5. NeuroMEMS: Neural Probe Microtechnologies

    Directory of Open Access Journals (Sweden)

    Sam Musallam

    2008-10-01

    Full Text Available Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer’s, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultralong multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

  6. Neural recording and modulation technologies

    Science.gov (United States)

    Chen, Ritchie; Canales, Andres; Anikeeva, Polina

    2017-01-01

    In the mammalian nervous system, billions of neurons connected by quadrillions of synapses exchange electrical, chemical and mechanical signals. Disruptions to this network manifest as neurological or psychiatric conditions. Despite decades of neuroscience research, our ability to treat or even to understand these conditions is limited by the capability of tools to probe the signalling complexity of the nervous system. Although orders of magnitude smaller and computationally faster than neurons, conventional substrate-bound electronics do not recapitulate the chemical and mechanical properties of neural tissue. This mismatch results in a foreign-body response and the encapsulation of devices by glial scars, suggesting that the design of an interface between the nervous system and a synthetic sensor requires additional materials innovation. Advances in genetic tools for manipulating neural activity have fuelled the demand for devices that are capable of simultaneously recording and controlling individual neurons at unprecedented scales. Recently, flexible organic electronics and bio- and nanomaterials have been developed for multifunctional and minimally invasive probes for long-term interaction with the nervous system. In this Review, we discuss the design lessons from the quarter-century-old field of neural engineering, highlight recent materials-driven progress in neural probes and look at emergent directions inspired by the principles of neural transduction.

  7. Cu(In,Ga)Se{sub 2} absorber thinning and the homo-interface model: Influence of Mo back contact and 3-stage process on device characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Leonard, E.; Arzel, L.; Tomassini, M.; Barreau, N., E-mail: nicolas.barreau@univ-nantes.fr [Institut des Matériaux Jean Rouxel (IMN)-UMR 6502, Université de Nantes, CNRS, 2 rue de la Houssinière, BP 32229, 44322 Nantes Cedex 3 (France); Zabierowski, P. [Faculty of Physics, Warsaw University of Technology, Koszykowa 75, PL 00-662 Warsaw (Poland); Fuertes Marrón, D. [Instituto de Energía Solar–ETSIT, Technical University of Madrid, Ciudad Universitaria s.n., 28040 Madrid (Spain)

    2014-08-21

    Thinning the absorber layer is one of the possibilities envisaged to further decrease the production costs of Cu(In,Ga)Se{sub 2} (CIGSe) thin films solar cell technology. In the present study, the electronic transport in submicron CIGSe-based devices has been investigated and compared to that of standard devices. It is observed that when the absorber is around 0.5 μm-thick, tunnelling enhanced interface recombination dominates, which harms cells energy conversion efficiency. It is also shown that by varying either the properties of the Mo back contact or the characteristics of 3-stage growth processing, one can shift the dominating recombination mechanism from interface to space charge region and thereby improve the cells efficiency. Discussions on these experimental facts led to the conclusions that 3-stage process implies the formation of a CIGSe/CIGSe homo-interface, whose location as well as properties rule the device operation; its influence is enhanced in submicron CIGSe based solar cells.

  8. Recent advances in neural recording microsystems.

    Science.gov (United States)

    Gosselin, Benoit

    2011-01-01

    The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

  9. Recent Advances in Neural Recording Microsystems

    Directory of Open Access Journals (Sweden)

    Benoit Gosselin

    2011-04-01

    Full Text Available The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

  10. Changes in functional connectivity correlate with behavioral gains in stroke patients after therapy using a brain-computer interface device

    Directory of Open Access Journals (Sweden)

    Brittany Mei Young

    2014-07-01

    Full Text Available Brain-computer interface (BCI technology is being incorporated into new stroke rehabilitation devices, but little is known about brain changes associated with its use. We collected anatomical and functional MRI of 9 stroke patients with persistent upper extremity motor impairment before, during, and after therapy using a BCI system. Subjects were asked to perform finger tapping of the impaired hand during fMRI. Action Research Arm Test (ARAT, 9-Hole Peg Test (9-HPT, and Stroke Impact Scale (SIS domains of Hand Function (HF and Activities of Daily Living (ADL were also assessed. Group-level analyses examined changes in whole-brain task-based functional connectivity (FC to seed regions in the motor network observed during and after BCI therapy. Whole-brain FC analyses seeded in each thalamus showed FC increases from baseline at mid-therapy and post-therapy (p< 0.05. Changes in FC between seeds at both the network and the connection levels were examined for correlations with changes in behavioral measures. Average motor network FC was increased post-therapy, and changes in average network FC correlated (p < 0.05 with changes in performance on ARAT (R2=0.21, 9-HPT (R2=0.41, SIS HF (R2=0.27, and SIS ADL (R2=0.40. Multiple individual connections within the motor network were found to correlate in change from baseline with changes in behavioral measures. Many of these connections involved the thalamus, with change in each of four behavioral measures significantly correlating with change from baseline FC of at least one thalamic connection. These preliminary results show changes in FC that occur with the administration of rehabilitative therapy using a BCI system. The correlations noted between changes in FC measures and changes in behavioral outcomes indicate that both adaptive and maladaptive changes in FC may develop with this therapy and also suggest a brain-behavior relationship that may be stimulated by the neuromodulatory component of BCI therapy.

  11. Graphene-Based Interfaces Do Not Alter Target Nerve Cells.

    Science.gov (United States)

    Fabbro, Alessandra; Scaini, Denis; León, Verónica; Vázquez, Ester; Cellot, Giada; Privitera, Giulia; Lombardi, Lucia; Torrisi, Felice; Tomarchio, Flavia; Bonaccorso, Francesco; Bosi, Susanna; Ferrari, Andrea C; Ballerini, Laura; Prato, Maurizio

    2016-01-26

    Neural-interfaces rely on the ability of electrodes to transduce stimuli into electrical patterns delivered to the brain. In addition to sensitivity to the stimuli, stability in the operating conditions and efficient charge transfer to neurons, the electrodes should not alter the physiological properties of the target tissue. Graphene is emerging as a promising material for neuro-interfacing applications, given its outstanding physico-chemical properties. Here, we use graphene-based substrates (GBSs) to interface neuronal growth. We test our GBSs on brain cell cultures by measuring functional and synaptic integrity of the emerging neuronal networks. We show that GBSs are permissive interfaces, even when uncoated by cell adhesion layers, retaining unaltered neuronal signaling properties, thus being suitable for carbon-based neural prosthetic devices.

  12. Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors

    Science.gov (United States)

    2012-01-01

    A brain-computer interface (BCI) is a communication system that can help users interact with the outside environment by translating brain signals into machine commands. The use of electroencephalographic (EEG) signals has become the most common approach for a BCI because of their usability and strong reliability. Many EEG-based BCI devices have been developed with traditional wet- or micro-electro-mechanical-system (MEMS)-type EEG sensors. However, those traditional sensors have uncomfortable disadvantage and require conductive gel and skin preparation on the part of the user. Therefore, acquiring the EEG signals in a comfortable and convenient manner is an important factor that should be incorporated into a novel BCI device. In the present study, a wearable, wireless and portable EEG-based BCI device with dry foam-based EEG sensors was developed and was demonstrated using a gaming control application. The dry EEG sensors operated without conductive gel; however, they were able to provide good conductivity and were able to acquire EEG signals effectively by adapting to irregular skin surfaces and by maintaining proper skin-sensor impedance on the forehead site. We have also demonstrated a real-time cognitive stage detection application of gaming control using the proposed portable device. The results of the present study indicate that using this portable EEG-based BCI device to conveniently and effectively control the outside world provides an approach for researching rehabilitation engineering. PMID:22284235

  13. Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors.

    Science.gov (United States)

    Liao, Lun-De; Chen, Chi-Yu; Wang, I-Jan; Chen, Sheng-Fu; Li, Shih-Yu; Chen, Bo-Wei; Chang, Jyh-Yeong; Lin, Chin-Teng

    2012-01-28

    A brain-computer interface (BCI) is a communication system that can help users interact with the outside environment by translating brain signals into machine commands. The use of electroencephalographic (EEG) signals has become the most common approach for a BCI because of their usability and strong reliability. Many EEG-based BCI devices have been developed with traditional wet- or micro-electro-mechanical-system (MEMS)-type EEG sensors. However, those traditional sensors have uncomfortable disadvantage and require conductive gel and skin preparation on the part of the user. Therefore, acquiring the EEG signals in a comfortable and convenient manner is an important factor that should be incorporated into a novel BCI device. In the present study, a wearable, wireless and portable EEG-based BCI device with dry foam-based EEG sensors was developed and was demonstrated using a gaming control application. The dry EEG sensors operated without conductive gel; however, they were able to provide good conductivity and were able to acquire EEG signals effectively by adapting to irregular skin surfaces and by maintaining proper skin-sensor impedance on the forehead site. We have also demonstrated a real-time cognitive stage detection application of gaming control using the proposed portable device. The results of the present study indicate that using this portable EEG-based BCI device to conveniently and effectively control the outside world provides an approach for researching rehabilitation engineering.

  14. Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors

    Directory of Open Access Journals (Sweden)

    Liao Lun-De

    2012-01-01

    Full Text Available Abstract A brain-computer interface (BCI is a communication system that can help users interact with the outside environment by translating brain signals into machine commands. The use of electroencephalographic (EEG signals has become the most common approach for a BCI because of their usability and strong reliability. Many EEG-based BCI devices have been developed with traditional wet- or micro-electro-mechanical-system (MEMS-type EEG sensors. However, those traditional sensors have uncomfortable disadvantage and require conductive gel and skin preparation on the part of the user. Therefore, acquiring the EEG signals in a comfortable and convenient manner is an important factor that should be incorporated into a novel BCI device. In the present study, a wearable, wireless and portable EEG-based BCI device with dry foam-based EEG sensors was developed and was demonstrated using a gaming control application. The dry EEG sensors operated without conductive gel; however, they were able to provide good conductivity and were able to acquire EEG signals effectively by adapting to irregular skin surfaces and by maintaining proper skin-sensor impedance on the forehead site. We have also demonstrated a real-time cognitive stage detection application of gaming control using the proposed portable device. The results of the present study indicate that using this portable EEG-based BCI device to conveniently and effectively control the outside world provides an approach for researching rehabilitation engineering.

  15. A comparative study: use of a Brain-computer Interface (BCI) device by people with cerebral palsy in interaction with computers.

    Science.gov (United States)

    Heidrich, Regina O; Jensen, Emely; Rebelo, Francisco; Oliveira, Tiago

    2015-01-01

    This article presents a comparative study among people with cerebral palsy and healthy controls, of various ages, using a Brain-computer Interface (BCI) device. The research is qualitative in its approach. Researchers worked with Observational Case Studies. People with cerebral palsy and healthy controls were evaluated in Portugal and in Brazil. The study aimed to develop a study for product evaluation in order to perceive whether people with cerebral palsy could interact with the computer and compare whether their performance is similar to that of healthy controls when using the Brain-computer Interface. Ultimately, it was found that there are no significant differences between people with cerebral palsy in the two countries, as well as between populations without cerebral palsy (healthy controls).

  16. A comparative study: use of a Brain-computer Interface (BCI device by people with cerebral palsy in interaction with computers

    Directory of Open Access Journals (Sweden)

    Regina O. Heidrich

    2015-12-01

    Full Text Available ABSTRACT This article presents a comparative study among people with cerebral palsy and healthy controls, of various ages, using a Brain-computer Interface (BCI device. The research is qualitative in its approach. Researchers worked with Observational Case Studies. People with cerebral palsy and healthy controls were evaluated in Portugal and in Brazil. The study aimed to develop a study for product evaluation in order to perceive whether people with cerebral palsy could interact with the computer and compare whether their performance is similar to that of healthy controls when using the Brain-computer Interface. Ultimately, it was found that there are no significant differences between people with cerebral palsy in the two countries, as well as between populations without cerebral palsy (healthy controls.

  17. Device- and system-independent personal touchless user interface for operating rooms : One personal UI to control all displays in an operating room.

    Science.gov (United States)

    Ma, Meng; Fallavollita, Pascal; Habert, Séverine; Weidert, Simon; Navab, Nassir

    2016-06-01

    In the modern day operating room, the surgeon performs surgeries with the support of different medical systems that showcase patient information, physiological data, and medical images. It is generally accepted that numerous interactions must be performed by the surgical team to control the corresponding medical system to retrieve the desired information. Joysticks and physical keys are still present in the operating room due to the disadvantages of mouses, and surgeons often communicate instructions to the surgical team when requiring information from a specific medical system. In this paper, a novel user interface is developed that allows the surgeon to personally perform touchless interaction with the various medical systems, switch effortlessly among them, all of this without modifying the systems' software and hardware. To achieve this, a wearable RGB-D sensor is mounted on the surgeon's head for inside-out tracking of his/her finger with any of the medical systems' displays. Android devices with a special application are connected to the computers on which the medical systems are running, simulating a normal USB mouse and keyboard. When the surgeon performs interaction using pointing gestures, the desired cursor position in the targeted medical system display, and gestures, are transformed into general events and then sent to the corresponding Android device. Finally, the application running on the Android devices generates the corresponding mouse or keyboard events according to the targeted medical system. To simulate an operating room setting, our unique user interface was tested by seven medical participants who performed several interactions with the visualization of CT, MRI, and fluoroscopy images at varying distances from them. Results from the system usability scale and NASA-TLX workload index indicated a strong acceptance of our proposed user interface.

  18. Methods for studying medical device technology and practitioner cognition: the case of user-interface issues with infusion pumps

    NARCIS (Netherlands)

    Schraagen, Johannes Martinus Cornelis; Verhoeven, F.

    2013-01-01

    Purpose The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Methods Starting from a Cognitive

  19. Methods for studying medical device technology and practitioner cognition : The case of user-interface issues with infusion pumps

    NARCIS (Netherlands)

    Schraagen, J.M.C.; Verhoeven, F.

    2013-01-01

    Purpose : The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Methods : Starting from a

  20. Methods for studying medical device technology and practitioner cognition : the case of user-interface issues with infusion pumps

    NARCIS (Netherlands)

    Jan Maarten Schraagen; Fenne Verhoeven

    2013-01-01

    Purpose: The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Methods: Starting from a

  1. Current Constriction at Electrode/Electrolyte Interfaces in Solid Oxide Cell Electrochemical Devices Calculated Via 3D Reconstructions

    DEFF Research Database (Denmark)

    Nielsen, Jimmi; Jørgensen, Peter Stanley; Graves, Christopher R.

    2016-01-01

    Electrochemical devices such as batteries, fuel cells, electrolysers, electrochemical reactors and electrochemical sensors are important technologies for the present and the future society. For further improvement or maturing of the various technologies it is important to understand, characterize...

  2. Body-Machine Interface Enables People With Cervical Spinal Cord Injury to Control Devices With Available Body Movements: Proof of Concept.

    Science.gov (United States)

    Abdollahi, Farnaz; Farshchiansadegh, Ali; Pierella, Camilla; Seáñez-González, Ismael; Thorp, Elias; Lee, Mei-Hua; Ranganathan, Rajiv; Pedersen, Jessica; Chen, David; Roth, Elliot; Casadio, Maura; Mussa-Ivaldi, Ferdinando

    2017-05-01

    This study tested the use of a customized body-machine interface (BoMI) for enhancing functional capabilities in persons with cervical spinal cord injury (cSCI). The interface allows people with cSCI to operate external devices by reorganizing their residual movements. This was a proof-of-concept phase 0 interventional nonrandomized clinical trial. Eight cSCI participants wore a custom-made garment with motion sensors placed on the shoulders. Signals derived from the sensors controlled a computer cursor. A standard algorithm extracted the combinations of sensor signals that best captured each participant's capacity for controlling a computer cursor. Participants practiced with the BoMI for 24 sessions over 12 weeks performing 3 tasks: reaching, typing, and game playing. Learning and performance were evaluated by the evolution of movement time, errors, smoothness, and performance metrics specific to each task. Through practice, participants were able to reduce the movement time and the distance from the target at the 1-second mark in the reaching task. They also made straighter and smoother movements while reaching to different targets. All participants became faster in the typing task and more skilled in game playing, as the pong hit rate increased significantly with practice. The results provide proof-of-concept for the customized BoMI as a means for people with absent or severely impaired hand movements to control assistive devices that otherwise would be manually operated.

  3. A novel device for head gesture measurement system in combination with eye-controlled human machine interface

    Science.gov (United States)

    Lin, Chern-Sheng; Ho, Chien-Wa; Chang, Kai-Chieh; Hung, San-Shan; Shei, Hung-Jung; Yeh, Mau-Shiun

    2006-06-01

    This study describes the design and combination of an eye-controlled and a head-controlled human-machine interface system. This system is a highly effective human-machine interface, detecting head movement by changing positions and numbers of light sources on the head. When the users utilize the head-mounted display to browse a computer screen, the system will catch the images of the user's eyes with CCD cameras, which can also measure the angle and position of the light sources. In the eye-tracking system, the program in the computer will locate each center point of the pupils in the images, and record the information on moving traces and pupil diameters. In the head gesture measurement system, the user wears a double-source eyeglass frame, so the system catches images of the user's head by using a CCD camera in front of the user. The computer program will locate the center point of the head, transferring it to the screen coordinates, and then the user can control the cursor by head motions. We combine the eye-controlled and head-controlled human-machine interface system for the virtual reality applications.

  4. Photovoltaic device

    Science.gov (United States)

    Reese, Jason A.; Keenihan, James R.; Gaston, Ryan S.; Kauffmann, Keith L.; Langmaid, Joseph A.; Lopez, Leonardo C.; Maak, Kevin D.; Mills, Michael E.; Ramesh, Narayan; Teli, Samar R.

    2015-09-01

    The present invention is premised upon an improved photovoltaic device ("PV device"), more particularly to an improved photovoltaic device (10) with a multilayered photovoltaic cell assembly (100) and a body portion (200) joined at an interface region (410) and including an intermediate layer (500), at least one interconnecting structural member (1500), relieving feature (2500), unique component geometry, or any combination thereof.

  5. Photovoltaic device

    Energy Technology Data Exchange (ETDEWEB)

    Reese, Jason A; Keenihan, James R; Gaston, Ryan S; Kauffmann, Keith L; Langmaid, Joseph A; Lopez, Leonardo; Maak, Kevin D; Mills, Michael E; Ramesh, Narayan; Teli, Samar R

    2017-03-21

    The present invention is premised upon an improved photovoltaic device ("PV device"), more particularly to an improved photovoltaic device with a multilayered photovoltaic cell assembly and a body portion joined at an interface region and including an intermediate layer, at least one interconnecting structural member, relieving feature, unique component geometry, or any combination thereof.

  6. Bonding effectiveness of composite-dentin interfaces after mechanical loading with a new device (Rub&Roll)

    NARCIS (Netherlands)

    Montagner, A.F.; Opdam, N.J.M.; Ruben, J.L.; Cenci, M.S.; Huysmans, M.C.D.N.J.M.

    2016-01-01

    This study evaluated the effect of mechanical loading with a new device on the microtensile bond strength (microTBS) of adhesive systems to dentin. Forty molars were divided according to adhesive systems: self-etch (ClearfilTM SE Bond -CSE) and etch-and-rinse (Adper ScotchbondTM 1XT -ASB); and to

  7. The PennBMBI: Design of a General Purpose Wireless Brain-Machine-Brain Interface System.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Subei, Basheer; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

    2015-04-01

    In this paper, a general purpose wireless Brain-Machine-Brain Interface (BMBI) system is presented. The system integrates four battery-powered wireless devices for the implementation of a closed-loop sensorimotor neural interface, including a neural signal analyzer, a neural stimulator, a body-area sensor node and a graphic user interface implemented on the PC end. The neural signal analyzer features a four channel analog front-end with configurable bandpass filter, gain stage, digitization resolution, and sampling rate. The target frequency band is configurable from EEG to single unit activity. A noise floor of 4.69 μVrms is achieved over a bandwidth from 0.05 Hz to 6 kHz. Digital filtering, neural feature extraction, spike detection, sensing-stimulating modulation, and compressed sensing measurement are realized in a central processing unit integrated in the analyzer. A flash memory card is also integrated in the analyzer. A 2-channel neural stimulator with a compliance voltage up to ± 12 V is included. The stimulator is capable of delivering unipolar or bipolar, charge-balanced current pulses with programmable pulse shape, amplitude, width, pulse train frequency and latency. A multi-functional sensor node, including an accelerometer, a temperature sensor, a flexiforce sensor and a general sensor extension port has been designed. A computer interface is designed to monitor, control and configure all aforementioned devices via a wireless link, according to a custom designed communication protocol. Wireless closed-loop operation between the sensory devices, neural stimulator, and neural signal analyzer can be configured. The proposed system was designed to link two sites in the brain, bridging the brain and external hardware, as well as creating new sensory and motor pathways for clinical practice. Bench test and in vivo experiments are performed to verify the functions and performances of the system.

  8. Highly Improved Efficiency of Deep-Blue Fluorescent Polymer Light-Emitting Device Based on a Novel Hole Interface Modifier with 1,3,5-Triazine Core.

    Science.gov (United States)

    Xia, Lianpeng; Xue, Yuyuan; Xiong, Kang; Cai, Chaosheng; Peng, Zuosheng; Wu, Ying; Li, Yuan; Miao, Jingsheng; Chen, Dongcheng; Hu, Zhanhao; Wang, Jianbin; Peng, Xiaobin; Mo, Yueqi; Hou, Lintao

    2015-12-09

    We present an investigation of deep-blue fluorescent polymer light-emitting diodes (PLEDs) with a novel functional 1,3,5-triazine core material (HQTZ) sandwiched between poly(3,4-ethylene dioxythiophene):poly(styrene sulfonic acid) layer and poly(vinylcarbazole) layer as a hole injection layer (HIL) without interface intermixing. Ultraviolet photoemission spectroscopy and Kelvin probe measurements were carried out to determine the change of anode work function influenced by the HQTZ modifier. The thin HQTZ layer can efficiently maximize the charge injection from anode to blue emitter and simultaneously enhance the hole mobility of HILs. The deep-blue device performance is remarkably improved with the maximum luminous efficiency of 4.50 cd/A enhanced by 80% and the maximum quantum efficiency of 4.93%, which is 1.8-fold higher than that of the conventional device without HQTZ layer, including a lower turn-on voltage of 3.7 V and comparable Commission Internationale de L'Eclairage coordinates of (0.16, 0.09). It is the highest efficiency ever reported to date for solution-processed deep-blue PLEDs based on the device structure of ITO/HILs/poly(9,9-dialkoxyphenyl-2,7-silafluorene)/CsF/AL. The results indicate that HQTZ based on 1,3,5-triazine core can be a promising candidate of interfacial materials for deep-blue fluorescent PLEDs.

  9. Developing a Graphical User Interface to Automate the Estimation and Prediction of Risk Values for Flood Protective Structures using Artificial Neural Network

    Science.gov (United States)

    Hasan, M.; Helal, A.; Gabr, M.

    2014-12-01

    In this project, we focus on providing a computer-automated platform for a better assessment of the potential failures and retrofit measures of flood-protecting earth structures, e.g., dams and levees. Such structures play an important role during extreme flooding events as well as during normal operating conditions. Furthermore, they are part of other civil infrastructures such as water storage and hydropower generation. Hence, there is a clear need for accurate evaluation of stability and functionality levels during their service lifetime so that the rehabilitation and maintenance costs are effectively guided. Among condition assessment approaches based on the factor of safety, the limit states (LS) approach utilizes numerical modeling to quantify the probability of potential failures. The parameters for LS numerical modeling include i) geometry and side slopes of the embankment, ii) loading conditions in terms of rate of rising and duration of high water levels in the reservoir, and iii) cycles of rising and falling water levels simulating the effect of consecutive storms throughout the service life of the structure. Sample data regarding the correlations of these parameters are available through previous research studies. We have unified these criteria and extended the risk assessment in term of loss of life through the implementation of a graphical user interface to automate input parameters that divides data into training and testing sets, and then feeds them into Artificial Neural Network (ANN) tool through MATLAB programming. The ANN modeling allows us to predict risk values of flood protective structures based on user feedback quickly and easily. In future, we expect to fine-tune the software by adding extensive data on variations of parameters.

  10. Sequences at the interface of the fifth immunoglobulin domain and first fibronectin type III repeat of the neural cell adhesion molecule are critical for its polysialylation.

    Science.gov (United States)

    Thompson, Matthew G; Foley, Deirdre A; Swartzentruber, Kristin G; Colley, Karen J

    2011-02-11

    Polysialic acid is an anti-adhesive glycan that modifies a select group of mammalian proteins. The primary substrate of the polysialyltransferases (polySTs) is the neural cell adhesion molecule (NCAM). Polysialic acid negatively regulates cell adhesion, is required for proper brain development, and is expressed in specific areas of the adult brain where it promotes on-going cell migration and synaptic plasticity. The first fibronectin type III repeat (FN1) of NCAM is required for polysialylation of the N-glycans on the adjacent immunoglobulin-like domain (Ig5), and acidic residues on the surface of FN1 play a role in polyST recognition. Recent work demonstrated that the FN1 domain from the unpolysialylated olfactory cell adhesion molecule (OCAM) was able to partially replace NCAM FN1 (Foley, D. A., Swartzentruber, K. G., Thompson, M. G., Mendiratta, S. S., and Colley, K. J. (2010) J. Biol. Chem. 285, 35056-35067). Here we demonstrate that individually replacing three identical regions shared by NCAM and OCAM FN1, (500)PSSP(503) (PSSP), (526)GGVPI(530) (GGVPI), and (580)NGKG(583) (NGKG), dramatically reduces NCAM polysialylation. In addition, we show that the polyST, ST8SiaIV/PST, specifically binds NCAM and that this binding requires the FN1 domain. Replacing the FN1 PSSP sequences and the acidic patch residues decreases NCAM-polyST binding, whereas replacing the GGVPI and NGKG sequences has no effect. The location of GGVPI and NGKG in loops that flank the Ig5-FN1 linker and the proximity of PSSP to this linker suggest that GGVPI and NGKG sequences may be critical for stabilizing the Ig5-FN1 linker, whereas PSSP may play a dual role maintaining the Ig5-FN1 interface and a polyST recognition site.

  11. Sequences at the Interface of the Fifth Immunoglobulin Domain and First Fibronectin Type III Repeat of the Neural Cell Adhesion Molecule Are Critical for Its Polysialylation*

    Science.gov (United States)

    Thompson, Matthew G.; Foley, Deirdre A.; Swartzentruber, Kristin G.; Colley, Karen J.

    2011-01-01

    Polysialic acid is an anti-adhesive glycan that modifies a select group of mammalian proteins. The primary substrate of the polysialyltransferases (polySTs) is the neural cell adhesion molecule (NCAM). Polysialic acid negatively regulates cell adhesion, is required for proper brain development, and is expressed in specific areas of the adult brain where it promotes on-going cell migration and synaptic plasticity. The first fibronectin type III repeat (FN1) of NCAM is required for polysialylation of the N-glycans on the adjacent immunoglobulin-like domain (Ig5), and acidic residues on the surface of FN1 play a role in polyST recognition. Recent work demonstrated that the FN1 domain from the unpolysialylated olfactory cell adhesion molecule (OCAM) was able to partially replace NCAM FN1 (Foley, D. A., Swartzentruber, K. G., Thompson, M. G., Mendiratta, S. S., and Colley, K. J. (2010) J. Biol. Chem. 285, 35056–35067). Here we demonstrate that individually replacing three identical regions shared by NCAM and OCAM FN1, 500PSSP503 (PSSP), 526GGVPI530 (GGVPI), and 580NGKG583 (NGKG), dramatically reduces NCAM polysialylation. In addition, we show that the polyST, ST8SiaIV/PST, specifically binds NCAM and that this binding requires the FN1 domain. Replacing the FN1 PSSP sequences and the acidic patch residues decreases NCAM-polyST binding, whereas replacing the GGVPI and NGKG sequences has no effect. The location of GGVPI and NGKG in loops that flank the Ig5-FN1 linker and the proximity of PSSP to this linker suggest that GGVPI and NGKG sequences may be critical for stabilizing the Ig5-FN1 linker, whereas PSSP may play a dual role maintaining the Ig5-FN1 interface and a polyST recognition site. PMID:21131353

  12. Biomechatronics in medical rehabilitation biomodelling, interface, and control

    CERN Document Server

    Xie, Shane (S Q )

    2017-01-01

    This book focuses on the key technologies in developing biomechatronic systems for medical rehabilitation purposes. It includes a detailed analysis of biosignal processing, biomechanics modelling, neural and muscular interfaces, artificial actuators, robot-assisted training, clinical setup/implementation and rehabilitation robot control. Encompassing highly multidisciplinary themes in the engineering and medical fields, it presents researchers’ insights into the emerging technologies and developments that are being utilized in biomechatronics for medical purposes. Presenting a detailed analysis of five key areas in rehabilitation robotics: (i) biosignal processing; (ii) biomechanics modelling; (iii) neural and muscular interfaces; (iv) artificial actuators and devices; and (v) the use of neurological and muscular interfaces in rehabilitation robots control, the book describes the design of biomechatronic systems, the methods and control systems used and the implementation and testing in order to show how th...

  13. Increasing Trustworthiness of Face Authentication in Mobile Devices by Modeling Gesture Behavior and Location Using Neural Networks

    OpenAIRE

    Blerim Rexha; Gresa Shala; Valon Xhafa

    2018-01-01

    Personal mobile devices currently have access to a significant portion of their user’s private sensitive data and are increasingly used for processing mobile payments. Consequently, securing access to these mobile devices is a requirement for securing access to the sensitive data and potentially costly services. Face authentication is one of the promising biometrics-based user authentication mechanisms that has been widely available in this era of mobile computing. With a built-in camera capa...

  14. On the Structural and Chemical Characteristics of Co/Al2O3/graphene Interfaces for Graphene Spintronic Devices.

    Science.gov (United States)

    Canto, Bárbara; Gouvea, Cristol P; Archanjo, Bráulio S; Schmidt, João E; Baptista, Daniel L

    2015-09-23

    We report a detailed investigation of the structural and chemical characteristics of thin evaporated Al2O3 tunnel barriers of variable thickness grown onto single-layer graphene sheets. Advanced electron microscopy and spectrum-imaging techniques were used to investigate the Co/Al2O3/graphene/SiO2 interfaces. Direct observation of pinhole contacts was achieved using FIB cross-sectional lamellas. Spatially resolved EDX spectrum profiles confirmed the presence of direct point contacts between the Co layer and the graphene. The high surface diffusion properties of graphene led to cluster-like Al2O3 film growth, limiting the minimal possible thickness for complete barrier coverage onto graphene surfaces using standard Al evaporation methods. The results indicate a minimum thickness of nominally 3 nm Al2O3, resulting in a 0.6 nm rms rough film with a maximum thickness reaching 5 nm.

  15. Optimal interfacing with coupled-cavities slow-light waveguides: mimicking periodic structures with a compact device.

    Science.gov (United States)

    Scheuer, Jacob

    2017-07-10

    We present a design for optimal interfacing (I/O coupling) with slow-light structures consisting of coupled cavities. The I/O couplers are based on adding a small set of cavities with varying coupling coefficients at edges of the coupled cavities waveguide in order to match its impedance with that of the I/O waveguides. I/O efficiencies exceeding 99.9% are shown to be possible over a bandwidth which is larger than 50% of that of the coupled cavities waveguide. Consequently, the reflections at the edges of the slow-light structure are practically eliminated. We discuss the properties of the perfectly impedance matched slow-light structure as an effective (super-structure) cavity and study the impact of the number of cavities comprising the I/O coupler. We also consider in details the impact of errors and disorder in the I/O coupling sections.

  16. [Brain-machine interface (BMI) - application to neurological disorders].

    Science.gov (United States)

    Yoshimine, Toshiki; Yanagisawa, Takufumi; Hirata, Masayuki

    2013-01-01

    Brain-machine interface (BMI) is a new technology to receive input from the brain which is translated to operate a computer or other external device in real time. After significant progress during the recent 10 years, this technology is now very close to the clinical use to restore neural functions of patients with severe neurologic impairment. This technology is also a strong tool to investigate the mode of neuro-signal processing in the brain and to understand the mechanism of neural dysfunction which leads to the development of novel neurotechnology for the treatment of various sorts of neurological disorders.

  17. Effects of basal-plane thermal conductivity and interface thermal conductance on the hot spot temperature in graphene electronic devices

    Science.gov (United States)

    Choi, David; Poudel, Nirakar; Cronin, Stephen B.; Shi, Li

    2017-02-01

    Electrostatic force microscopy and scanning thermal microscopy are employed to investigate the electric transport and localized heating around defects introduced during transfer of graphene grown by chemical vapor deposition to an oxidized Si substrate. Numerical and analytical models are developed to explain the results based on the reported basal-plane thermal conductivity, κ, and interfacial thermal conductance, G, of graphene and to investigate their effects on the peak temperature. Irrespective of the κ values, increasing G beyond 4 × 107 W m-2 K-1 can reduce the peak temperature effectively for graphene devices made on sub-10 nm thick gate dielectric, but not for the measured device made on 300-nm-thick oxide dielectric, which yields a cross-plane thermal conductance (Gox) much smaller than the typical G of graphene. In contrast, for typical G values reported for graphene, increasing κ from 300 W m-1 K-1 toward 3000 W m-1 K-1 is effective in reducing the hot spot temperature for the 300-nm-thick oxide devices but not for the sub-10 nm gate dielectric case, because the heat spreading length (l) can be appreciably increased relative to the micron-scale localized heat generation spot size (r0) only when the oxide layer is sufficiently thick. As such, enhancement of κ increases the vertical heat transfer area above the gate dielectric only for the thick oxide case. In all cases considered, the hot spot temperature is sensitive to varying G and κ only when the G/Gox ratio and r0/l ratio are below about 5, respectively.

  18. TEMPO: a New Insertion Device Beamline at SOLEIL for Time Resolved Photoelectron Spectroscopy Experiments on Solids and Interfaces

    Science.gov (United States)

    Polack, F.; Silly, M.; Chauvet, C.; Lagarde, B.; Bergeard, N.; Izquierdo, M.; Chubar, O.; Krizmancic, D.; Ribbens, M.; Duval, J.-P.; Basset, C.; Kubsky, S.; Sirotti, F.

    2010-06-01

    A new insertion device beamline is now operational on straight section 8 at the SOLEIL synchrotron radiation source in France. The beamline and the experimental station were developed to optimize the study of the dynamics of electronic and magnetic properties of materials. Here we present the main technical characteristics of the installation and the general principles behind them. The source is composed of two APPLE II type insertion devices. The monochromator with plane gratings and spherical mirrors is working in the energy range 40-1500 eV. It is equipped with VLS, VGD gratings to allow the user optimization of flux or higher harmonics rejection. The observed resonance structures measured in gas phase enable us to determine the available energy resolution: a resolving power higher than 10000 is obtained at the Ar 2p, N 1s and Ne K-edges when using all the optical elements at full aperture. The total flux as a function of the measured photon energy and the characterization of the focal spot size complete the beamline characterization.

  19. Highly Simplified Tandem Organic Light-Emitting Devices Incorporating a Green Phosphorescence Ultrathin Emitter within a Novel Interface Exciplex for High Efficiency.

    Science.gov (United States)

    Xu, Ting; Zhou, Jun-Gui; Huang, Chen-Chao; Zhang, Lei; Fung, Man-Keung; Murtaza, Imran; Meng, Hong; Liao, Liang-Sheng

    2017-03-29

    Herein we report a novel design philosophy of tandem OLEDs incorporating a doping-free green phosphorescent bis[2-(2-pyridinyl-N)phenyl-C](acetylacetonato)iridium(III) (Ir(ppy)2(acac)) as an ultrathin emissive layer (UEML) into a novel interface-exciplex-forming structure of 1,1-bis[(di-4-tolylamino)phenyl]cyclohexane (TAPC) and 1,3,5-tri(p-pyrid-3-yl-phenyl)benzene (TmPyPB). Particularly, relatively low working voltage and remarkable efficiency are achieved and the designed tandem OLEDs exhibit a peak current efficiency of 135.74 cd/A (EQE = 36.85%) which is two times higher than 66.2 cd/A (EQE = 17.97%) of the device with a single emitter unit. This might be one of the highest efficiencies of OLEDs applying ultrathin emitters without light extraction. Moreover, with the proposed structure, the color gamut of the displays can be effectively increased from 76% to 82% NTSC if the same red and blue emissions as those in the NTSC are applied. A novel form of harmonious fusion among interface exciplex, UEML, and tandem structure is successfully realized, which sheds light on further development of ideal OLED structure with high efficiency, simplified fabrication, low power consumption, low cost, and improved color gamut, simultaneously.

  20. Impact of after-treatment devices and biofuels on diesel exhausts genotoxicity in A549 cells exposed at air-liquid interface.

    Science.gov (United States)

    Barraud, C; Corbière, C; Pottier, I; Estace, E; Blanchard, K; Logie, C; Lagadu, S; Kéravec, V; Pottier, D; Dionnet, F; Morin, J P; Préterre, D; André, V; Monteil, C; Sichel, F

    2017-12-01

    Using an air-liquid interface (ALI) device in dynamic conditions, we evaluated the efficiency of fuel after-treatment strategies (diesel oxidation catalysis, DOC, and diesel particulate filter, DPF, devices) and the impact of 7% and 30% rapeseed methyl esters (RME) blending on oxidative stress and genotoxicity induced in A549 lung cells after 3h exposure to whole Diesel exhausts. Oxidative stress was studied using assays of ROS production, glutathione level, catalase and superoxide-dismutase (SOD) activities. No oxidative stress and no clear differences on cytotoxicity patterns between biodiesel and standard Diesel exhausts were found. A weak but significant genotoxicity (8-oxodGuo adducts) and, for standard Diesel only, a DNA damage response (DDR) as evidenced by ƔH2AX foci, remained after DOC+DPF flowing. All together, these data could contribute to the improvement of the after treatment strategies and to health risk assessment of current diesel exhausts. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. The LEAP™ Gesture Interface Device and Take-Home Laparoscopic Simulators: A Study of Construct and Concurrent Validity.

    Science.gov (United States)

    Partridge, Roland W; Brown, Fraser S; Brennan, Paul M; Hennessey, Iain A M; Hughes, Mark A

    2016-02-01

    To assess the potential of the LEAP™ infrared motion tracking device to map laparoscopic instrument movement in a simulated environment. Simulator training is optimized when augmented by objective performance feedback. We explore the potential LEAP has to provide this in a way compatible with affordable take-home simulators. LEAP and the previously validated InsTrac visual tracking tool mapped expert and novice performances of a standardized simulated laparoscopic task. Ability to distinguish between the 2 groups (construct validity) and correlation between techniques (concurrent validity) were the primary outcome measures. Forty-three expert and 38 novice performances demonstrated significant differences in LEAP-derived metrics for instrument path distance (P simulator. Construct validity is demonstrated by its ability to distinguish novice from expert performances. Only time and instrument path distance demonstrated concurrent validity with an existing tracking method however. A number of limitations to the tracking method used by LEAP have been identified. These need to be addressed before it can be considered an alternative to visual tracking for the delivery of objective performance metrics in take-home laparoscopic simulators. © The Author(s) 2015.

  2. Optimization of a polymer composite employing molecular mechanic simulations and artificial neural networks for a novel intravaginal bioadhesive drug delivery device.

    Science.gov (United States)

    Ndesendo, Valence M K; Pillay, Viness; Choonara, Yahya E; du Toit, Lisa C; Kumar, Pradeep; Buchmann, Eckhart; Meyer, Leith C R; Khan, Riaz A

    2012-01-01

    This study aimed at elucidating an optimal synergistic polymer composite for achieving a desirable molecular bioadhesivity and Matrix Erosion of a bioactive-loaded Intravaginal Bioadhesive Polymeric Device (IBPD) employing Molecular Mechanic Simulations and Artificial Neural Networks (ANN). Fifteen lead caplet-shaped devices were formulated by direct compression with the model bioactives zidovudine and polystyrene sulfonate. The Matrix Erosion was analyzed in simulated vaginal fluid to assess the critical integrity. Blueprinting the molecular mechanics of bioadhesion between vaginal epithelial glycoprotein (EGP), mucin (MUC) and the IBPD were performed on HyperChem 8.0.8 software (MM+ and AMBER force fields) for the quantification and characterization of correlative molecular interactions during molecular bioadhesion. Results proved that the IBPD bioadhesivity was pivoted on the conformation, orientation, and poly(acrylic acid) (PAA) composition that interacted with EGP and MUC present on the vaginal epithelium due to heterogeneous surface residue distributions (free energy= -46.33 kcalmol(-1)). ANN sensitivity testing as a connectionist model enabled strategic polymer selection for developing an IBPD with an optimally prolonged Matrix Erosion and superior molecular bioadhesivity (ME = 1.21-7.68%; BHN = 2.687-4.981 N/mm(2)). Molecular modeling aptly supported the EGP-MUC-PAA molecular interaction at the vaginal epithelium confirming the role of PAA in bioadhesion of the IBPD once inserted into the posterior fornix of the vagina.

  3. Automatic Speech Recognition from Neural Signals: A Focused Review.

    Science.gov (United States)

    Herff, Christian; Schultz, Tanja

    2016-01-01

    Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e., patients suffering from locked-in syndrome). For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences. Interfaces based on imagined speech would enable fast and natural communication without the need for audible speech and would give a voice to otherwise mute people. This focused review analyzes the potential of different brain imaging techniques to recognize speech from neural signals by applying Automatic Speech Recognition technology. We argue that modalities based on metabolic processes, such as functional Near Infrared Spectroscopy and functional Magnetic Resonance Imaging, are less suited for Automatic Speech Recognition from neural signals due to low temporal resolution but are very useful for the investigation of the underlying neural mechanisms involved in speech processes. In contrast, electrophysiologic activity is fast enough to capture speech processes and is therefor better suited for ASR. Our experimental results indicate the potential of these signals for speech recognition from neural data with a focus on invasively measured brain activity (electrocorticography). As a first example of Automatic Speech Recognition techniques used from neural signals, we discuss the Brain-to-text system.

  4. Automatic Speech Recognition from Neural Signals: A Focused Review

    Directory of Open Access Journals (Sweden)

    Christian Herff

    2016-09-01

    Full Text Available Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e.~patients suffering from locked-in syndrome. For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences. Interfaces based on imagined speech would enable fast and natural communication without the need for audible speech and would give a voice to otherwise mute people.This focused review analyzes the potential of different brain imaging techniques to recognize speech from neural signals by applying Automatic Speech Recognition technology. We argue that modalities based on metabolic processes, such as functional Near Infrared Spectroscopy and functional Magnetic Resonance Imaging, are less suited for Automatic Speech Recognition from neural signals due to low temporal resolution but are very useful for the investigation of the underlying neural mechanisms involved in speech processes. In contrast, electrophysiologic activity is fast enough to capture speech processes and is therefor better suited for ASR. Our experimental results indicate the potential of these signals for speech recognition from neural data with a focus on invasively measured brain activity (electrocorticography. As a first example of Automatic Speech Recognition techniques used from neural signals, we discuss the emph{Brain-to-text} system.

  5. An Evaluation of Hand-Force Prediction Using Artificial Neural-Network Regression Models of Surface EMG Signals for Handwear Devices

    Directory of Open Access Journals (Sweden)

    Masayuki Yokoyama

    2017-01-01

    Full Text Available Hand-force prediction is an important technology for hand-oriented user interface systems. Specifically, surface electromyography (sEMG is a promising technique for hand-force prediction, which requires a sensor with a small design space and low hardware costs. In this study, we applied several artificial neural-network (ANN regression models with different numbers of neurons and hidden layers and evaluated handgrip forces by using a dynamometer. A handwear with dry electrodes on the dorsal interosseous muscles was used for our evaluation. Eleven healthy subjects participated in our experiments. sEMG signals with six different levels of forces from 0 N to 200 N and maximum voluntary contraction (MVC are measured to train and test our ANN regression models. We evaluated three different methods (intrasession, intrasubject, and intersubject evaluation, and our experimental results show a high correlation (0.840, 0.770, and 0.789 each between the predicted forces and observed forces, which are normalized by the MVC for each subject. Our results also reveal that ANNs with deeper layers of up to four hidden layers show fewer errors in intrasession and intrasubject evaluations.

  6. Development of a Microfluidic Open Interface with Flow Isolated Desorption Volume for the Direct Coupling of SPME Devices to Mass Spectrometry.

    Science.gov (United States)

    Tascon, Marcos; Alam, Md Nazmul; Gómez-Ríos, Germán Augusto; Pawliszyn, Janusz

    2018-02-20

    Technologies that efficiently integrate the sampling and sample preparation steps with direct introduction to mass spectrometry (MS), providing simple and sensitive analytical workflows as well as capabilities for automation, can generate a great impact in a vast variety of fields, such as in clinical, environmental, and food-science applications. In this study, a novel approach that facilitates direct coupling of Bio-SPME devices to MS using a microfluidic design is presented. This technology, named microfluidic open interface (MOI), which operates under the concept of flow-isolated desorption volume, consists of an open-to-ambient desorption chamber (V ≤ 7 μL) connected to an ionization source. Subsequently, compounds of interest are transported to the ionization source by means of the self-aspiration process intrinsic of these interfaces. Thus, any ionization technology that provides a reliable and constant suction, such as electrospray ionization (ESI), atmospheric-pressure chemical ionization (APCI), or inductively coupled plasma ionization (ICP), can be hyphenated to MOI. Using this setup, the desorption chamber is used to release target compounds from the coating, while the isolation of the flow enables the ionization source to be continuously fed with solvent, all without the necessity of employment of additional valves. As a proof of concept, the design was applied to an ESI-MS/MS system for experimental validation. Furthermore, numerical simulations were undertaken to provide a detailed understanding of the fluid flow pattern inside the interface, then used to optimize the system for better efficiency. The analytical workflow of the developed Bio-SPME-MOI-MS setup consists of the direct immersion of SPME fibers into the matrix to extract/enrich analytes of interest within a short period of time, followed by a rinsing step with water to remove potentially adhering proteins, salts, and/or other interfering compounds. Next, the fiber is inserted into the

  7. The impact of command signal power distribution, processing delays, and speed scaling on neurally-controlled devices

    Science.gov (United States)

    Marathe, A. R.; Taylor, D. M.

    2015-08-01

    Objective. Decoding algorithms for brain-machine interfacing (BMI) are typically only optimized to reduce the magnitude of decoding errors. Our goal was to systematically quantify how four characteristics of BMI command signals impact closed-loop performance: (1) error magnitude, (2) distribution of different frequency components in the decoding errors, (3) processing delays, and (4) command gain. Approach. To systematically evaluate these different command features and their interactions, we used a closed-loop BMI simulator where human subjects used their own wrist movements to command the motion of a cursor to targets on a computer screen. Random noise with three different power distributions and four different relative magnitudes was added to the ongoing cursor motion in real time to simulate imperfect decoding. These error characteristics were tested with four different visual feedback delays and two velocity gains. Main results. Participants had significantly more trouble correcting for errors with a larger proportion of low-frequency, slow-time-varying components than they did with jittery, higher-frequency errors, even when the error magnitudes were equivalent. When errors were present, a movement delay often increased the time needed to complete the movement by an order of magnitude more than the delay itself. Scaling down the overall speed of the velocity command can actually speed up target acquisition time when low-frequency errors and delays are present. Significance. This study is the first to systematically evaluate how the combination of these four key command signal features (including the relatively-unexplored error power distribution) and their interactions impact closed-loop performance independent of any specific decoding method. The equations we derive relating closed-loop movement performance to these command characteristics can provide guidance on how best to balance these different factors when designing BMI systems. The equations reported

  8. Induced- and alternating-current electro-osmotic control of the diffusion layer growth in a microchannel-membrane interface device

    Science.gov (United States)

    Park, Sinwook; Yossifon, Gilad

    2014-11-01

    The passage of an electric current through an ionic permselective medium under an applied electric field is characterized by the formation of ionic concentration gradients, which result in regions of depleted and enriched ionic concentration at opposite ends of the medium. Induced-current electro-osmosis (ICEO) and alternating-current-electro-osmosis (ACEO) are shown to control the growth of the diffusion layer (DL) which, in turn, controls the diffusion limited ion transport through the microchannel-membrane system. We fabricated and tested devices made of a Nafion membrane connecting two opposite PDMS microchannels. An interdigitated electrode array was embedded within the microchannel with various distances from the microchannel-membrane interface. The induced ICEO (floating electrodes) / ACEO (active electrodes) vortices formed at the electrode array stir the fluid and thereby suppress the growth of the DL. The intensity of the ACEO vortices is controlled by either varying the voltage amplitude or the frequency, each having its own unique effect. Enhancement of the limiting current by on-demand control of the diffusion length is of importance in on-chip electro-dialysis, desalination and preconcentration of analytes.

  9. Non-invasive neural stimulation

    Science.gov (United States)

    Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

    2017-05-01

    Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

  10. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  11. Conduction Mechanisms at Interface of AlN/SiN Dielectric Stacks with AlGaN/GaN Heterostructures for Normally-off High Electron Mobility Transistors: Correlating Device Behavior with Nanoscale Interfaces Properties.

    Science.gov (United States)

    Greco, Giuseppe; Fiorenza, Patrick; Iucolano, Ferdinando; Severino, Andrea; Giannazzo, Filippo; Roccaforte, Fabrizio

    2017-10-11

    In this work, the conduction mechanisms at the interface of AlN/SiN dielectric stacks with AlGaN/GaN heterostructures have been studied combining different macroscopic and nanoscale characterizations on bare materials and devices. The AlN/SiN stacks grown on the recessed region of AlGaN/GaN heterostructures have been used as gate dielectric of hybrid metal-insulator-semiconductor high electron mobility transistors (MISHEMTs), showing a normally-off behavior (V th = +1.2 V), high channel mobility (204 cm 2 V -1 s -1 ), and very good switching behavior (I ON /I OFF current ratio of (5-6) × 10 8 and subthreshold swing of 90 mV/dec). However, the transistors were found to suffer from a positive shift of the threshold voltage during subsequent bias sweeps, which indicates electron trapping in the dielectric stack. To get a complete understanding of the conduction mechanisms and of the charge trapping phenomena in AlN/SiN films, nanoscale current and capacitance measurements by conductive atomic force microscopy (C-AFM) and scanning capacitance microscopy (SCM) have been compared with a macroscopic temperature-dependent characterization of gate current in MIS capacitors. The nanoscale electrical analyses showed the presence of a spatially uniform distribution of electrons trapping states in the insulator and the occurrence of a density of 7 × 10 8 cm -2 of local and isolated current spots at high bias values. These nanoscale conductive paths can be associated with electrically active defects responsible for the trap-assisted current transport mechanism through the dielectric, observed by the temperature-dependent characterization of the gate current. The results of this study can be relevant for future applications of AlN/SiN bilayers in GaN hybrid MISHEMT technology.

  12. A novel asynchronous access method with binary interfaces

    Directory of Open Access Journals (Sweden)

    Torres-Solis Jorge

    2008-10-01

    Full Text Available Abstract Background Traditionally synchronous access strategies require users to comply with one or more time constraints in order to communicate intent with a binary human-machine interface (e.g., mechanical, gestural or neural switches. Asynchronous access methods are preferable, but have not been used with binary interfaces in the control of devices that require more than two commands to be successfully operated. Methods We present the mathematical development and evaluation of a novel asynchronous access method that may be used to translate sporadic activations of binary interfaces into distinct outcomes for the control of devices requiring an arbitrary number of commands to be controlled. With this method, users are required to activate their interfaces only when the device under control behaves erroneously. Then, a recursive algorithm, incorporating contextual assumptions relevant to all possible outcomes, is used to obtain an informed estimate of user intention. We evaluate this method by simulating a control task requiring a series of target commands to be tracked by a model user. Results When compared to a random selection, the proposed asynchronous access method offers a significant reduction in the number of interface activations required from the user. Conclusion This novel access method offers a variety of advantages over traditionally synchronous access strategies and may be adapted to a wide variety of contexts, with primary relevance to applications involving direct object manipulation.

  13. Effects of Interfaces on Dynamics in Micro-Fluidic Devices: Slip-Boundaries’ Impact on Rotation Characteristics of Polar Liquid Film Motors

    Science.gov (United States)

    Jiang, Su-Rong; Liu, Zhong-Qiang; Amos Yinnon, Tamar; Kong, Xiang-Mu

    2017-05-01

    A new approach for exploring effects of interfaces on polar liquids is presented. Their impact on the polar liquid film motor (PLFM) – a novel micro-fluidic device – is studied. We account for the interface’s impact by modeling slip boundary effects on the PLFM’s electro-hydro-dynamical rotations. Our analytical results show as k={l}s/R increases (with {l}s denoting the slip length resulting from the interface’s impact on the film’s properties, k > -1 and R denoting the film’s radius): (a) PLFMs subsequently exhibit rotation characteristics under “negative-”, “no-”, “partial-” and “perfect-” slip boundary conditions; (b) The maximum value of the linear velocity of the steady rotating film increases linearly and its location approaches the film’s border; (c) The decay of the angular velocities’ dependency on the distance from the center of the film slows down, resulting in a macroscopic flow near the boundary. With our calculated rotation speed distributions consistent with the existing experimental ones, research aiming at fitting computed to measured distributions promises identifying the factors affecting {l}s, e.g., solid-fluid potential interactions and surface roughness. The consistency also is advantageous for optimizing PLFM’s applications as micro-washers, centrifuges, mixers in the lab-on-a-chip. Supported by National Natural Science Foundation of China under Grant Nos. 11302118, 11275112, and Natural Science Foundation of Shandong Province under Grant No. ZR2013AQ015

  14. Brain-computer interfaces: military, neurosurgical, and ethical perspective.

    Science.gov (United States)

    Kotchetkov, Ivan S; Hwang, Brian Y; Appelboom, Geoffrey; Kellner, Christopher P; Connolly, E Sander

    2010-05-01

    Brain-computer interfaces (BCIs) are devices that acquire and transform neural signals into actions intended by the user. These devices have been a rapidly developing area of research over the past 2 decades, and the military has made significant contributions to these efforts. Presently, BCIs can provide humans with rudimentary control over computer systems and robotic devices. Continued advances in BCI technology are especially pertinent in the military setting, given the potential for therapeutic applications to restore function after combat injury, and for the evolving use of BCI devices in military operations and performance enhancement. Neurosurgeons will play a central role in the further development and implementation of BCIs, but they will also have to navigate important ethical questions in the translation of this highly promising technology. In the following commentary the authors discuss realistic expectations for BCI use in the military and underscore the intersection of the neurosurgeon's civic and clinical duty to care for those who serve their country.

  15. Current challenges to the clinical translation of brain machine interface technology.

    Science.gov (United States)

    Lu, Charles W; Patil, Parag G; Chestek, Cynthia A

    2012-01-01

    Development of neural prostheses over the past few decades has produced a number of clinically relevant brain-machine interfaces (BMIs), such as the cochlear prostheses and deep brain stimulators. Current research pursues the restoration of communication or motor function to individuals with neurological disorders. Efforts in the field, such as the BrainGate trials, have already demonstrated that such interfaces can enable humans to effectively control external devices with neural signals. However, a number of significant issues regarding BMI performance, device capabilities, and surgery must be resolved before clinical use of BMI technology can become widespread. This chapter reviews challenges to clinical translation and discusses potential solutions that have been reported in recent literature, with focuses on hardware reliability, state-of-the-art decoding algorithms, and surgical considerations during implantation. Copyright © 2012 Elsevier Inc. All rights reserved.

  16. A 515 nW, 0-18 dB Programmable Gain Analog-to-Digital Converter for In-Channel Neural Recording Interfaces.

    Science.gov (United States)

    Rodriguez-Perez, Alberto; Delgado-Restituto, Manuel; Medeiro, Fernando

    2014-06-01

    This paper presents a low-area low-power Switched-Capacitor (SC)-based Programmable-Gain Analog-to-Digital Converter (PG-ADC) suitable for in-channel neural recording applications. The PG-ADC uses a novel implementation of the binary search algorithm that is complemented with adaptive biasing techniques for power saving. It has been fabricated in a standard CMOS 130 nm technology and only occupies 0.0326 mm(2). The PG-ADC has been optimized to operate under two different sampling modes, 27 kS/s and 90 kS/s. The former is tailored for raw data conversion of neural activity, whereas the latter is used for the on-the-fly feature extraction of neural spikes. Experimental results show that, under a voltage supply of 1.2 V, the PG-ADC obtains an ENOB of 7.56 bit (8-bit output) for both sampling modes, regardless of the gain setting. The amplification gain can be programmed from 0 to 18 dB. The power consumption of the PG-ADC at 90 kS/s is 1.52 μW with a FoM of 89.49 fJ/conv, whereas at 27 kS/s it consumes 515 nW and obtains a FoM of 98.31 fJ/conv .

  17. Dynamic Brain-Machine Interface: a novel paradigm for bidirectional interaction between brains and dynamical systems.

    Science.gov (United States)

    Szymanski, Francois D; Semprini, Marianna; Mussa-Ivaldi, Ferdinando A; Fadiga, Luciano; Panzeri, Stefano; Vato, Alessandro

    2011-01-01

    Brain-Machine Interfaces (BMIs) are systems which mediate communication between brains and artificial devices. Their long term goal is to restore motor functions, and this ultimately demands the development of a new generation of bidirectional brain-machine interfaces establishing a two-way brain-world communication channel, by both decoding motor commands from neural activity and providing feedback to the brain by electrical stimulation. Taking inspiration from how the spinal cord of vertebrates mediates communication between the brain and the limbs, here we present a model of a bidirectional brain-machine interface that interacts with a dynamical system by generating a control policy in the form of a force field. In our model, bidirectional communication takes place via two elements: (a) a motor interface decoding activities recorded from a motor cortical area, and (b) a sensory interface encoding the state of the controlled device into electrical stimuli delivered to a somatosensory area. We propose a specific mathematical model of the sensory and motor interfaces guiding a point mass moving in a viscous medium, and we demonstrate its performance by testing it on realistically simulated neural responses.

  18. Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: three-class classification of rest, right-, and left-hand motor execution.

    Science.gov (United States)

    Trakoolwilaiwan, Thanawin; Behboodi, Bahareh; Lee, Jaeseok; Kim, Kyungsoo; Choi, Ji-Woong

    2018-01-01

    The aim of this work is to develop an effective brain-computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification are desired. Previous studies have mainly extracted features from the signal manually, but proper features need to be selected carefully. To avoid performance degradation caused by manual feature selection, we applied convolutional neural networks (CNNs) as the automatic feature extractor and classifier for fNIRS-based BCI. In this study, the hemodynamic responses evoked by performing rest, right-, and left-hand motor execution tasks were measured on eight healthy subjects to compare performances. Our CNN-based method provided improvements in classification accuracy over conventional methods employing the most commonly used features of mean, peak, slope, variance, kurtosis, and skewness, classified by support vector machine (SVM) and artificial neural network (ANN). Specifically, up to 6.49% and 3.33% improvement in classification accuracy was achieved by CNN compared with SVM and ANN, respectively.

  19. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.

    Science.gov (United States)

    Hochberg, Leigh R; Bacher, Daniel; Jarosiewicz, Beata; Masse, Nicolas Y; Simeral, John D; Vogel, Joern; Haddadin, Sami; Liu, Jie; Cash, Sydney S; van der Smagt, Patrick; Donoghue, John P

    2012-05-16

    Paralysis following spinal cord injury, brainstem stroke, amyotrophic lateral sclerosis and other disorders can disconnect the brain from the body, eliminating the ability to perform volitional movements. A neural interface system could restore mobility and independence for people with paralysis by translating neuronal activity directly into control signals for assistive devices. We have previously shown that people with long-standing tetraplegia can use a neural interface system to move and click a computer cursor and to control physical devices. Able-bodied monkeys have used a neural interface system to control a robotic arm, but it is unknown whether people with profound upper extremity paralysis or limb loss could use cortical neuronal ensemble signals to direct useful arm actions. Here we demonstrate the ability of two people with long-standing tetraplegia to use neural interface system-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm and hand over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor 5 years earlier, also used a robotic arm to drink coffee from a bottle. Although robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after injury to the central nervous system, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals.

  20. Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface.

    Science.gov (United States)

    Jarosiewicz, Beata; Sarma, Anish A; Bacher, Daniel; Masse, Nicolas Y; Simeral, John D; Sorice, Brittany; Oakley, Erin M; Blabe, Christine; Pandarinath, Chethan; Gilja, Vikash; Cash, Sydney S; Eskandar, Emad N; Friehs, Gerhard; Henderson, Jaimie M; Shenoy, Krishna V; Donoghue, John P; Hochberg, Leigh R

    2015-11-11

    Brain-computer interfaces (BCIs) promise to restore independence for people with severe motor disabilities by translating decoded neural activity directly into the control of a computer. However, recorded neural signals are not stationary (that is, can change over time), degrading the quality of decoding. Requiring users to pause what they are doing whenever signals change to perform decoder recalibration routines is time-consuming and impractical for everyday use of BCIs. We demonstrate that signal nonstationarity in an intracortical BCI can be mitigated automatically in software, enabling long periods (hours to days) of self-paced point-and-click typing by people with tetraplegia, without degradation in neural control. Three key innovations were included in our approach: tracking the statistics of the neural activity during self-timed pauses in neural control, velocity bias correction during neural control, and periodically recalibrating the decoder using data acquired during typing by mapping neural activity to movement intentions that are inferred retrospectively based on the user's self-selected targets. These methods, which can be extended to a variety of neurally controlled applications, advance the potential for intracortical BCIs to help restore independent communication and assistive device control for people with paralysis. Copyright © 2015, American Association for the Advancement of Science.

  1. A chronic generalized bi-directional brain-machine interface.

    Science.gov (United States)

    Rouse, A G; Stanslaski, S R; Cong, P; Jensen, R M; Afshar, P; Ullestad, D; Gupta, R; Molnar, G F; Moran, D W; Denison, T J

    2011-06-01

    A bi-directional neural interface (NI) system was designed and prototyped by incorporating a novel neural recording and processing subsystem into a commercial neural stimulator architecture. The NI system prototype leverages the system infrastructure from an existing neurostimulator to ensure reliable operation in a chronic implantation environment. In addition to providing predicate therapy capabilities, the device adds key elements to facilitate chronic research, such as four channels of electrocortigram/local field potential amplification and spectral analysis, a three-axis accelerometer, algorithm processing, event-based data logging, and wireless telemetry for data uploads and algorithm/configuration updates. The custom-integrated micropower sensor and interface circuits facilitate extended operation in a power-limited device. The prototype underwent significant verification testing to ensure reliability, and meets the requirements for a class CF instrument per IEC-60601 protocols. The ability of the device system to process and aid in classifying brain states was preclinically validated using an in vivo non-human primate model for brain control of a computer cursor (i.e. brain-machine interface or BMI). The primate BMI model was chosen for its ability to quantitatively measure signal decoding performance from brain activity that is similar in both amplitude and spectral content to other biomarkers used to detect disease states (e.g. Parkinson's disease). A key goal of this research prototype is to help broaden the clinical scope and acceptance of NI techniques, particularly real-time brain state detection. These techniques have the potential to be generalized beyond motor prosthesis, and are being explored for unmet needs in other neurological conditions such as movement disorders, stroke and epilepsy.

  2. A chronic generalized bi-directional brain-machine interface

    Science.gov (United States)

    Rouse, A. G.; Stanslaski, S. R.; Cong, P.; Jensen, R. M.; Afshar, P.; Ullestad, D.; Gupta, R.; Molnar, G. F.; Moran, D. W.; Denison, T. J.

    2011-06-01

    A bi-directional neural interface (NI) system was designed and prototyped by incorporating a novel neural recording and processing subsystem into a commercial neural stimulator architecture. The NI system prototype leverages the system infrastructure from an existing neurostimulator to ensure reliable operation in a chronic implantation environment. In addition to providing predicate therapy capabilities, the device adds key elements to facilitate chronic research, such as four channels of electrocortigram/local field potential amplification and spectral analysis, a three-axis accelerometer, algorithm processing, event-based data logging, and wireless telemetry for data uploads and algorithm/configuration updates. The custom-integrated micropower sensor and interface circuits facilitate extended operation in a power-limited device. The prototype underwent significant verification testing to ensure reliability, and meets the requirements for a class CF instrument per IEC-60601 protocols. The ability of the device system to process and aid in classifying brain states was preclinically validated using an in vivo non-human primate model for brain control of a computer cursor (i.e. brain-machine interface or BMI). The primate BMI model was chosen for its ability to quantitatively measure signal decoding performance from brain activity that is similar in both amplitude and spectral content to other biomarkers used to detect disease states (e.g. Parkinson's disease). A key goal of this research prototype is to help broaden the clinical scope and acceptance of NI techniques, particularly real-time brain state detection. These techniques have the potential to be generalized beyond motor prosthesis, and are being explored for unmet needs in other neurological conditions such as movement disorders, stroke and epilepsy.

  3. Nanowire electrodes for high-density stimulation and measurement of neural circuits

    Directory of Open Access Journals (Sweden)

    Jacob T. Robinson

    2013-03-01

    Full Text Available Brain-machine interfaces (BMIs that can precisely monitor and control neural activity will likely require new hardware with improved resolution and specificity. New nanofabricated electrodes with feature sizes and densities comparable to neural circuits may lead to such improvements. In this perspective, we review the recent development of vertical nanowire (NW electrodes that could provide highly parallel single-cell recording and stimulation for future BMIs. We compare the advantages of these devices and discuss some of the technical challenges that must be overcome for this technology to become a platform for next-generation closed-loop BMIs.

  4. Wireless communication links for brain-machine interface applications

    Science.gov (United States)

    Larson, L.

    2016-05-01

    Recent technological developments have given neuroscientists direct access to neural signals in real time, with the accompanying ability to decode the resulting information and control various prosthetic devices and gain insight into deeper aspects of cognition. These developments - along with deep brain stimulation for Parkinson's disease and the possible use of electro-stimulation for other maladies - leads to the conclusion that the widespread use electronic brain interface technology is a long term possibility. This talk will summarize the various technical challenges and approaches that have been developed to wirelessly communicate with the brain, including technology constraints, dc power limits, compression and data rate issues.

  5. Development of wireless, chipless neural stimulator by using one-port surface acoustic wave delay line and diode-capacitor interface

    Science.gov (United States)

    Kim, Jisung; Kim, Saehan; Lee, Keekeun

    2017-06-01

    For the first time, a wireless and chipless neuron stimulator was developed by utilizing a surface acoustic wave (SAW) delay line, a diode-capacitor interface, a sharp metal tip, and antennas for the stimulation of neurons in the brain. The SAW delay line supersedes presently existing complex wireless transmission systems composed of a few thousands of transistors, enabling the fabrication of wireless and chipless transceiver systems. The diode-capacitor interface was used to convert AC signals to DC signals and induce stimulus pulses at a sharp metal probe. A 400 MHz RF energy was wirelessly radiated from antennas and then stimulation pulses were observed at a sharp gold probe. A ˜5 m reading distance was obtained using a 1 mW power from a network analyzer. The cycles of electromagnetic (EM) radiation from an antenna were controlled by shielding the antenna with an EM absorber. Stimulation pulses with different amplitudes and durations were successfully observed at the probe. The obtained pulses were ˜0.08 mV in amplitude and 3-10 Hz in frequency. Coupling-of-mode (COM) and SPICE modeling simulations were also used to determine the optimal structural parameters for SAW delay line and the values of passive elements. On the basis of the extracted parameters, the entire system was experimentally implemented and characterized.

  6. A brain-machine-muscle interface for restoring hindlimb locomotion after complete spinal transection in rats.

    Directory of Open Access Journals (Sweden)

    Monzurul Alam

    Full Text Available A brain-machine interface (BMI is a neuroprosthetic device that can restore motor function of individuals with paralysis. Although the feasibility of BMI control of upper-limb neuroprostheses has been demonstrated, a BMI for the restoration of lower-limb motor functions has not yet been developed. The objective of this study was to determine if gait-related information can be captured from neural activity recorded from the primary motor cortex of rats, and if this neural information can be used to stimulate paralysed hindlimb muscles after complete spinal cord transection. Neural activity was recorded from the hindlimb area of the primary motor cortex of six female Sprague Dawley rats during treadmill locomotion before and after mid-thoracic transection. Before spinal transection there was a strong association between neural activity and the step cycle. This association decreased after spinal transection. However, the locomotive state (standing vs. walking could still be successfully decoded from neural recordings made after spinal transection. A novel BMI device was developed that processed this neural information in real-time and used it to control electrical stimulation of paralysed hindlimb muscles. This system was able to elicit hindlimb muscle contractions that mimicked forelimb stepping. We propose this lower-limb BMI as a future neuroprosthesis for human paraplegics.

  7. A brain-machine-muscle interface for restoring hindlimb locomotion after complete spinal transection in rats.

    Science.gov (United States)

    Alam, Monzurul; Chen, Xi; Zhang, Zicong; Li, Yan; He, Jufang

    2014-01-01

    A brain-machine interface (BMI) is a neuroprosthetic device that can restore motor function of individuals with paralysis. Although the feasibility of BMI control of upper-limb neuroprostheses has been demonstrated, a BMI for the restoration of lower-limb motor functions has not yet been developed. The objective of this study was to determine if gait-related information can be captured from neural activity recorded from the primary motor cortex of rats, and if this neural information can be used to stimulate paralysed hindlimb muscles after complete spinal cord transection. Neural activity was recorded from the hindlimb area of the primary motor cortex of six female Sprague Dawley rats during treadmill locomotion before and after mid-thoracic transection. Before spinal transection there was a strong association between neural activity and the step cycle. This association decreased after spinal transection. However, the locomotive state (standing vs. walking) could still be successfully decoded from neural recordings made after spinal transection. A novel BMI device was developed that processed this neural information in real-time and used it to control electrical stimulation of paralysed hindlimb muscles. This system was able to elicit hindlimb muscle contractions that mimicked forelimb stepping. We propose this lower-limb BMI as a future neuroprosthesis for human paraplegics.

  8. Optical-to-optical interface device. [consisting of two transparent electrodes on glass substrates that enclose thin film photoconductor and thin layer of nematic liquid crystal

    Science.gov (United States)

    Jacobson, A. D.

    1973-01-01

    Studies were conducted on the performance of a photoactivated dc liquid crystal light valve. The dc light valve is a thin film device that consists of two transparent electrodes, deposited on glass substrates, that enclose a thin film photoconductor (cadmium sulfide) and a thin layer of a nematic liquid crystal that operates in the dynamic scattering mode. The work was directed toward application of the light valve to high resolution non-coherent light to coherent light image conversion. The goal of these studies was to improve the performance and quality of the already existing dc light valve device and to evaluate quantitatively the properties and performance of the device as they relate to the coherent optical data processing application. As a result of these efforts, device sensitivity was improved by a factor of ten, device resolution was improved by a factor of three, device lifetime was improved by two-orders of magnitude, undesirable secondary liquid crystal scattering effects were eliminated, the scattering characteristics of the liquid crystal were thoroughly documented, the cosmetic quality of the devices was dramatically improved, and the performance of the device was fully documented.

  9. Kinetic Interface

    DEFF Research Database (Denmark)

    2009-01-01

    A kinetic interface for orientation detection in a video training system is disclosed. The interface includes a balance platform instrumented with inertial motion sensors. The interface engages a participant's sense of balance in training exercises.......A kinetic interface for orientation detection in a video training system is disclosed. The interface includes a balance platform instrumented with inertial motion sensors. The interface engages a participant's sense of balance in training exercises....

  10. Cognitive Control Signals for Neural Prosthetics

    National Research Council Canada - National Science Library

    S. Musallam; B. D. Corneil; B. Greger; H. Scherberger; R. A. Andersen

    2004-01-01

    Recent development of neural prosthetics for assisting paralyzed patients has focused on decoding intended hand trajectories from motor cortical neurons and using this signal to control external devices...

  11. Activity Patterns of Cultured Neural Networks on Micro Electrode Arrays

    National Research Council Canada - National Science Library

    Rutten, Wim

    2001-01-01

    A hybrid neuro-electronic interface is a cell-cultured micro electrode array, acting as a neural information transducer for stimulation and/or recording of neural activity in the brain or the spinal cord...

  12. Cultured neural networks: Optimisation of patterned network adhesiveness and characterisation of their neural activity

    NARCIS (Netherlands)

    Rutten, Wim; Ruardij, T.G.; Marani, Enrico; Roelofsen, B.H.

    2006-01-01

    One type of future, improved neural interface is the "cultured probe"?. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA) on a planar substrate, each electrode being covered and

  13. Study of the interface stability of the metal (Mo, Ni, Pd/HfO2/AlN/InGaAs MOS devices

    Directory of Open Access Journals (Sweden)

    Huy Binh Do

    2017-08-01

    Full Text Available The degeneration of the metal/HfO2 interfaces for Mo, Ni, and Pd gate metals was studied in this paper. An unstable PdOx interfacial layer formed at the Pd/HfO2 interface, inducing the oxygen segregation for the Pd/HfO2/InGaAs metal oxide capacitor (MOSCAP. The low dissociation energy for the Pd-O bond was the reason for oxygen segregation. The PdOx layer contains O2− and OH− ions which are mobile during thermal annealing and electrical stress test. The phenomenon was not observed for the (Mo, Ni/HfO2/InGaAs MOSCAPs. The results provide the guidance for choosing the proper metal electrode for the InGaAs based MOSFET.

  14. Estimation of current constriction losses via 3D tomography reconstructions in electrochemical devices: a case study of a solid oxide cell electrode/electrolyte interface

    DEFF Research Database (Denmark)

    Nielsen, Jimmi; Jørgensen, Peter Stanley

    2017-01-01

    In the present study, the methodology for accurate estimations of the current constriction resistance in solid state electrochemical devices via 3D tomography reconstructions is developed. The methodology is used to determine the current constriction resistances at the Ni:YSZ anode/YSZ electrolyte...

  15. An integrated neuro-robotic interface for stroke rehabilitation using the NASA X1 powered lower limb exoskeleton.

    Science.gov (United States)

    He, Yongtian; Nathan, Kevin; Venkatakrishnan, Anusha; Rovekamp, Roger; Beck, Christopher; Ozdemir, Recep; Francisco, Gerard E; Contreras-Vidal, Jose L

    2014-01-01

    Stroke remains a leading cause of disability, limiting independent ambulation in survivors, and consequently affecting quality of life (QOL). Recent technological advances in neural interfacing with robotic rehabilitation devices are promising in the context of gait rehabilitation. Here, the X1, NASA's powered robotic lower limb exoskeleton, is introduced as a potential diagnostic, assistive, and therapeutic tool for stroke rehabilitation. Additionally, the feasibility of decoding lower limb joint kinematics and kinetics during walking with the X1 from scalp electroencephalographic (EEG) signals--the first step towards the development of a brain-machine interface (BMI) system to the X1 exoskeleton--is demonstrated.

  16. Powering biomedical devices

    CERN Document Server

    Romero, Edwar

    2013-01-01

    From exoskeletons to neural implants, biomedical devices are no less than life-changing. Compact and constant power sources are necessary to keep these devices running efficiently. Edwar Romero's Powering Biomedical Devices reviews the background, current technologies, and possible future developments of these power sources, examining not only the types of biomedical power sources available (macro, mini, MEMS, and nano), but also what they power (such as prostheses, insulin pumps, and muscular and neural stimulators), and how they work (covering batteries, biofluids, kinetic and ther

  17. Source interface for ALICE

    CERN Multimedia

    Patrice Loïez

    2001-01-01

    This interface is part of the ALICE detector data link (DDL), which transmits data at 100 Mbytes/sec from the detectors to a host computer. A total of 400 DDLs will be installed on ALICE. These silicon devices have been developed especially for use in the high radiation levels produced in detector environments.

  18. Is the interface OK?

    Digital Repository Service at National Institute of Oceanography (India)

    Suresh, T.

    When a peripheral device fails, software methods can be initially resorted to before the usual hardware test procedures are used. A test program is presented here that allows various peripherals, inter-faced to a Norsk Data computer, to be tested...

  19. An artifical neural network for detection of simulated dental caries

    Energy Technology Data Exchange (ETDEWEB)

    Kositbowornchai, S. [Khon Kaen Univ. (Thailand). Dept. of Oral Diagnosis; Siriteptawee, S.; Plermkamon, S.; Bureerat, S. [Khon Kaen Univ. (Thailand). Dept. of Mechanical Engineering; Chetchotsak, D. [Khon Kaen Univ. (Thailand). Dept. of Industrial Engineering

    2006-08-15

    Objects: A neural network was developed to diagnose artificial dental caries using images from a charged-coupled device (CCD)camera and intra-oral digital radiography. The diagnostic performance of this neural network was evaluated against a gold standard. Materials and methods: The neural network design was the Learning Vector Quantization (LVQ) used to classify a tooth surface as sound or as having dental caries. The depth of the dental caries was indicated on a graphic user interface (GUI) screen developed by Matlab programming. Forty-nine images of both sound and simulated dental caries, derived from a CCD camera and by digital radiography, were used to 'train' an artificial neural network. After the 'training' process, a separate test-set comprising 322 unseen images was evaluated. Tooth sections and microscopic examinations were used to confirm the actual dental caries status.The performance of neural network was evaluated using diagnostic test. Results: The sensitivity (95%CI)/specificity (95%CI) of dental caries detection by the CCD camera and digital radiography were 0.77(0.68-0.85)/0.85(0.75-0.92) and 0.81(0.72-0.88)/0.93(0.84-0.97), respectively. The accuracy of caries depth-detection by the CCD camera and digital radiography was 58 and 40%, respectively. Conclusions: The model neural network used in this study could be a prototype for caries detection but should be improved for classifying caries depth. Our study suggests an artificial neural network can be trained to make the correct interpretations of dental caries. (orig.)

  20. Interface Consistency

    DEFF Research Database (Denmark)

    Staunstrup, Jørgen

    1998-01-01

    This paper proposes that Interface Consistency is an important issue for the development of modular designs. Byproviding a precise specification of component interfaces it becomes possible to check that separately developedcomponents use a common interface in a coherent matter thus avoiding a very...

  1. EMG-based and gaze-tracking-based man-machine interfaces.

    Science.gov (United States)

    Carpi, Federico; Rossi, Danilo De

    2009-01-01

    A great demand for brain-machine and, more generally, man-machine interfaces is arising nowadays, pushed by several promising scientific and technological results, which are encouraging the concentration of efforts in this field. The possibility of measuring, processing and decoding brain activity, so as to interpret neural signals, is often looked at as a possibility to bypass lost or damaged neural and/or motor structures. Beyond that, such interfaces currently show a potential for applications in other fields, space science being certainly one of them. At present, the concept of "reading" the brain to detect intended actions and use these to control external devices is being studied with several technical and methodological approaches; among these, interfaces based on electroencephalographic signals play today a prominent role. Within such a context, the aim of this section is to present a brief survey on two types of noninvasive man-machine interfaces based on a different approach. In particular, they rely on the extraction of control signals from the user with techniques that adopt electromyography and gaze tracking. Working principles, implementations, typical features, and applications of these two types of interfaces are reported.

  2. Using synthetic biology to interface with physical micro and nano-sized sensors (Conference Presentation)

    Science.gov (United States)

    Hanson, Russell; Fuller, Jason; Cheng, Andrew

    2017-05-01

    This talk will discuss the current goals and efforts of point of care and personal health monitoring systems: what they can do now and what is in the works. These interfaces can be used in a precision medicine context—making diagnoses and getting the right drugs to the right patients at the right time. Many of the same sensors and engineering are being prototyped now for neural interfaces and recording devices with applications in visual, auditory, and motor cortex, allowing basic research along with preliminary applications in actuation and sensing. While miniaturization and electronics development using established manufacturing protocols can provide the current engineering foundations, novel biochemical ligands and molecular detectors can provide the needed flexibility for next-generation devices.

  3. A bidirectional brain-machine interface connecting alert rodents to a dynamical system.

    Science.gov (United States)

    Boi, Fabio; Semprini, Marianna; Mussa Ivaldi, Ferdinando A; Panzeri, Stefano; Vato, Alessandro

    2015-01-01

    We present a novel experimental framework that implements a bidirectional brain-machine interface inspired by the operation of the spinal cord in vertebrates that generates a control policy in the form of a force field. The proposed experimental set-up allows connecting the brain of freely moving rats to an external device. We tested this apparatus in a preliminary experiment with an alert rat that used the interface for acquiring a food reward. The goal of this approach to bidirectional interfaces is to explore the role of voluntary neural commands in controlling a dynamical system represented by a small cart moving on vertical plane and connected to a water/pellet dispenser.

  4. Nanoelectronics Meets Biology: From Novel Nanoscale Devices for Live Cell Recording to 3D Innervated Tissues†

    Science.gov (United States)

    Duan, Xiaojie; Lieber, Charles M.

    2013-01-01

    High spatio-temporal resolution interfacing between electrical sensors and biological systems, from single live cells to tissues, is crucial for many areas, including fundamental biophysical studies as well as medical monitoring and intervention. This focused review summarizes recent progresses in the development and application of novel nanoscale devices for intracellular electrical recordings of action potentials, and the effort of merging electronic and biological systems seamlessly in three dimension using macroporous nanoelectronic scaffolds. The uniqueness of these nanoscale devices for minimally invasive, large scale, high spatial resolution, and three dimensional neural activity mapping will be highlighted. PMID:23946279

  5. Wireless gigabit data telemetry for large-scale neural recording.

    Science.gov (United States)

    Kuan, Yen-Cheng; Lo, Yi-Kai; Kim, Yanghyo; Chang, Mau-Chung Frank; Liu, Wentai

    2015-05-01

    Implantable wireless neural recording from a large ensemble of simultaneously acting neurons is a critical component to thoroughly investigate neural interactions and brain dynamics from freely moving animals. Recent researches have shown the feasibility of simultaneously recording from hundreds of neurons and suggested that the ability of recording a larger number of neurons results in better signal quality. This massive recording inevitably demands a large amount of data transfer. For example, recording 2000 neurons while keeping the signal fidelity ( > 12 bit, > 40 KS/s per neuron) needs approximately a 1-Gb/s data link. Designing a wireless data telemetry system to support such (or higher) data rate while aiming to lower the power consumption of an implantable device imposes a grand challenge on neuroscience community. In this paper, we present a wireless gigabit data telemetry for future large-scale neural recording interface. This telemetry comprises of a pair of low-power gigabit transmitter and receiver operating at 60 GHz, and establishes a short-distance wireless link to transfer the massive amount of neural signals outward from the implanted device. The transmission distance of the received neural signal can be further extended by an externally rendezvous wireless transceiver, which is less power/heat-constraint since it is not at the immediate proximity of the cortex and its radiated signal is not seriously attenuated by the lossy tissue. The gigabit data link has been demonstrated to achieve a high data rate of 6 Gb/s with a bit-error-rate of 10(-12) at a transmission distance of 6 mm, an applicable separation between transmitter and receiver. This high data rate is able to support thousands of recording channels while ensuring a low energy cost per bit of 2.08 pJ/b.

  6. Wireless microsensor network solutions for neurological implantable devices

    Science.gov (United States)

    Abraham, Jose K.; Whitchurch, Ashwin; Varadan, Vijay K.

    2005-05-01

    The design and development of wireless mocrosensor network systems for the treatment of many degenerative as well as traumatic neurological disorders is presented in this paper. Due to the advances in micro and nano sensors and wireless systems, the biomedical sensors have the potential to revolutionize many areas in healthcare systems. The integration of nanodevices with neurons that are in communication with smart microsensor systems has great potential in the treatment of many neurodegenerative brain disorders. It is well established that patients suffering from either Parkinson"s disease (PD) or Epilepsy have benefited from the advantages of implantable devices in the neural pathways of the brain to alter the undesired signals thus restoring proper function. In addition, implantable devices have successfully blocked pain signals and controlled various pelvic muscles in patients with urinary and fecal incontinence. Even though the existing technology has made a tremendous impact on controlling the deleterious effects of disease, it is still in its infancy. This paper presents solutions of many problems of today's implantable and neural-electronic interface devices by combining nanowires and microelectronics with BioMEMS and applying them at cellular level for the development of a total wireless feedback control system. The only device that will actually be implanted in this research is the electrodes. All necessary controllers will be housed in accessories that are outside the body that communicate with the implanted electrodes through tiny inductively-coupled antennas. A Parkinson disease patient can just wear a hat-system close to the implantable neural probe so that the patient is free to move around, while the sensors continually monitor, record, transmit all vital information to health care specialist. In the event of a problem, the system provides an early warning to the patient while they are still mobile thus providing them the opportunity to react and

  7. Interfacing for Economical Data Gathering and Processing.

    Science.gov (United States)

    Slezak, Tom

    1981-01-01

    By interfacing a Biotran II counting device with an Apple II computer, biologists in a biomedical laboratory increased accuracy and speed over manual logging of Biotran readings. Suggests that others interface small computers to computer readable devices as a cost-effective approach. Outlines necessary steps. (DC)

  8. XML Interfaces to the Internet of Things

    NARCIS (Netherlands)

    S. Pemberton (Steven); C Foster

    2015-01-01

    htmlabstractThe internet of things is predicated on tiny, cheap, lower power computers being embedded in devices everywhere. However such tiny devices by definition have very little memory and computing power available to support user interfaces or extended servers, and so the user interface

  9. Interface Realisms

    DEFF Research Database (Denmark)

    Pold, Søren

    2005-01-01

    This article argues for seeing the interface as an important representational and aesthetic form with implications for postmodern culture and digital aesthetics. The interface emphasizes realism due in part to the desire for transparency in Human-Computer Interaction (HCI) and partly to the devel......This article argues for seeing the interface as an important representational and aesthetic form with implications for postmodern culture and digital aesthetics. The interface emphasizes realism due in part to the desire for transparency in Human-Computer Interaction (HCI) and partly...

  10. Combining Non-Pharmacological Treatments with Pharmacotherapies for Neurological Disorders: A Unique Interface of the Brain, Drug–Device, and Intellectual Property

    Science.gov (United States)

    Bulaj, Grzegorz

    2014-01-01

    Mobile medical applications (mHealth), music, and video games are being developed and tested for their ability to improve pharmacotherapy outcomes and medication adherence. Pleiotropic mechanism of music and gamification engages an intrinsic motivation and the brain reward system, supporting therapies in patients with neurological disorders, including neuropathic pain, depression, anxiety, or neurodegenerative disorders. Based on accumulating results from clinical trials, an innovative combination treatment of epilepsy seizures, comorbidities, and the medication non-adherence can be designed, consisting of antiepileptic drugs and disease self-management software delivering clinically beneficial music. Since creative elements and art expressed in games, music, and software are copyrighted, therefore clinical and regulatory challenges in developing copyrighted, drug–device therapies may be offset by a value proposition of the exclusivity due to the patent–independent protection, which can last for over 70 years. Taken together, development of copyrighted non-pharmacological treatments (e-therapies), and their combinations with pharmacotherapies, offer incentives to chronically ill patients and outcome-driven health care industries. PMID:25071711

  11. Combining non-pharmacological treatments with pharmacotherapies for neurological disorders: a unique interface of the brain, drug-device, and intellectual property.

    Science.gov (United States)

    Bulaj, Grzegorz

    2014-01-01

    Mobile medical applications (mHealth), music, and video games are being developed and tested for their ability to improve pharmacotherapy outcomes and medication adherence. Pleiotropic mechanism of music and gamification engages an intrinsic motivation and the brain reward system, supporting therapies in patients with neurological disorders, including neuropathic pain, depression, anxiety, or neurodegenerative disorders. Based on accumulating results from clinical trials, an innovative combination treatment of epilepsy seizures, comorbidities, and the medication non-adherence can be designed, consisting of antiepileptic drugs and disease self-management software delivering clinically beneficial music. Since creative elements and art expressed in games, music, and software are copyrighted, therefore clinical and regulatory challenges in developing copyrighted, drug-device therapies may be offset by a value proposition of the exclusivity due to the patent-independent protection, which can last for over 70 years. Taken together, development of copyrighted non-pharmacological treatments (e-therapies), and their combinations with pharmacotherapies, offer incentives to chronically ill patients and outcome-driven health care industries.

  12. Combining Non-pharmacological Treatments with Pharmacotherapies for Neurological Disorders: a Unique Interface of the Brain, Drug-Device and Intellectual Property

    Directory of Open Access Journals (Sweden)

    Grzegorz eBulaj

    2014-07-01

    Full Text Available Mobile medical applications (mHealth, music and video games are being developed and tested for their ability to improve pharmacotherapy outcomes and medication adherence. Pleiotropic mechanism of music and gamification engage an intrinsic motivation and the brain reward system, supporting therapies in patients with neurological disorders, including neuropathic pain, depression, anxiety, or neurodegenerative disorders. Based on accumulating results from clinical trials, an innovative combination treatment of epilepsy seizures, comorbidities and the medication non-adherence can be designed, consisting of antiepileptic drugs and disease self-management software delivering clinically beneficial music. Since creative elements and art expressed in games, music and software are copyrighted, therefore clinical and regulatory challenges in developing copyrighted, drug-device therapies may be offset by a value proposition of the exclusivity due to the patent-independent protection which can last for over 70 years. Taken together, development of copyrighted non-pharmacological treatments (e-therapies, and their combinations with pharmacotherapies, offers incentives to chronically-ill patients and outcome-driven health care industries.

  13. A bidirectional brain-machine interface algorithm that approximates arbitrary force-fields.

    Directory of Open Access Journals (Sweden)

    Alessandro Vato

    Full Text Available We examine bidirectional brain-machine interfaces that control external devices in a closed loop by decoding motor cortical activity to command the device and by encoding the state of the device by delivering electrical stimuli to sensory areas. Although it is possible to design this artificial sensory-motor interaction while maintaining two independent channels of communication, here we propose a rule that closes the loop between flows of sensory and motor information in a way that approximates a desired dynamical policy expressed as a field of forces acting upon the controlled external device. We previously developed a first implementation of this approach based on linear decoding of neural activity recorded from the motor cortex into a set of forces (a force field applied to a point mass, and on encoding of position of the point mass into patterns of electrical stimuli delivered to somatosensory areas. However, this previous algorithm had the limitation that it only worked in situations when the position-to-force map to be implemented is invertible. Here we overcome this limitation by developing a new non-linear form of the bidirectional interface that can approximate a virtually unlimited family of continuous fields. The new algorithm bases both the encoding of position information and the decoding of motor cortical activity on an explicit map between spike trains and the state space of the device computed with Multi-Dimensional-Scaling. We present a detailed computational analysis of the performance of the interface and a validation of its robustness by using synthetic neural responses in a simulated sensory-motor loop.

  14. A bidirectional brain-machine interface algorithm that approximates arbitrary force-fields.

    Science.gov (United States)

    Vato, Alessandro; Szymanski, Francois D; Semprini, Marianna; Mussa-Ivaldi, Ferdinando A; Panzeri, Stefano

    2014-01-01

    We examine bidirectional brain-machine interfaces that control external devices in a closed loop by decoding motor cortical activity to command the device and by encoding the state of the device by delivering electrical stimuli to sensory areas. Although it is possible to design this artificial sensory-motor interaction while maintaining two independent channels of communication, here we propose a rule that closes the loop between flows of sensory and motor information in a way that approximates a desired dynamical policy expressed as a field of forces acting upon the controlled external device. We previously developed a first implementation of this approach based on linear decoding of neural activity recorded from the motor cortex into a set of forces (a force field) applied to a point mass, and on encoding of position of the point mass into patterns of electrical stimuli delivered to somatosensory areas. However, this previous algorithm had the limitation that it only worked in situations when the position-to-force map to be implemented is invertible. Here we overcome this limitation by developing a new non-linear form of the bidirectional interface that can approximate a virtually unlimited family of continuous fields. The new algorithm bases both the encoding of position information and the decoding of motor cortical activity on an explicit map between spike trains and the state space of the device computed with Multi-Dimensional-Scaling. We present a detailed computational analysis of the performance of the interface and a validation of its robustness by using synthetic neural responses in a simulated sensory-motor loop.

  15. Research and Implementation of a USB Interfaced Real-Time Power Quality Disturbance Classification System

    Directory of Open Access Journals (Sweden)

    GOK, M.

    2017-08-01

    Full Text Available In this study, the research and implementation of an automatic power quality (PQ recognition system are presented. This system contains a USB interfaced multichannel data acquisition (DAQ device and a graphical user interfaced (GUI application. The DAQ device consists of an analog-to-digital (ADC converter, field programmable gate array (FPGA and a USB first in first out (FIFO buffer interface chip. The application employs Stockwell Transform (ST technique combined with neural network model to build the classifier. Eight basic and two combined PQ disturbances are determined for the classification. Different from the previous studies, the synthetic signals used for neural network training are modified by adding the harmonics detected in the real signal. This approach is used to increase the classifier accuracy against the real line power signal. Also, ST is simplified by using only the frequencies which are required in the feature extraction step to reduce the processing time. Developed application handles the signal processing, the classification, and the database recording tasks by using multi-threaded programming approach under the mean time of 41 ms. The experimental results show that the proposed power quality disturbance detection system is capable of recognizing and reporting power quality faults effectively within the real-time requirements.

  16. A non-linear mapping algorithm shaping the control policy of a bidirectional brain machine interface.

    Science.gov (United States)

    Boi, Fabio; Semprini, Marianna; Vato, Alessandro

    2016-08-01

    Motor brain-machine interfaces (BMIs) transform neural activities recorded directly from the brain into motor commands to control the movements of an external object by establishing an interface between the central nervous system (CNS) and the device. Bidirectional BMIs are closed-loop systems that add a sensory channel to provide the brain with an artificial feedback signal produced by the interaction between the device and the external world. Taking inspiration from the functioning of the spinal cord in mammalians, in our previous works we designed and developed a bidirectional BMI that uses the neural signals recorded form rats' motor cortex to control the movement of an external object. We implemented a decoding interface based on the approximation of a predefined force field with a central attractor point. Now we consider a non-linear transformation that allows to design a decoder approximating force fields with arbitrary attractors. We describe here the non-linear mapping algorithm and preliminary results of its use with behaving rats.

  17. Interface models

    DEFF Research Database (Denmark)

    Ravn, Anders P.; Staunstrup, Jørgen

    1994-01-01

    This paper proposes a model for specifying interfaces between concurrently executing modules of a computing system. The model does not prescribe a particular type of communication protocol and is aimed at describing interfaces between both software and hardware modules or a combination of the two...

  18. Organic interfaces

    NARCIS (Netherlands)

    Poelman, W.A.; Tempelman, E.

    2014-01-01

    This paper deals with the consequences for product designers resulting from the replacement of traditional interfaces by responsive materials. Part 1 presents a theoretical framework regarding a new paradigm for man-machine interfacing. Part 2 provides an analysis of the opportunities offered by new

  19. Fluid Interfaces

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius

    2001-01-01

    Fluid interaction, interaction by the user with the system that causes few breakdowns, is essential to many user interfaces. We present two concrete software systems that try to support fluid interaction for different work practices. Furthermore, we present specificity, generality, and minimality...... as design goals for fluid interfaces....

  20. Microchip-Embedded Capacitors for Implantable Neural Stimulators

    Science.gov (United States)

    Auciello, Orlando

    Miniaturization of microchips for implantation in the human body (e.g., microchip for the artificial retina to restore sight to people blinded by retina photoreceptors degeneration) requires the integration of high-capacitance (≥ 10 μF) energy-storage capacitors into the microchip. These capacitors would be based on high-dielectric constant layers, preferably made of materials that are bioinert (not affected by human body fluids) and are biocompatible (do not elicit adverse reactions in the human body). This chapter focuses on reviewing the work being done at Argonne National Laboratory (Materials Science Division and Center for Nanoscale Materials) to develop high-capacitance microchip-embedded capacitors based on novel high-K dielectric layers (TiAlOx or TiO2/Al2O3 superlattices). The microchip-embedded capacitor provides energy storage and electromagnetic signal coupling needed for neural stimulations. Advances in neural prostheses such as artificial retinas and cochlear implants require miniaturization of device size to minimize tissue damage and improve device/tissue interfaces in the human body. Therefore, development of microchip-embedded capacitors is critical to achieve full-implantable biomedical device miniaturization.

  1. Affective Brain-Computer Interfaces (aBCI 2011)

    NARCIS (Netherlands)

    Mühl, C.; Nijholt, Antinus; Allison, Brandan; Dunne, Stephen; Heylen, Dirk K.J.; D' Mello, Sidney; Graesser, Arthur; Schuller, Björn; Martin, Jean-Claude

    2011-01-01

    Recently, many groups (see Zander and Kothe. Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general. J. Neural Eng., 8, 2011) have worked toward expanding brain-computer interface (BCI) systems to include not only active control,

  2. A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface.

    Science.gov (United States)

    Su, Yi; Routhu, Sudhamayee; Moon, Kee S; Lee, Sung Q; Youm, WooSub; Ozturk, Yusuf

    2016-09-24

    All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex. This paper introduces a compact-sized implantable wireless 32-channel bidirectional brain machine interface (BBMI) to be used with freely-moving primates. The system is designed to monitor brain sensorimotor rhythms and present current stimuli with a configurable duration, frequency and amplitude in real time to the brain based on the brain activity report. The battery is charged via a novel ultrasonic wireless power delivery module developed for efficient delivery of power into a deeply-implanted system. The system was successfully tested through bench tests and in vivo tests on a behaving primate to record the local field potential (LFP) oscillation and stimulate the target area at the same time.

  3. A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface

    Directory of Open Access Journals (Sweden)

    Yi Su

    2016-09-01

    Full Text Available All neural information systems (NIS rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex. This paper introduces a compact-sized implantable wireless 32-channel bidirectional brain machine interface (BBMI to be used with freely-moving primates. The system is designed to monitor brain sensorimotor rhythms and present current stimuli with a configurable duration, frequency and amplitude in real time to the brain based on the brain activity report. The battery is charged via a novel ultrasonic wireless power delivery module developed for efficient delivery of power into a deeply-implanted system. The system was successfully tested through bench tests and in vivo tests on a behaving primate to record the local field potential (LFP oscillation and stimulate the target area at the same time.

  4. Matched Interface and Boundary Method for Elasticity Interface Problems

    Science.gov (United States)

    Wang, Bao; Xia, Kelin; Wei, Guo-Wei

    2015-01-01

    Elasticity theory is an important component of continuum mechanics and has had widely spread applications in science and engineering. Material interfaces are ubiquity in nature and man-made devices, and often give rise to discontinuous coefficients in the governing elasticity equations. In this work, the matched interface and boundary (MIB) method is developed to address elasticity interface problems. Linear elasticity theory for both isotropic homogeneous and inhomogeneous media is employed. In our approach, Lamé’s parameters can have jumps across the interface and are allowed to be position dependent in modeling isotropic inhomogeneous material. Both strong discontinuity, i.e., discontinuous solution, and weak discontinuity, namely, discontinuous derivatives of the solution, are considered in the present study. In the proposed method, fictitious values are utilized so that the standard central finite different schemes can be employed regardless of the interface. Interface jump conditions are enforced on the interface, which in turn, accurately determines fictitious values. We design new MIB schemes to account for complex interface geometries. In particular, the cross derivatives in the elasticity equations are difficult to handle for complex interface geometries. We propose secondary fictitious values and construct geometry based interpolation schemes to overcome this difficulty. Numerous analytical examples are used to validate the accuracy, convergence and robustness of the present MIB method for elasticity interface problems with both small and large curvatures, strong and weak discontinuities, and constant and variable coefficients. Numerical tests indicate second order accuracy in both L∞ and L2 norms. PMID:25914439

  5. Portable non-invasive brain-computer interface: challenges and opportunities of optical modalities

    Science.gov (United States)

    Scholl, Clara A.; Hendrickson, Scott M.; Swett, Bruce A.; Fitch, Michael J.; Walter, Erich C.; McLoughlin, Michael P.; Chevillet, Mark A.; Blodgett, David W.; Hwang, Grace M.

    2017-05-01

    The development of portable non-invasive brain computer interface technologies with higher spatio-temporal resolution has been motivated by the tremendous success seen with implanted devices. This talk will discuss efforts to overcome several major obstacles to viability including approaches that promise to improve spatial and temporal resolution. Optical approaches in particular will be highlighted and the potential benefits of both Blood-Oxygen Level Dependent (BOLD) and Fast Optical Signal (FOS) will be discussed. Early-stage research into the correlations between neural activity and FOS will be explored.

  6. Neural stimulation and recording with bidirectional, soft carbon nanotube fiber microelectrodes.

    Science.gov (United States)

    Vitale, Flavia; Summerson, Samantha R; Aazhang, Behnaam; Kemere, Caleb; Pasquali, Matteo

    2015-01-01

    The development of microelectrodes capable of safely stimulating and recording neural activity is a critical step in the design of many prosthetic devices, brain-machine interfaces, and therapies for neurologic or nervous-system-mediated disorders. Metal electrodes are inadequate prospects for the miniaturization needed to attain neuronal-scale stimulation and recording because of their poor electrochemical properties, high stiffness, and propensity to fail due to bending fatigue. Here we demonstrate neural recording and stimulation using carbon nanotube (CNT) fiber electrodes. In vitro characterization shows that the tissue contact impedance of CNT fibers is remarkably lower than that of state-of-the-art metal electrodes, making them suitable for recording single-neuron activity without additional surface treatments. In vivo chronic studies in parkinsonian rodents show that CNT fiber microelectrodes stimulate neurons as effectively as metal electrodes with 10 times larger surface area, while eliciting a significantly reduced inflammatory response. The same CNT fiber microelectrodes can record neural activity for weeks, paving the way for the development of novel multifunctional and dynamic neural interfaces with long-term stability.

  7. Microprocessor interfacing

    CERN Document Server

    Vears, R E

    2014-01-01

    Microprocessor Interfacing provides the coverage of the Business and Technician Education Council level NIII unit in Microprocessor Interfacing (syllabus U86/335). Composed of seven chapters, the book explains the foundation in microprocessor interfacing techniques in hardware and software that can be used for problem identification and solving. The book focuses on the 6502, Z80, and 6800/02 microprocessor families. The technique starts with signal conditioning, filtering, and cleaning before the signal can be processed. The signal conversion, from analog to digital or vice versa, is expl

  8. Rapid Prototyping Human Interfaces Using Stretchable Strain Sensor

    Directory of Open Access Journals (Sweden)

    Tokiya Yamaji

    2017-01-01

    Full Text Available In the modern society with a variety of information electronic devices, human interfaces increase their importance in a boundary of a human and a device. In general, the human is required to get used to the device. Even if the device is designed as a universal device or a high-usability device, the device is not suitable for all users. The usability of the device depends on the individual user. Therefore, personalized and customized human interfaces are effective for the user. To create customized interfaces, we propose rapid prototyping human interfaces using stretchable strain sensors. The human interfaces comprise parts formed by a three-dimensional printer and the four strain sensors. The three-dimensional printer easily makes customized human interfaces. The outputs of the interface are calculated based on the sensor’s lengths. Experiments evaluate three human interfaces: a sheet-shaped interface, a sliding lever interface, and a tilting lever interface. We confirm that the three human interfaces obtain input operations with a high accuracy.

  9. Manufacturing Interfaces

    NARCIS (Netherlands)

    van Houten, Frederikus J.A.M.

    1992-01-01

    The paper identifies the changing needs and requirements with respect to the interfacing of manufacturing functions. It considers the manufacturing system, its components and their relationships from the technological and logistic point of view, against the background of concurrent engineering.

  10. Nanoelectronics meets biology: from new nanoscale devices for live-cell recording to 3D innervated tissues.

    Science.gov (United States)

    Duan, Xiaojie; Lieber, Charles M

    2013-10-01

    High spatiotemporal resolution interfaces between electrical sensors and biological systems, from single live cells to tissues, is crucial for many areas, including fundamental biophysical studies as well as medical monitoring and intervention. Herein, we summarize recent progress in the development and application of novel nanoscale devices for intracellular electrical recording of action potentials and the effort of merging electronic and biological systems seamlessly in three dimensions by using macroporous nanoelectronic scaffolds. The uniqueness of these nanoscale devices for minimally invasive, large-scale, high spatial resolution, and three-dimensional neural activity mapping are highlighted. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. EDITORIAL: Why we need a new journal in neural engineering

    Science.gov (United States)

    Durand, Dominique M.

    2004-03-01

    The field of neural engineering crystallizes for many engineers and scientists an area of research at the interface between neuroscience and engineering. For the last 15 years or so, the discipline of neural engineering (neuroengineering) has slowly appeared at conferences as a theme or track. The first conference devoted entirely to this area was the 1st International IEEE EMBS Conference on Neural Engineering which took place in Capri, Italy in 2003. Understanding how the brain works is considered the ultimate frontier and challenge in science. The complexity of the brain is so great that understanding even the most basic functions will require that we fully exploit all the tools currently at our disposal in science and engineering and simultaneously develop new methods of analysis. While neuroscientists and engineers from varied fields such as brain anatomy, neural development and electrophysiology have made great strides in the analysis of this complex organ, there remains a great deal yet to be uncovered. The potential for applications and remedies deriving from scientific discoveries and breakthroughs is extremely high. As a result of the growing availability of micromachining technology, research into neurotechnology has grown relatively rapidly in recent years and appears to be approaching a critical mass. For example, by understanding how neuronal circuits process and store information, we could design computers with capabilities beyond current limits. By understanding how neurons develop and grow, we could develop new technologies for spinal cord repair or central nervous system repair following neurological disorders. Moreover, discoveries related to higher-level cognitive function and consciousness could have a profound influence on how humans make sense of their surroundings and interact with each other. The ability to successfully interface the brain with external electronics would have enormous implications for our society and facilitate a

  12. Annealing effect on donor-acceptor interface and its impact on the performance of organic photovoltaic devices based on PSiF-DBT copolymer and C{sub 60}

    Energy Technology Data Exchange (ETDEWEB)

    Marchiori, Cleber F. N.; Yamamoto, Natasha A. D.; Koehler, Marlus; Roman, Lucimara S. [Department of Physics, Federal University of Paraná, P.O. Box 19044, 81531-990 Curitiba, Paraná (Brazil); Matos, Carolina F.; Zarbin, Aldo J. G. [Department of Chemistry, Federal University of Paraná, P.O. Box 19081, 81531-990 Curitiba, Paraná (Brazil); Kujala, Jiri; Tuomisto, Filip [Department of Applied Physics, Aalto University School of Science, P.O. Box 14100, FI-00076 Aalto (Finland); Macedo, Andréia G. [Department of Physics, Technological Federal University of Paraná, Curitiba 80230-901 (Brazil)

    2015-03-30

    In this work, poly[2,7-(9,9-bis(2-ethylhexyl)-dibenzosilole)-alt-4,7-bis(thiophen-2-yl) benzo-2,1,3-thiadiazole] (PSiF-DBT) was used as active layer in bilayer solar cell with C{sub 60} as electron acceptor. As cast devices already show reasonable power conversion efficiency (PCE) that increases to 4% upon annealing at 100 °C. Space charge limited measurements of the hole mobility (μ) in PSiF-DBT give μ ∼ 1.0 × 10{sup −4} cm{sup 2}/(V s) which does not depend on the temperature of the annealing treatment. Moreover, positron annihilation spectroscopy experiments revealed that PSiF-DBT films are well stacked even without the thermal treatment. The variations in the transport of holes upon annealing are then small. As a consequence, the PCE rise was mainly induced by the increase of the polymer surface roughness that leads to a more effective interface for exciton dissociation at the PSiF-DBT/fullerene heterojunction.

  13. Optoelectronics Interfaces for Power Converters

    Directory of Open Access Journals (Sweden)

    Ovidiu Neamtu

    2009-05-01

    Full Text Available The most important issue interface is galvanicseparation between the signal part and the power board.Standards in the field have increased continuouslyelectro-security requirements on the rigidity of thedielectric and insulation resistance. Recommendations forclassical solutions require the use of galvanic separationoptoelectronics devices. Interfacing with a PC or DSP -controller is a target of interposition optical signals viathe power hardware commands.

  14. An Artificial Neural Network Based Robot Controller that Uses Rat’s Brain Signals

    Directory of Open Access Journals (Sweden)

    Marsel Mano

    2013-04-01

    Full Text Available Brain machine interface (BMI has been proposed as a novel technique to control prosthetic devices aimed at restoring motor functions in paralyzed patients. In this paper, we propose a neural network based controller that maps rat’s brain signals and transforms them into robot movement. First, the rat is trained to move the robot by pressing the right and left lever in order to get food. Next, we collect brain signals with four implanted electrodes, two in the motor cortex and two in the somatosensory cortex area. The collected data are used to train and evaluate different artificial neural controllers. Trained neural controllers are employed online to map brain signals and transform them into robot motion. Offline and online classification results of rat’s brain signals show that the Radial Basis Function Neural Networks (RBFNN outperforms other neural networks. In addition, online robot control results show that even with a limited number of electrodes, the robot motion generated by RBFNN matched the motion generated by the left and right lever position.

  15. [Brain-machine interface--current status and future prospects].

    Science.gov (United States)

    Ushiba, Junichi

    2010-02-01

    Recent advances in brain activity analysis and computational algorithms have enabled people with severe motor disorders to control external devices via brain activity. Brain-machine interface (BMI)/brain-computer interface has gained importance as the ultimate strategy for functional compensation because it improves impaired neuromuscular systems. Invasive BMI performed using needle arrays can best control robotic arms or computer cursors because it records neural activity in the primary motor cortex in detail. The extensive and validated physiological background of recorded signals enables researchers to develop highly accurate BMI systems with needle electrodes. Less invasive neural recording with an electrocorticogram (ECoG)-electrode array provides good temporal and spatial information for use in prosthetic control. ECoG electrodes have wide clinical applications in pain control and epilepsy; therefore, techniques for electrode implantation are well established compared to those for needle arrays. These electrodes may find wide clinical applications if their accuracy level reaches that suitable for practical use. Noninvasive BMI involving neural recording by electroencephalography (EEG) is the most widely used technique because of a convenient experimental setup, although it provides a limited range of decodable motor outputs. In EEG, arc-shaped mu rhythms of 8-12 Hz appear around the sensorimotor area in the resting state and diminish in amplitude during motor imagery. Thus, the mu rhythm amplitude may correlate with cortical excitability of the sensorimotor area, and EEG-BMI may be useful in the neurorehabilitation of patients with stroke-induced hemiplegia. Research on BMI as a therapeutic tool though emergent, may widen the scope of conventional BMI.

  16. Toward more versatile and intuitive cortical brain machine interfaces

    Science.gov (United States)

    Andersen, Richard A.; Kellis, Spencer; Klaes, Christian; Aflalo, Tyson

    2015-01-01

    Brain machine interfaces have great potential in neuroprosthetic applications to assist patients with brain injury and neurodegenerative diseases. One type of BMI is a cortical motor prosthetic which is used to assist paralyzed subjects. Motor prosthetics to date have typically used the motor cortex as a source of neural signals for controlling external devices. The review will focus on several new topics in the arena of cortical prosthetics. These include using 1) recordings from cortical areas outside motor cortex; 2) local field potentials (LFPs) as a source of recorded signals; 3) somatosensory feedback for more dexterous control of robotics; and 4) new decoding methods that work in concert to form an ecology of decode algorithms. These new advances hold promise in greatly accelerating the applicability and ease of operation of motor prosthetics. PMID:25247368

  17. Intracortical Brain-Machine Interfaces Advance Sensorimotor Neuroscience.

    Science.gov (United States)

    Schroeder, Karen E; Chestek, Cynthia A

    2016-01-01

    Brain-machine interfaces (BMIs) decode brain activity to control external devices. Over the past two decades, the BMI community has grown tremendously and reached some impressive milestones, including the first human clinical trials using chronically implanted intracortical electrodes. It has also contributed experimental paradigms and important findings to basic neuroscience. In this review, we discuss neuroscience achievements stemming from BMI research, specifically that based upon upper limb prosthetic control with intracortical microelectrodes. We will focus on three main areas: first, we discuss progress in neural coding of reaches in motor cortex, describing recent results linking high dimensional representations of cortical activity to muscle activation. Next, we describe recent findings on learning and plasticity in motor cortex on various time scales. Finally, we discuss how bidirectional BMIs have led to better understanding of somatosensation in and related to motor cortex.

  18. Biomimetic approaches to bionic touch through a peripheral nerve interface.

    Science.gov (United States)

    Saal, Hannes P; Bensmaia, Sliman J

    2015-12-01

    State-of-the-art prosthetic hands nearly match the dexterity of the human hand, and sophisticated approaches have been developed to control them intuitively. However, grasping and dexterously manipulating objects relies heavily on the sense of touch, without which we would struggle to perform even the most basic activities of daily living. Despite the importance of touch, not only in motor control but also in affective communication and embodiment, the restoration of touch through bionic hands is still in its infancy, a shortcoming that severely limits their effectiveness. Here, we focus on approaches to restore the sense of touch through an electrical interface with the peripheral nerve. First, we describe devices that can be chronically implanted in the nerve to electrically activate nerve fibers. Second, we discuss how these interfaces have been used to convey basic somatosensory feedback. Third, we review what is known about how the somatosensory nerve encodes information about grasped objects in intact limbs and discuss how these natural neural codes can be exploited to convey artificial tactile feedback. Finally, we offer a blueprint for how these codes could be implemented in a neuroprosthetic device to deliver rich, natural, and versatile tactile sensations. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. Physiological properties of brain-machine interface input signals.

    Science.gov (United States)

    Slutzky, Marc W; Flint, Robert D

    2017-08-01

    Brain-machine interfaces (BMIs), also called brain-computer interfaces (BCIs), decode neural signals and use them to control some type of external device. Despite many experimental successes and terrific demonstrations in animals and humans, a high-performance, clinically viable device has not yet been developed for widespread usage. There are many factors that impact clinical viability and BMI performance. Arguably, the first of these is the selection of brain signals used to control BMIs. In this review, we summarize the physiological characteristics and performance-including movement-related information, longevity, and stability-of multiple types of input signals that have been used in invasive BMIs to date. These include intracortical spikes as well as field potentials obtained inside the cortex, at the surface of the cortex (electrocorticography), and at the surface of the dura mater (epidural signals). We also discuss the potential for future enhancements in input signal performance, both by improving hardware and by leveraging the knowledge of the physiological characteristics of these signals to improve decoding and stability. Copyright © 2017 the American Physiological Society.

  20. Intelligent virtual interfaces for telerobotics

    Science.gov (United States)

    Grinstein, Georges G.; Maybury, Mark T.; Mitchell, Richard B.

    1992-11-01

    One promise of telerobotics is the ability to interact in environments that are distant (e.g., deep sea or deep space), dangerous (e.g., nuclear, chemical, or biological environments), or inaccessible by humans for political or legal reasons. A key component to such interactions are sophisticated human-computer interfaces that can replicate sufficient information about a local environment to permit remote navigation and manipulation. This environment replication can, in part, be provided by technologies such as virtual reality. In addition, however, telerobotic interfaces may need to enhance human-machine interaction to assist users in task performance, for example, governing motion or manipulation controls to avoid obstacles or to restrict interaction with certain objects (e.g., avoiding contact with a live mine or a deep sea treasure). Thus, effective interactions within remote environments require intelligent virtual interfaces to telerobotic devices. In part to address this problem, MITRE is investigating virtual reality architectures that will enable enhanced interaction within virtual environments. Key components to intelligent virtual interfaces include spoken language processing, gesture recognition algorithms, and more generally, task recognition. In addition, these interfaces will eventually have to take into account properties of the user, the task, and discourse context to be more adaptive to the current situation at hand. While our work has not yet investigated the connection of virtual interfaces to external robotic devices, we have begun developing the key components for intelligent virtual interfaces for information and training systems.

  1. Hands in space: gesture interaction with augmented-reality interfaces.

    Science.gov (United States)

    Billinghurst, Mark; Piumsomboon, Tham; Huidong Bai

    2014-01-01

    Researchers at the Human Interface Technology Laboratory New Zealand (HIT Lab NZ) are investigating free-hand gestures for natural interaction with augmented-reality interfaces. They've applied the results to systems for desktop computers and mobile devices.

  2. Designing Interfaces

    CERN Document Server

    Tidwell, Jenifer

    2010-01-01

    Despite all of the UI toolkits available today, it's still not easy to design good application interfaces. This bestselling book is one of the few reliable sources to help you navigate through the maze of design options. By capturing UI best practices and reusable ideas as design patterns, Designing Interfaces provides solutions to common design problems that you can tailor to the situation at hand. This updated edition includes patterns for mobile apps and social media, as well as web applications and desktop software. Each pattern contains full-color examples and practical design advice th

  3. A bidirectional brain-machine interface featuring a neuromorphic hardware decoder

    Directory of Open Access Journals (Sweden)

    Fabio Boi

    2016-12-01

    Full Text Available Bidirectional brain-machine interfaces (BMIs establish a two-way direct communication link4 between the brain and the external world. A decoder translates recorded neural activity into motor5 commands and an encoder delivers sensory information collected from the environment directly6 to the brain creating a closed-loop system. These two modules are typically integrated in bulky7 external devices. However, the clinical support of patients with severe motor and sensory deficits8 requires compact, low-power, and fully implantable systems that can decode neural signals to9 control external devices. As a first step toward this goal, we developed a modular bidirectional BMI10 setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented11 a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits.12 On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn13 to decode neural signals recorded from the brain into motor outputs controlling the movements14 of an external device. The modularity of the BMI allowed us to tune the individual components15 of the setup without modifying the whole system. In this paper we present the features of16 this modular BMI, and describe how we configured the network of spiking neuron circuits to17 implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm18 that connects bidirectionally the brain of an anesthetized rat with an external object. We show that19 the chip learned the decoding task correctly, allowing the interfaced brain to control the object’s20 trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is21 mature enough for the development of BMI modules that are sufficiently low-power and compact,22 while being highly computationally powerful and adaptive.

  4. A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

    Science.gov (United States)

    Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

    2016-01-01

    Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

  5. Testing Interfaces

    DEFF Research Database (Denmark)

    Holbøll, Joachim T.; Henriksen, Mogens; Nilson, Jesper K.

    1999-01-01

    The wide use of solid insulating materials combinations in combinations has introduced problems in the interfaces between components. The most common insulating materials are cross-linked polyethylene (XLPE), silicone rubber (SIR) and ethylene-propylene rubbers (EPR). Assemblies of these materials...

  6. Surface and interface effects in VLSI

    CERN Document Server

    Einspruch, Norman G

    1985-01-01

    VLSI Electronics Microstructure Science, Volume 10: Surface and Interface Effects in VLSI provides the advances made in the science of semiconductor surface and interface as they relate to electronics. This volume aims to provide a better understanding and control of surface and interface related properties. The book begins with an introductory chapter on the intimate link between interfaces and devices. The book is then divided into two parts. The first part covers the chemical and geometric structures of prototypical VLSI interfaces. Subjects detailed include, the technologically most import

  7. Parallel Approach for Time Series Analysis with General Regression Neural Networks

    Directory of Open Access Journals (Sweden)

    J.C. Cuevas-Tello

    2012-04-01

    Full Text Available The accuracy on time delay estimation given pairs of irregularly sampled time series is of great relevance in astrophysics. However the computational time is also important because the study of large data sets is needed. Besides introducing a new approach for time delay estimation, this paper presents a parallel approach to obtain a fast algorithm for time delay estimation. The neural network architecture that we use is general Regression Neural Network (GRNN. For the parallel approach, we use Message Passing Interface (MPI on a beowulf-type cluster and on a Cray supercomputer and we also use the Compute Unified Device Architecture (CUDA™ language on Graphics Processing Units (GPUs. We demonstrate that, with our approach, fast algorithms can be obtained for time delay estimation on large data sets with the same accuracy as state-of-the-art methods.

  8. Keeping Disability in Mind: A Case Study in Implantable Brain-Computer Interface Research.

    Science.gov (United States)

    Sullivan, Laura Specker; Klein, Eran; Brown, Tim; Sample, Matthew; Pham, Michelle; Tubig, Paul; Folland, Raney; Truitt, Anjali; Goering, Sara

    2017-06-22

    Brain-Computer Interface (BCI) research is an interdisciplinary area of study within Neural Engineering. Recent interest in end-user perspectives has led to an intersection with user-centered design (UCD). The goal of user-centered design is to reduce the translational gap between researchers and potential end users. However, while qualitative studies have been conducted with end users of BCI technology, little is known about individual BCI researchers' experience with and attitudes towards UCD. Given the scientific, financial, and ethical imperatives of UCD, we sought to gain a better understanding of practical and principled considerations for researchers who engage with end users. We conducted a qualitative interview case study with neural engineering researchers at a center dedicated to the creation of BCIs. Our analysis generated five themes common across interviews. The thematic analysis shows that participants identify multiple beneficiaries of their work, including other researchers, clinicians working with devices, device end users, and families and caregivers of device users. Participants value experience with device end users, and personal experience is the most meaningful type of interaction. They welcome (or even encourage) end-user input, but are skeptical of limited focus groups and case studies. They also recognize a tension between creating sophisticated devices and developing technology that will meet user needs. Finally, interviewees espouse functional, assistive goals for their technology, but describe uncertainty in what degree of function is "good enough" for individual end users. Based on these results, we offer preliminary recommendations for conducting future UCD studies in BCI and neural engineering.

  9. Investigation of sputtered iridium oxide as a stimulating/sensing material for neural prostheses

    Science.gov (United States)

    Negi, Sandeep

    Neural interface devices are developed for neuroscience and neuroprosthetics applications to record and stimulate nerve signals. Microelectrodes represent the direct interface between the biological tissue and the electronic system in neural prostheses that serve to record electrical signals from the nerves to obtain information from the natural sensors of the body or the motor fibers of the muscles. Also, the microelectrodes can inject charge into the targeted tissue to functionally excite nerves and muscles by electrical stimulation. Overall, the neural microelectrodes have to measure electrical potentials and have to exchange charge between the solid state of the electrode and the fluid state of the electrolyte in the body. Therefore, the interface between the microelectrode and biological fluid is a critical factor for the performance of the neural device. The interface properties depend mainly on the physical, electrical and chemical property of the electrode material. Even though a large selection of electrode materials has been tested for this purpose, to date no electrode material or coating process presented in scientific literature has been identified or qualified for long-term stimulation and recording neural signals. In this work, sputtered iridium oxide film (SIROF) was investigated as a potential electrode material. SIROF was deposited on the microelectrodes by reactive pulsed DC sputtering. The deposition parameters and corresponding film properties were examined and correlated with the stimulation and recording characteristics. Furthermore, for chronic applications, the stability of SIROF was investigated and stimulation protocol was determined for damage threshold of the film. The sputtering pressure was varied to obtain SIROF with desired properties. The SIROF properties were optimized based on its ability to inject charge in the tissue and its mechanical strength. The electrochemical characterization of SIROF was studied by electrochemical

  10. Memristor-based neural networks

    Science.gov (United States)

    Thomas, Andy

    2013-03-01

    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them.

  11. Brain-computer interfaces increase whole-brain signal to noise.

    Science.gov (United States)

    Papageorgiou, T Dorina; Lisinski, Jonathan M; McHenry, Monica A; White, Jason P; LaConte, Stephen M

    2013-08-13

    Brain-computer interfaces (BCIs) can convert mental states into signals to drive real-world devices, but it is not known if a given covert task is the same when performed with and without BCI-based control. Using a BCI likely involves additional cognitive processes, such as multitasking, attention, and conflict monitoring. In addition, it is challenging to measure the quality of covert task performance. We used whole-brain classifier-based real-time functional MRI to address these issues, because the method provides both classifier-based maps to examine the neural requirements of BCI and classification accuracy to quantify the quality of task performance. Subjects performed a covert counting task at fast and slow rates to control a visual interface. Compared with the same task when viewing but not controlling the interface, we observed that being in control of a BCI improved task classification of fast and slow counting states. Additional BCI control increased subjects' whole-brain signal-to-noise ratio compared with the absence of control. The neural pattern for control consisted of a positive network comprised of dorsal parietal and frontal regions and the anterior insula of the right hemisphere as well as an expansive negative network of regions. These findings suggest that real-time functional MRI can serve as a platform for exploring information processing and frontoparietal and insula network-based regulation of whole-brain task signal-to-noise ratio.

  12. EDITORIAL: Commercial opportunities for neural engineers

    Science.gov (United States)

    Cavuoto, James

    2008-03-01

    Research and academic professionals in neural engineering know well the promise the field offers for advancing our understanding of basic neuroscience and devising new therapies for treating neurological diseases and disorders. But there is also considerable commercial opportunity for new start-up companies in several areas of neural engineering. The neurotechnology industry, which includes firms that manufacture neuromodulation devices, neural prostheses, neurorehabilitation systems, and neurosensing devices, is forecast to grow to grow from 3.6 billion this year to 8.8 billion in 2012, according to a recently published market research study from Neurotech Reports. In recent years, there have been several successful spinoffs of neurotechnology startup firms that originated with research at universities and clinical institutions. In many cases, the academic researchers who invented the new technology or product innovation have stayed on with their startup firms after receiving funding from venture capital firms, or after going public. Among the most successful neurotechnology industry spinoffs in recent years were: Cyberkinetics Inc., Foxborough, MA, a manufacturer of brain-computer interface devices based on research at Brown University. John Donoghue, a professor and chairman of the department of neuroscience at Brown University and executive director of the brain science program at Brown, founded the company in 2001 and remains on board as the chief scientific officer. Synapse Biomedical, Inc., Oberlin, OH, a manufacturer of diaphragm pacing systems, based on research at Case Western Reserve University. Raymond Onders, director of minimal invasive surgery and associate professor at University Hospital Case Medical Center in Cleveland, was the primary researcher. He was helped by J. Thomas Mortimer, professor emeritus of biomedical engineering at Case, and it was Mortimer who came up with the name NeuRx for the device. Onders performed his first surgical implant

  13. SNE Industrial Fieldbus Interface

    Science.gov (United States)

    Lucena, Angel; Raines, Matthew; Oostdyk, Rebecca; Mata, Carlos

    2011-01-01

    Programmable logic controllers (PLCs) have very limited diagnostic and no prognostic capabilities, while current smart sensor designs do not have the capability to communicate over Fieldbus networks. The aim is to interface smart sensors with PLCs so that health and status information, such as failure mode identification and measurement tolerance, can be communicated via an industrial Fieldbus such as ControlNet. The SNE Industrial Fieldbus Interface (SIFI) is an embedded device that acts as a communication module in a networked smart sensor. The purpose is to enable a smart sensor to communicate health and status information to other devices, such as PLCs, via an industrial Fieldbus networking protocol. The SNE (Smart Network Element) is attached to a commercial off-the-shelf Any bus-S interface module through the SIFI. Numerous Anybus-S modules are available, each one designed to interface with a specific Fieldbus. Development of the SIFI focused on communications using the ControlNet protocol, but any of the Anybus-S modules can be used. The SIFI communicates with the Any-bus module via a data buffer and mailbox system on the Anybus module, and supplies power to the module. The Anybus module transmits and receives data on the Fieldbus using the proper protocol. The SIFI is intended to be connected to other existing SNE modules in order to monitor the health and status of a transducer. The SIFI can also monitor aspects of its own health using an onboard watchdog timer and voltage monitors. The SIFI also has the hardware to drive a touchscreen LCD (liquid crystal display) unit for manual configuration and status monitoring.

  14. Metal semiconductor contacts and devices

    CERN Document Server

    Cohen, Simon S; Einspruch, Norman G

    1986-01-01

    VLSI Electronics Microstructure Science, Volume 13: Metal-Semiconductor Contacts and Devices presents the physics, technology, and applications of metal-semiconductor barriers in digital integrated circuits. The emphasis is placed on the interplay among the theory, processing, and characterization techniques in the development of practical metal-semiconductor contacts and devices.This volume contains chapters that are devoted to the discussion of the physics of metal-semiconductor interfaces and its basic phenomena; fabrication procedures; and interface characterization techniques, particularl

  15. Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array

    Science.gov (United States)

    Simeral, J. D.; Kim, S.-P.; Black, M. J.; Donoghue, J. P.; Hochberg, L. R.

    2011-04-01

    The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess the feasibility of using neural activity obtained from a small-scale, chronically implanted, intracortical microelectrode array to provide control signals for a neural prosthesis system. Critical questions include how long implanted microelectrodes will record useful neural signals, how reliably those signals can be acquired and decoded, and how effectively they can be used to control various assistive technologies such as computers and robotic assistive devices, or to enable functional electrical stimulation of paralyzed muscles. Here we examined these questions by assessing neural cursor control and BrainGate system characteristics on five consecutive days 1000 days after implant of a 4 × 4 mm array of 100 microelectrodes in the motor cortex of a human with longstanding tetraplegia subsequent to a brainstem stroke. On each of five prospectively-selected days we performed time-amplitude sorting of neuronal spiking activity, trained a population-based Kalman velocity decoding filter combined with a linear discriminant click state classifier, and then assessed closed-loop point-and-click cursor control. The participant performed both an eight-target center-out task and a random target Fitts metric task which was adapted from a human-computer interaction ISO standard used to quantify performance of computer input devices. The neural interface system was further characterized by daily measurement of electrode impedances, unit waveforms and local field potentials. Across the five days, spiking signals were obtained from 41 of 96 electrodes and were successfully decoded to provide neural cursor point-and-click control with a mean task performance of 91.3% ± 0.1% (mean ± s.d.) correct target acquisition. Results across five consecutive days demonstrate that a neural interface system based on an intracortical microelectrode array can provide repeatable, accurate point

  16. Emotional Brain-Computer Interfaces

    NARCIS (Netherlands)

    Garcia Molina, Gary; Tsoneva, Tsvetomira; Cohn, J.; Nijholt, Antinus; Pantic, Maja

    2009-01-01

    Research in Brain-computer interface (BCI) has significantly increased during the last few years. In addition to their initial role as assisting devices for the physically challenged, BCIs are now proposed for a wider range of applications. As in any HCI application, BCIs can also benefit from

  17. Usability of Nomadic User Interfaces

    NARCIS (Netherlands)

    Dees, W.

    2011-01-01

    During the last decade, a number of research activities have been performed to enable user interfaces and the underlying user activities to be migrated from one device to another. We call this “Nomadic User Interfaces”. The primary goal of these research activities has been to develop the

  18. Emotional Brain-Computer Interfaces

    NARCIS (Netherlands)

    Garcia Molina, G.; Nijholt, A.; Nijholt, Antinus; Tsoneva, T.; Heylen, Dirk K.J.; Heylen, D.K.J.

    2013-01-01

    Research in brain-computer interface (BCI) has significantly increased during the last few years. Additionally to their initial role as assisting devices for the physically challenged, BCIs are now proposed for a wider range of applications. As any human-machine interaction system, BCIs can benefit

  19. Robust Brain-Computer Interfaces

    NARCIS (Netherlands)

    Reuderink, B.

    2011-01-01

    A brain-computer interface (BCI) enables direct communication from the brain to devices, bypassing the traditional pathway of peripheral nerves and muscles. Current BCIs aimed at patients require that the user invests weeks, or even months, to learn the skill to intentionally modify their brain

  20. Neural network based system for equipment surveillance

    Science.gov (United States)

    Vilim, R.B.; Gross, K.C.; Wegerich, S.W.

    1998-04-28

    A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

  1. Functional network reorganization during learning in a brain-computer interface paradigm.

    Science.gov (United States)

    Jarosiewicz, Beata; Chase, Steven M; Fraser, George W; Velliste, Meel; Kass, Robert E; Schwartz, Andrew B

    2008-12-09

    Efforts to study the neural correlates of learning are hampered by the size of the network in which learning occurs. To understand the importance of learning-related changes in a network of neurons, it is necessary to understand how the network acts as a whole to generate behavior. Here we introduce a paradigm in which the output of a cortical network can be perturbed directly and the neural basis of the compensatory changes studied in detail. Using a brain-computer interface, dozens of simultaneously recorded neurons in the motor cortex of awake, behaving monkeys are used to control the movement of a cursor in a three-dimensional virtual-reality environment. This device creates a precise, well-defined mapping between the firing of the recorded neurons and an expressed behavior (cursor movement). In a series of experiments, we force the animal to relearn the association between neural firing and cursor movement in a subset of neurons and assess how the network changes to compensate. We find that changes in neural activity reflect not only an alteration of behavioral strategy but also the relative contributions of individual neurons to the population error signal.

  2. Recasting brain-machine interface design from a physical control system perspective.

    Science.gov (United States)

    Zhang, Yin; Chase, Steven M

    2015-10-01

    With the goal of improving the quality of life for people suffering from various motor control disorders, brain-machine interfaces provide direct neural control of prosthetic devices by translating neural signals into control signals. These systems act by reading motor intent signals directly from the brain and using them to control, for example, the movement of a cursor on a computer screen. Over the past two decades, much attention has been devoted to the decoding problem: how should recorded neural activity be translated into the movement of the cursor? Most approaches have focused on this problem from an estimation standpoint, i.e., decoders are designed to return the best estimate of motor intent possible, under various sets of assumptions about how the recorded neural signals represent motor intent. Here we recast the decoder design problem from a physical control system perspective, and investigate how various classes of decoders lead to different types of physical systems for the subject to control. This framework leads to new interpretations of why certain types of decoders have been shown to perform better than others. These results have implications for understanding how motor neurons are recruited to perform various tasks, and may lend insight into the brain's ability to conceptualize artificial systems.

  3. PinBus Interface Design

    Energy Technology Data Exchange (ETDEWEB)

    Hammerstrom, Donald J.; Adgerson, Jewel D.; Sastry, Chellury; Pratt, Richard M.; Pratt, Robert G.

    2009-12-30

    On behalf of the U.S. Department of Energy, PNNL has explored and expanded upon a simple control interface that might have merit for the inexpensive communication of smart grid operational objectives (demand response, for example) to small electric end-use devices and appliances. The approach relies on bi-directional communication via the electrical voltage states of from one to eight shared interconnection pins. The name PinBus has been suggested and adopted for the proposed interface protocol. The protocol is defined through the presentation of state diagrams and the pins’ functional definitions. Both simulations and laboratory demonstrations are being conducted to demonstrate the elegance and power of the suggested approach. PinBus supports a very high degree of interoperability across its interfaces, allowing innumerable pairings of devices and communication protocols and supporting the practice of practically any smart grid use case.

  4. Interface learning

    DEFF Research Database (Denmark)

    Thorhauge, Sally

    2014-01-01

    "Interface learning - New goals for museum and upper secondary school collaboration" investigates and analyzes the learning that takes place when museums and upper secondary schools in Denmark work together in local partnerships to develop and carry out school-related, museum-based coursework...... for students. The research focuses on the learning that the students experience in the interface of the two learning environments: The formal learning environment of the upper secondary school and the informal learning environment of the museum. Focus is also on the learning that the teachers and museum...... professionals experience as a result of their collaboration. The dissertation demonstrates how a given partnership’s collaboration affects the students’ learning experiences when they are doing the coursework. The dissertation presents findings that museum-school partnerships can use in order to develop...

  5. Hybridization at superconductor-semiconductor interfaces

    OpenAIRE

    Mikkelsen, August E. G.; Kotetes, Panagiotis; Krogstrup, Peter; Flensberg, Karsten

    2018-01-01

    Hybrid superconductor-semiconductor devices are currently one of the most promising platforms for realizing Majorana zero modes. We address the role of band bending and superconductor-semiconductor hybridization in such devices by analyzing a gated single Al-InAs interface using a self-consistent Schroedinger-Poisson approach. Our numerical analysis shows that the band bending leads to an interface quantum well, which localizes the charge in the system near the superconductor-semiconductor in...

  6. Surfaces and interfaces of electronic materials

    CERN Document Server

    Brillson, Leonard J

    2012-01-01

    An advanced level textbook covering geometric, chemical, and electronic structure of electronic materials, and their applications to devices based on semiconductor surfaces, metal-semiconductor interfaces, and semiconductor heterojunctions. Starting with the fundamentals of electrical measurements on semiconductor interfaces, it then describes the importance of controlling macroscopic electrical properties by atomic-scale techniques. Subsequent chapters present the wide range of surface and interface techniques available to characterize electronic, optical, chemical, and structural propertie

  7. MIB Galerkin method for elliptic interface problems.

    Science.gov (United States)

    Xia, Kelin; Zhan, Meng; Wei, Guo-Wei

    2014-12-15

    Material interfaces are omnipresent in the real-world structures and devices. Mathematical modeling of material interfaces often leads to elliptic partial differential equations (PDEs) with discontinuous coefficients and singular sources, which are commonly called elliptic interface problems. The development of high-order numerical schemes for elliptic interface problems has become a well defined field in applied and computational mathematics and attracted much attention in the past decades. Despite of significant advances, challenges remain in the construction of high-order schemes for nonsmooth interfaces, i.e., interfaces with geometric singularities, such as tips, cusps and sharp edges. The challenge of geometric singularities is amplified when they are associated with low solution regularities, e.g., tip-geometry effects in many fields. The present work introduces a matched interface and boundary (MIB) Galerkin method for solving two-dimensional (2D) elliptic PDEs with complex interfaces, geometric singularities and low solution regularities. The Cartesian grid based triangular elements are employed to avoid the time consuming mesh generation procedure. Consequently, the interface cuts through elements. To ensure the continuity of classic basis functions across the interface, two sets of overlapping elements, called MIB elements, are defined near the interface. As a result, differentiation can be computed near the interface as if there is no interface. Interpolation functions are constructed on MIB element spaces to smoothly extend function values across the interface. A set of lowest order interface jump conditions is enforced on the interface, which in turn, determines the interpolation functions. The performance of the proposed MIB Galerkin finite element method is validated by numerical experiments with a wide range of interface geometries, geometric singularities, low regularity solutions and grid resolutions. Extensive numerical studies confirm the

  8. Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system

    Directory of Open Access Journals (Sweden)

    Daniel Brüderle

    2009-06-01

    Full Text Available Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

  9. Establishing a Novel Modeling Tool: A Python-Based Interface for a Neuromorphic Hardware System

    Science.gov (United States)

    Brüderle, Daniel; Müller, Eric; Davison, Andrew; Muller, Eilif; Schemmel, Johannes; Meier, Karlheinz

    2008-01-01

    Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated. PMID:19562085

  10. ARACHNE: A neural-neuroglial network builder with remotely controlled parallel computing

    Science.gov (United States)

    Rusakov, Dmitri A.; Savtchenko, Leonid P.

    2017-01-01

    Creating and running realistic models of neural networks has hitherto been a task for computing professionals rather than experimental neuroscientists. This is mainly because such networks usually engage substantial computational resources, the handling of which requires specific programing skills. Here we put forward a newly developed simulation environment ARACHNE: it enables an investigator to build and explore cellular networks of arbitrary biophysical and architectural complexity using the logic of NEURON and a simple interface on a local computer or a mobile device. The interface can control, through the internet, an optimized computational kernel installed on a remote computer cluster. ARACHNE can combine neuronal (wired) and astroglial (extracellular volume-transmission driven) network types and adopt realistic cell models from the NEURON library. The program and documentation (current version) are available at GitHub repository https://github.com/LeonidSavtchenko/Arachne under the MIT License (MIT). PMID:28362877

  11. Design Patterns for User Interfaces on Mobile Equipment

    Science.gov (United States)

    Nilsson, Erik G.

    The objective of this tutorial is to enhance the participants’ skills in designing user interfaces for mobile equipment, including adaptive and context sensitive user interfaces and multimodal interaction. Through a combination of lectures and practical exercises, a collection of patterns addressing issues regarding designing user interfaces on mobile devices is presented. The patterns address typical challenges and opportunities when designing user interfaces that are to run on PDAs and SmartPhones - both challenges connected to characteristics of the equipment and connected to tasks to which designing suitable user interfaces is challenging. The tutorial is intended for user interface designer, systems developers, and project leaders that work with or plan to work on development of applications on mobile devices. The tutorial requires basic knowledge of user interface design in general, and basic understanding of challenges connected to designing user interfaces on mobile devices.

  12. Brain-machine interface (BMI) in paralysis.

    Science.gov (United States)

    Chaudhary, U; Birbaumer, N; Curado, M R

    2015-02-01

    Brain-machine interfaces (BMIs) use brain activity to control external devices, facilitating paralyzed patients to interact with the environment. In this review, we focus on the current advances of non-invasive BMIs for communication in patients with amyotrophic lateral sclerosis (ALS) and for restoration of motor impairment after severe stroke. BMI represents a promising strategy to establish communication with paralyzed ALS patients as it does not need muscle engagement for its use. Distinct techniques have been explored to assess brain neurophysiology to control BMI for patients' communication, especially electroencephalography (EEG) and more recently near-infrared spectroscopy (NIRS). Previous studies demonstrated successful communication with ALS patients using EEG-BMI when patients still showed residual eye control, but patients with complete paralysis were unable to communicate with this system. We recently introduced functional NIRS (fNIRS)-BMI for communication in ALS patients in the complete locked-in syndrome (i.e., when ALS patients are unable to engage any muscle), opening new doors for communication in ALS patients after complete paralysis. In addition to assisted communication, BMI is also being extensively studied for motor recovery after stroke. BMI for stroke motor recovery includes intensive BMI training linking brain activity related to patient's intention to move the paretic limb with the contingent sensory feedback of the paretic limb movement guided by assistive devices. BMI studies in this area are mainly focused on EEG- or magnetoencephalography (MEG)-BMI systems due to their high temporal resolution, which facilitates online contingency between intention to move and sensory feedback of the intended movement. EEG-BMI training was recently demonstrated in a controlled study to significantly improve motor performance in stroke patients with severe paresis. Neural basis for BMI-induced restoration of motor function and perspectives for future

  13. Polymers at Surfaces and Interfaces

    Science.gov (United States)

    Tsige, Mesfin

    2015-03-01

    Interfaces between solids, liquids, and gases play an important role in a wide range of practical applications and have been a subject of scientific interest since Poisson showed in 1831 that the order parameter of liquids near interfaces must deviate considerably from its bulk value. In particular, polymers at surfaces and interfaces have been a subject of extensive theoretical, experimental and computational studies for a long time due to their use in many diverse applications ranging from antifouling coatings to flexible electronic devices. Understanding the structure and thermodynamic properties of polymers at surfaces and interfaces is thus an area of fundamental and current technological interest. Although encouraging experimental progress has been made over the years in understanding the molecular structure of polymers in contact with various environments, selectively probing their structure and dynamics at surfaces and interfaces has been extremely difficult. Computer simulations, especially molecular dynamics (MD) simulations, have proven over the years to be an invaluable tool in providing molecular details at interfaces that are usually lacking in the experimental data. In this talk, I'll give an overview of some previous simulation efforts to understand the structure and dynamics of polymers at surfaces and buried interfaces. I will conclude by presenting our current and ongoing work on combining ab initio calculations and MD simulations with Sum Frequency Generation (SFG) Spectroscopy to study polymer surfaces. This approach demonstrates the future role of MD in surface science. Work supported by NSF (DMR0847580 and DMR1410290) and Petroleum Research Fund of the American Chemical Society.

  14. Emerging trends in neuro engineering and neural computation

    CERN Document Server

    Lee, Kendall; Garmestani, Hamid; Lim, Chee

    2017-01-01

    This book focuses on neuro-engineering and neural computing, a multi-disciplinary field of research attracting considerable attention from engineers, neuroscientists, microbiologists and material scientists. It explores a range of topics concerning the design and development of innovative neural and brain interfacing technologies, as well as novel information acquisition and processing algorithms to make sense of the acquired data. The book also highlights emerging trends and advances regarding the applications of neuro-engineering in real-world scenarios, such as neural prostheses, diagnosis of neural degenerative diseases, deep brain stimulation, biosensors, real neural network-inspired artificial neural networks (ANNs) and the predictive modeling of information flows in neuronal networks. The book is broadly divided into three main sections including: current trends in technological developments, neural computation techniques to make sense of the neural behavioral data, and application of these technologie...

  15. 'Interfaces' 4

    Directory of Open Access Journals (Sweden)

    Paolo Borsa

    2018-01-01

    Full Text Available Issue No. 4 is the first open issue of Interfaces: A Journal of Medieval European Literatures. It contains contributions by Henry Bainton (12th-century historiography, Lucie Doležalová (parabiblical texts and the canon, Máire Ní Mhaonaigh (Irish literary culture in Latin and Irish, Isabel Varillas Sánchez (legends of composition of canonical texts, Septuaginta, Wim Verbaal (letter collections, Bernard of Clairvaux, and Jonas Wellendorf (canons of skaldic poets in the 12th/13th century, preceded by a brief Introduction by the editors.

  16. Localized neurotransmitter release for use in a prototype retinal interface.

    Science.gov (United States)

    Peterman, Mark C; Bloom, David M; Lee, Christina; Bent, Stacey F; Marmor, Michael F; Blumenkranz, Mark S; Fishman, Harvey A

    2003-07-01

    Current neural prostheses use electricity as the mode of stimulation, yet information transfer in neural circuitry is primarily through chemical transmitters. To address this disparity, this study was conducted to devise a prototype interface for a retinal prosthetic based on localized chemical delivery. The goal was to determine whether fluidic delivery through microfabricated apertures could be used to stimulate at single-cell dimensions. A drug delivery system was microfabricated based on a 5- or 10- microm aperture in a 500-nm thick silicon nitride membrane to localize and limit transmitter release. The aperture overlies a microfluidic delivery channel in a silicone elastomer. To demonstrate the effectiveness of this transmitter-based prosthesis, rat pheochromocytoma cells (PC12 cell line) were grown on the surface of the device to test the precision of stimulation, using bradykinin as a stimulant and measuring fluorescence from the calcium indicator, fluo-4. The extent of stimulation could be controlled accurately by varying the concentration of stimulant, from a single cell adjacent to the aperture to a broad area of cells. The stimulation radius was as small as 10 microm, corresponding to stimulation volumes as small as 2 pL. The relationship between the extent of stimulation and concentration was linear. The demonstration of localized chemical stimulation of excitable cells illustrates the potential of this technology for retinal prostheses. Although this is only a proof of concept of neurotransmitter stimulation for a retinal prosthesis, it is a significant first step toward mimicking neurotransmitter release during synaptic transmission.

  17. QoE-Aware Device-to-Device Multimedia Communications

    Directory of Open Access Journals (Sweden)

    Liang ZHOU

    2015-08-01

    Full Text Available Multimedia services over mobile device-to-device (D2D networks has recently received considerable attention. In this scenario, each device is equipped with a cellular communication interface, as well as a D2D interface over a shared medium. In this work, we study the performance properties of the mobile D2D communications in the framework of user satisfaction, and develop a fully distributed QoE-aware multimedia communication scheme (QAMCS. Specifically, we translate the opportunistic multimedia communications issue into a stochastic optimization problem, which opens up a new degree of performance to exploit. Moreover, QAMCS is designed for a heterogeneous and dynamic environment, in which user demand, device mobility, and transmission fashion may vary across different devices and applications. Importantly, QAMCS is able to maximize the user satisfaction and only needs each device to implement its own scheme individually in the absence of a central controller.

  18. IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK FOR FACE RECOGNITION USING GABOR FEATURE EXTRACTION

    Directory of Open Access Journals (Sweden)

    Muthukannan K

    2013-11-01

    Full Text Available Face detection and recognition is the first step for many applications in various fields such as identification and is used as a key to enter into the various electronic devices, video surveillance, and human computer interface and image database management. This paper focuses on feature extraction in an image using Gabor filter and the extracted image feature vector is then given as an input to the neural network. The neural network is trained with the input data. The Gabor wavelet concentrates on the important components of the face including eye, mouth, nose, cheeks. The main requirement of this technique is the threshold, which gives privileged sensitivity. The threshold values are the feature vectors taken from the faces. These feature vectors are given into the feed forward neural network to train the network. Using the feed forward neural network as a classifier, the recognized and unrecognized faces are classified. This classifier attains a higher face deduction rate. By training more input vectors the system proves to be effective. The effectiveness of the proposed method is demonstrated by the experimental results.

  19. Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS

    Directory of Open Access Journals (Sweden)

    Christopher Bergmeir

    2012-01-01

    Full Text Available Neural networks are important standard machine learning procedures for classification and regression. We describe the R package RSNNS that provides a convenient interface to the popular Stuttgart Neural Network Simulator SNNS. The main features are (a encapsulation of the relevant SNNS parts in a C++ class, for sequential and parallel usage of different networks, (b accessibility of all of the SNNSalgorithmic functionality from R using a low-level interface, and (c a high-level interface for convenient, R-style usage of many standard neural network procedures. The package also includes functions for visualization and analysis of the models and the training procedures, as well as functions for data input/output from/to the original SNNSfile formats.

  20. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  1. Computer interfacing

    CERN Document Server

    Dixey, Graham

    1994-01-01

    This book explains how computers interact with the world around them and therefore how to make them a useful tool. Topics covered include descriptions of all the components that make up a computer, principles of data exchange, interaction with peripherals, serial communication, input devices, recording methods, computer-controlled motors, and printers.In an informative and straightforward manner, Graham Dixey describes how to turn what might seem an incomprehensible 'black box' PC into a powerful and enjoyable tool that can help you in all areas of your work and leisure. With plenty of handy

  2. Capillary zone electrophoresis-mass spectrometer interface

    Science.gov (United States)

    D`Silva, A.

    1996-08-06

    A device for providing equal electrical potential between two loci unconnected by solid or liquid electrical conductors is provided. The device comprises a first electrical conducting terminal, a second electrical conducting terminal connected to the first terminal by a rigid dielectric structure, and an electrically conducting gas contacting the first and second terminals. This device is particularly suitable for application in the electrospray ionization interface between a capillary zone electrophoresis apparatus and a mass spectrometer. 1 fig.

  3. Control of neural stem cell survival by electroactive polymer substrates.

    Directory of Open Access Journals (Sweden)

    Vanessa Lundin

    Full Text Available Stem cell function is regulated by intrinsic as well as microenvironmental factors, including chemical and mechanical signals. Conducting polymer-based cell culture substrates provide a powerful tool to control both chemical and physical stimuli sensed by stem cells. Here we show that polypyrrole (PPy, a commonly used conducting polymer, can be tailored to modulate survival and maintenance of rat fetal neural stem cells (NSCs. NSCs cultured on PPy substrates containing different counter ions, dodecylbenzenesulfonate (DBS, tosylate (TsO, perchlorate (ClO(4 and chloride (Cl, showed a distinct correlation between PPy counter ion and cell viability. Specifically, NSC viability was high on PPy(DBS but low on PPy containing TsO, ClO(4 and Cl. On PPy(DBS, NSC proliferation and differentiation was comparable to standard NSC culture on tissue culture polystyrene. Electrical reduction of PPy(DBS created a switch for neural stem cell viability, with widespread cell death upon polymer reduction. Coating the PPy(DBS films with a gel layer composed of a basement membrane matrix efficiently prevented loss of cell viability upon polymer reduction. Here we have defined conditions for the biocompatibility of PPy substrates with NSC culture, critical for the development of devices based on conducting polymers interfacing with NSCs.

  4. Hardware Acceleration of Adaptive Neural Algorithms.

    Energy Technology Data Exchange (ETDEWEB)

    James, Conrad D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-11-01

    As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - world conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.

  5. Adhesion testing device

    Science.gov (United States)

    LaPeyronnie, Glenn M. (Inventor); Huff, Charles M. (Inventor)

    2010-01-01

    The present invention provides a testing apparatus and method for testing the adhesion of a coating to a surface. The invention also includes an improved testing button or dolly for use with the testing apparatus and a self aligning button hook or dolly interface on the testing apparatus. According to preferred forms, the apparatus and method of the present invention are simple, portable, battery operated rugged, and inexpensive to manufacture and use, are readily adaptable to a wide variety of uses, and provide effective and accurate testing results. The device includes a linear actuator driven by an electric motor coupled to the actuator through a gearbox and a rotatable shaft. The electronics for the device are contained in the head section of the device. At the contact end of the device, is positioned a self aligning button hook, attached below the load cell located on the actuator shaft.

  6. Neural network signal understanding for instrumentation

    DEFF Research Database (Denmark)

    Pau, L. F.; Johansen, F. S.

    1990-01-01

    A report is presented on the use of neural signal interpretation theory and techniques for the purpose of classifying the shapes of a set of instrumentation signals, in order to calibrate devices, diagnose anomalies, generate tuning/settings, and interpret the measurement results. Neural signal...... understanding research is surveyed, and the selected implementation and its performance in terms of correct classification rates and robustness to noise are described. Formal results on neural net training time and sensitivity to weights are given. A theory for neural control using functional link nets is given......, and an explanation facility designed to help neural signal understanding is described. The results are compared to those obtained with a knowledge-based signal interpretation system using the same instrument and data...

  7. Neural networks with discontinuous/impact activations

    CERN Document Server

    Akhmet, Marat

    2014-01-01

    This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided. This book also: Explores questions related to the biological underpinning for models of neural networks\\ Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities Provides all necessary mathematical basics for application to the theory of neural networks Neural Networks with Discontinuous/Impact Activations is an ideal book for researchers and professionals in the field of engineering mathematics that have an interest in app...

  8. KNOWBOT; An adaptive data base interface

    Energy Technology Data Exchange (ETDEWEB)

    Heger, A.S.; Koen, B.U. (Texas Univ., Austin, TX (United States). Dept. of Mechanical Engineering)

    1991-02-01

    This paper reports on an adaptive interface KNOWBOT designed to solve some of the problems that face the users of large centralized data bases. The interface applies the neural network approach to information retrieval from a data base. The data base is a subset of the Nuclear Plant Reliability Data System. The interface KNOWBOT preempts an existing data base interface and works in conjunction with it. By design, KNOWBOT starts as a tabula rasa but acquires knowledge through its interactions with the user and the data base. The interface uses its gained knowledge to personalize the data base retrieval process and to induce new queries. The interface also forgets the information that is no longer needed by the user. These self-organizing features of the interface reduce the scope of the data base to the subsets that are highly relevant to the user needs. A proof-of-principal version of this interface has been implemented in Common LISP on a Texas Instruments Explorer I workstation. Experiments with KNOWBOT have been successful in demonstrating the robustness of the model especially with induction and self-organization. This paper describes the design of KNOWBOT and presents some of the experimental results.

  9. A 110-nW in-channel sigma-delta converter for large-scale neural recording implants.

    Science.gov (United States)

    Rezaei, M; Maghsoudloo, E; Sawan, M; Gosselin, B

    2016-08-01

    Advancement in wireless and microsystems technology have ushered in new devices that can directly interface with the central nervous system for stimulating and/or monitoring neural circuitry. In this paper, we present an ultra low-power sigma-delta analog-to-digital converter (ADC) intended for utilization into large-scale multi-channel neural recording implants. This proposed design, which provides a resolution of 9 bits using a one-bit oversampled ADC, presents several desirable features that allow for an in-channel ADC scheme, where one sigma-delta converter is provided for each channel, enabling development of scalable systems that can interface with different types of high-density neural microprobes. The proposed circuit, which have been fabricated in a TSMC 180-nm CMOS process, employs a first order noise shaping topology with a passive integrator and a low-supply voltage of 0.6 V to achieve ultra low-power consumption and small size. The proposed ADC clearly outperforms other designs with a power consumption as low as 110 nW for a precision of 9 bits (11-fJ per conversion), a silicon area of only 82 μm × 84 μm and one of the best reported figure of merit among recently published data converters utilized in similar applications.

  10. Performance sustaining intracortical neural prostheses

    Science.gov (United States)

    Nuyujukian, Paul; Kao, Jonathan C.; Fan, Joline M.; Stavisky, Sergey D.; Ryu, Stephen I.; Shenoy, Krishna V.

    2014-12-01

    Objective. Neural prostheses, or brain-machine interfaces, aim to restore efficient communication and movement ability to those suffering from paralysis. A major challenge these systems face is robust performance, particularly with aging signal sources. The aim in this study was to develop a neural prosthesis that could sustain high performance in spite of signal instability while still minimizing retraining time. Approach. We trained two rhesus macaques implanted with intracortical microelectrode arrays 1-4 years prior to this study to acquire targets with a neurally-controlled cursor. We measured their performance via achieved bitrate (bits per second, bps). This task was repeated over contiguous days to evaluate the sustained performance across time. Main results. We found that in the monkey with a younger (i.e., two year old) implant and better signal quality, a fixed decoder could sustain performance for a month at a rate of 4 bps, the highest achieved communication rate reported to date. This fixed decoder was evaluated across 22 months and experienced a performance decline at a rate of 0.24 bps yr-1. In the monkey with the older (i.e., 3.5 year old) implant and poorer signal quality, a fixed decoder could not sustain performance for more than a few days. Nevertheless, performance in this monkey was maintained for two weeks without requiring additional online retraining time by utilizing prior days’ experimental data. Upon analysis of the changes in channel tuning, we found that this stability appeared partially attributable to the cancelling-out of neural tuning fluctuations when projected to two-dimensional cursor movements. Significance. The findings in this study (1) document the highest-performing communication neural prosthesis in monkeys, (2) confirm and extend prior reports of the stability of fixed decoders, and (3) demonstrate a protocol for system stability under conditions where fixed decoders would otherwise fail. These improvements to decoder

  11. Neural Tube Defects

    Science.gov (United States)

    ... vitamin, before and during pregnancy prevents most neural tube defects. Neural tube defects are usually diagnosed before the infant is ... or imaging tests. There is no cure for neural tube defects. The nerve damage and loss of function ...

  12. [An outlook on the present and future of brain-machine interface research].

    Science.gov (United States)

    Majima, Kei; Kamitani, Yukiyasu

    2011-03-01

    The goal of brain-machine interface (BMI) research is to interpret brain signals in order to control an external device. Substantial progress toward this goal has been achieved over the last decade. Currently, BMI algorithms can translate neural signals into motor commands that reproduce arm-reaching and hand-grasping movements in artificial actuators, thereby promising the restoration of limb mobility in paralyzed people. In one study, a tetraplegic human subject used a clinical neuromotor prosthesis to restore his communication and mobility. Furthermore, a recently developed neural decoding technology provides an effective means to read out mental states from human brain activity. Decoding of mental states could be used for direct human-human communication outside the brain's normal pathways. However, for BMI practical, long-term stability of signal interpretation is required. Unfortunately, the classical invasive BMI methods suffer from poor long-term stability because of deterioration in signal quality. Two new approaches to long-term BMI applications are showing promising results in maintaining signal quality. One is the use of newly developed electrodes that are less harmful to neural tissues, and the other is the use of electrocorticograms (ECoGs), which measure population activity of neurons with electrodes placed on the surface of the brain. Both these new technologies facilitate clearer signals from the brain and greater stability of brain signals over time. In this review, we summarize the previous BMI approaches and shed light upon the new advances that may enable long-term BMI use.

  13. A training platform for many-dimensional prosthetic devices using a virtual reality environment.

    Science.gov (United States)

    Putrino, David; Wong, Yan T; Weiss, Adam; Pesaran, Bijan

    2015-04-15

    Brain machine interfaces (BMIs) have the potential to assist in the rehabilitation of millions of patients worldwide. Despite recent advancements in BMI technology for the restoration of lost motor function, a training environment to restore full control of the anatomical segments of an upper limb extremity has not yet been presented. Here, we develop a virtual upper limb prosthesis with 27 independent dimensions, the anatomical dimensions of the human arm and hand, and deploy the virtual prosthesis as an avatar in a virtual reality environment (VRE) that can be controlled in real-time. The prosthesis avatar accepts kinematic control inputs that can be captured from movements of the arm and hand as well as neural control inputs derived from processed neural signals. We characterize the system performance under kinematic control using a commercially available motion capture system. We also present the performance under kinematic control achieved by two non-human primates (Macaca Mulatta) trained to use the prosthetic avatar to perform reaching and grasping tasks. This is the first virtual prosthetic device that is capable of emulating all the anatomical movements of a healthy upper limb in real-time. Since the system accepts both neural and kinematic inputs for a variety of many-dimensional skeletons, we propose it provides a customizable training platform for the acquisition of many-dimensional neural prosthetic control. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Electronic properties of organic/metal interfaces

    CERN Document Server

    Koch, N

    2000-01-01

    Conjugated organic materials are the promising class of materials for the application in new electronic and opto-electronic devices. The successful realization of highly efficient organic light emitting devices with oligomers and polymers as active electroluminescent layers has lead to a large number of investigations on such systems, the key point being to find means of increasing efficiency and performance of the devices. Intrinsically present in light emitting devices are interfaces, and it appears that the structural and electronic properties of those are of uttermost importance for the device quality. In the present work, ultraviolet and X-ray photoelectron spectroscopy, plus related surface sensitive experimental methods, were used to investigate the electronic properties of interfaces between conjugated organic materials (based on para-phenylene) and various metals. The observed interactions between the two different kinds of materials ranged from physisorption (aluminum and samarium), to the formation...

  15. Insertion devices

    CERN Document Server

    Bahrdt, J

    2006-01-01

    The interaction of an insertion device with the electron beam in a storage ring is discussed. The radiation property including brightness, ux and polarization of an ideal and real planar and helical / elliptical device is described. The magnet design of planar, helical, quasiperiodic devices and of devices with a reduced on axis power density are resumed.

  16. XML Translator for Interface Descriptions

    Science.gov (United States)

    Boroson, Elizabeth R.

    2009-01-01

    A computer program defines an XML schema for specifying the interface to a generic FPGA from the perspective of software that will interact with the device. This XML interface description is then translated into header files for C, Verilog, and VHDL. User interface definition input is checked via both the provided XML schema and the translator module to ensure consistency and accuracy. Currently, programming used on both sides of an interface is inconsistent. This makes it hard to find and fix errors. By using a common schema, both sides are forced to use the same structure by using the same framework and toolset. This makes for easy identification of problems, which leads to the ability to formulate a solution. The toolset contains constants that allow a programmer to use each register, and to access each field in the register. Once programming is complete, the translator is run as part of the make process, which ensures that whenever an interface is changed, all of the code that uses the header files describing it is recompiled.

  17. Visual Prosthesis: Interfacing Stimulating Electrodes with Retinal Neurons to Restore Vision

    Directory of Open Access Journals (Sweden)

    Alejandro Barriga-Rivera

    2017-11-01

    Full Text Available The bypassing of degenerated photoreceptors using retinal neurostimulators is helping the blind to recover functional vision. Researchers are investigating new ways to improve visual percepts elicited by these means as the vision produced by these early devices remain rudimentary. However, several factors are hampering the progression of bionic technologies: the charge injection limits of metallic electrodes, the mechanical mismatch between excitable tissue and the stimulating elements, neural and electric crosstalk, the physical size of the implanted devices, and the inability to selectively activate different types of retinal neurons. Electrochemical and mechanical limitations are being addressed by the application of electromaterials such as conducting polymers, carbon nanotubes and nanocrystalline diamonds, among other biomaterials, to electrical neuromodulation. In addition, the use of synthetic hydrogels and cell-laden biomaterials is promising better interfaces, as it opens a door to establishing synaptic connections between the electrode material and the excitable cells. Finally, new electrostimulation approaches relying on the use of high-frequency stimulation and field overlapping techniques are being developed to better replicate the neural code of the retina. All these elements combined will bring bionic vision beyond its present state and into the realm of a viable, mainstream therapy for vision loss.

  18. Visual Prosthesis: Interfacing Stimulating Electrodes with Retinal Neurons to Restore Vision

    Science.gov (United States)

    Barriga-Rivera, Alejandro; Bareket, Lilach; Goding, Josef; Aregueta-Robles, Ulises A.; Suaning, Gregg J.

    2017-01-01

    The bypassing of degenerated photoreceptors using retinal neurostimulators is helping the blind to recover functional vision. Researchers are investigating new ways to improve visual percepts elicited by these means as the vision produced by these early devices remain rudimentary. However, several factors are hampering the progression of bionic technologies: the charge injection limits of metallic electrodes, the mechanical mismatch between excitable tissue and the stimulating elements, neural and electric crosstalk, the physical size of the implanted devices, and the inability to selectively activate different types of retinal neurons. Electrochemical and mechanical limitations are being addressed by the application of electromaterials such as conducting polymers, carbon nanotubes and nanocrystalline diamonds, among other biomaterials, to electrical neuromodulation. In addition, the use of synthetic hydrogels and cell-laden biomaterials is promising better interfaces, as it opens a door to establishing synaptic connections between the electrode material and the excitable cells. Finally, new electrostimulation approaches relying on the use of high-frequency stimulation and field overlapping techniques are being developed to better replicate the neural code of the retina. All these elements combined will bring bionic vision beyond its present state and into the realm of a viable, mainstream therapy for vision loss. PMID:29184478

  19. Seeding neural progenitor cells on silicon-based neural probes.

    Science.gov (United States)

    Azemi, Erdrin; Gobbel, Glenn T; Cui, Xinyan Tracy

    2010-09-01

    Chronically implanted neural electrode arrays have the potential to be used as neural prostheses in patients with various neurological disorders. While these electrodes perform well in acute recordings, they often fail to function reliably in clinically relevant chronic settings because of glial encapsulation and the loss of neurons. Surface modification of these implants may provide a means of improving their biocompatibility and integration within host brain tissue. The authors proposed a method of improving the brain-implant interface by seeding the implant's surface with a layer of neural progenitor cells (NPCs) derived from adult murine subependyma. Neural progenitor cells may reduce the foreign body reaction by presenting a tissue-friendly surface and repair implant-induced injury and inflammation by releasing neurotrophic factors. In this study, the authors evaluated the growth and differentiation of NPCs on laminin-immobilized probe surfaces and explored the potential impact on transplant survival of these cells. Laminin protein was successfully immobilized on the silicon surface via covalent binding using silane chemistry. The growth, adhesion, and differentiation of NPCs expressing green fluorescent protein (GFP) on laminin-modified silicon surfaces were characterized in vitro by using immunocytochemical techniques. Shear forces were applied to NPC cultures in growth medium to evaluate their shearing properties. In addition, neural probes seeded with GFP-labeled NPCs cultured in growth medium for 14 days were implanted in murine cortex. The authors assessed the adhesion properties of these cells during implantation conditions. Moreover, the tissue response around NPC-seeded implants was observed after 1 and 7 days postimplantation. Significantly improved NPC attachment and growth was found on the laminin-immobilized surface compared with an unmodified control before and after shear force application. The NPCs grown on the laminin-immobilized surface

  20. Stereo vision based 3D game interface

    Science.gov (United States)

    Lu, Peng; Chen, Yisong; Dong, Chao

    2009-10-01

    Currently, keyboards, mice, wands and joysticks are still the most popular interactive devices. While these devices are mostly adequate, they are so unnatural that they are unable to give players the feeling of immersiveness. Researchers have begun investigation into natural interfaces that are intuitively simple and unobtrusive to the user. Recent advances in various signal-processing technologies, coupled with an explosion in the available computing power, have given rise to a number of natural human computer interface (HCI) modalities: speech, vision-based gesture recognition, etc. In this paper we propose a natural three dimensional (3D) game interface, which uses the motion of the player fists in 3D space to achieve the control of sixd egree of freedom (DOFs). And we also propose a real-time 3D fist tracking algorithm, which is based on stereo vision and Bayesian network. Finally, a flying game is used to test our interface.

  1. Cortical neural prosthetics.

    Science.gov (United States)

    Schwartz, Andrew B

    2004-01-01

    Control of prostheses using cortical signals is based on three elements: chronic microelectrode arrays, extraction algorithms, and prosthetic effectors. Arrays of microelectrodes are permanently implanted in cerebral cortex. These arrays must record populations of single- and multiunit activity indefinitely. Information containing position and velocity correlates of animate movement needs to be extracted continuously in real time from the recorded activity. Prosthetic arms, the current effectors used in this work, need to have the agility and configuration of natural arms. Demonstrations using closed-loop control show that subjects change their neural activity to improve performance with these devices. Adaptive-learning algorithms that capitalize on these improvements show that this technology has the capability of restoring much of the arm movement lost with immobilizing deficits.

  2. Neural prostheses in clinical applications--trends from precision mechanics towards biomedical microsystems in neurological rehabilitation.

    Science.gov (United States)

    Stieglitz, T; Schuettler, M; Koch, K P

    2004-04-01

    Neural prostheses partially restore body functions by technical nerve excitation after trauma or neurological diseases. External devices and implants have been developed since the early 1960s for many applications. Several systems have reached nowadays clinical practice: Cochlea implants help the deaf to hear, micturition is induced by bladder stimulators in paralyzed persons and deep brain stimulation helps patients with Parkinson's disease to participate in daily life again. So far, clinical neural prostheses are fabricated with means of precision mechanics. Since microsystem technology opens the opportunity to design and develop complex systems with a high number of electrodes to interface with the nervous systems, the opportunity for selective stimulation and complex implant scenarios seems to be feasible in the near future. The potentials and limitations with regard to biomedical microdevices are introduced and discussed in this paper. Target specifications are derived from existing implants and are discussed on selected applications that has been investigated in experimental research: a micromachined implant to interface a nerve stump with a sieve electrode, cuff electrodes with integrated electronics, and an epiretinal vision prosthesis.

  3. [Neural repair].

    Science.gov (United States)

    Kitada, Masaaki; Dezawa, Mari

    2008-05-01

    Recent progress of stem cell biology gives us the hope for neural repair. We have established methods to specifically induce functional Schwann cells and neurons from bone marrow stromal cells (MSCs). The effectiveness of these induced cells was evaluated by grafting them either into peripheral nerve injury, spinal cord injury, or Parkinson' s disease animal models. MSCs-derived Schwann cells supported axonal regeneration and re-constructed myelin to facilitate the functional recovery in peripheral and spinal cord injury. MSCs-derived dopaminergic neurons integrated into host striatum and contributed to behavioral repair. In this review, we introduce the differentiation potential of MSCs and finally discuss about their benefits and drawbacks of these induction systems for cell-based therapy in neuro-traumatic and neuro-degenerative diseases.

  4. Spacecraft Neural Network Control System Design using FPGA

    OpenAIRE

    Hanaa T. El-Madany; Faten H. Fahmy; Ninet M. A. El-Rahman; Hassen T. Dorrah

    2011-01-01

    Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffer...

  5. Spiking Neural Networks based on OxRAM Synapses for Real-time Unsupervised Spike Sorting

    Directory of Open Access Journals (Sweden)

    Thilo Werner

    2016-11-01

    Full Text Available In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN. The proposed architecture is suitable for hardware implementation by using RRAM technology for the implementation of synapses whose low latency (< 1μs enable real-time spike sorting. This offers promising advantagesto conventional spike sorting techniques for brain-computer interface and neural prosthesis applications. Moreover, the ultralow power consumption of the RRAM synapses of the spiking neural network (nW range may enable the design of autonomous implantable devices for rehabilitation purposes. We demonstrate an original methodology to use Oxide based RRAM (OxRAM as easy to program and low power (< 75 pJ synapses. Synaptic weights are modulated through the application of an online learning strategy inspired by biological Spike Timing Dependent Plasticity. Real spiking data have been recorded both intraand extracellularly from an in-vitro preparation of the Crayfish sensory-motor system and used for validation of the proposed OxRAM based SNN. This artificial SNN is able to identify, learn, recognize and distinguish between different spike shapes in the input signal with a recognition rate about 90% without any supervision.

  6. Multiphase Microfluidics The Diffuse Interface Model

    CERN Document Server

    2012-01-01

    Multiphase flows are typically described assuming that the different phases are separated by a sharp interface, with appropriate boundary conditions. This approach breaks down whenever the lengthscale of the phenomenon that is being studied is comparable with the real interface thickness, as it happens, for example, in the coalescence and breakup of bubbles and drops, the wetting and dewetting of solid surfaces and, in general, im micro-devices. The diffuse interface model resolves these probems by assuming that all quantities can vary continuously, so that interfaces have a non-zero thickness, i.e. they are "diffuse". The contributions in this book review the theory and describe some relevant applications of the diffuse interface model for one-component, two-phase fluids and for liquid binary mixtures, to model multiphase flows in confined geometries.

  7. Ludic interfaces. Driver and product of gamification

    Directory of Open Access Journals (Sweden)

    Mathias Fuchs

    2012-05-01

    Full Text Available The recent success of non-standard and playful interface devices like Wii Remote, Move, and Kinect is an indicator of a process that demonstrates that ludic interfaces might be the core driver for a transformation in the sector of video games cultures and beyond. Yet, ludic interfaces are drivers—as well as driven by social developments known as the ludification (Raessens, 2006; Fuchs & Strouhal, 2008, or the gamification of society (Schell, 2010; Bogost, 2010; Ionifides, 2011; Deterding, Khaled, Nacke, & Dixon, 2011.

  8. Organic solar cells materials and device physics

    CERN Document Server

    Choy, Wallace CH

    2014-01-01

    This book discusses synthesis, properties and uses of new materials in devices from electrodes, interface and carrier transport materials to the active layer of donors and acceptors. Covers polymers, exciton and charge dynamics, organic photovoltaics and more.

  9. Augmented reality as a design tool for mobile interfaces

    DEFF Research Database (Denmark)

    Bertelsen, Olav Wedege; Nielsen, Christina

    2000-01-01

    applications derived from the classification of augmented reality interfaces. The focus on physical interaction with objects of work and with the mobile device provides us with a range of interaction styles, based on e.g. gestures and manipulation of objects. Furthermore, issues of transparency and directness......This paper challenges user interface paradigms for mobile devices, by using the technical classification of augmented reality interfaces as a thinking tool to develop ideas for interaction with mobile devices. The paper presents future work scenarios from a wastewater treatment plant embodying PDA...... are addressed. The future scenarios indicate that the concepts of augmented reality support solving context problems in mobile design....

  10. Neural prostheses and brain plasticity

    Science.gov (United States)

    Fallon, James B.; Irvine, Dexter R. F.; Shepherd, Robert K.

    2009-12-01

    The success of modern neural prostheses is dependent on a complex interplay between the devices' hardware and software and the dynamic environment in which the devices operate: the patient's body or 'wetware'. Over 120 000 severe/profoundly deaf individuals presently receive information enabling auditory awareness and speech perception from cochlear implants. The cochlear implant therefore provides a useful case study for a review of the complex interactions between hardware, software and wetware, and of the important role of the dynamic nature of wetware. In the case of neural prostheses, the most critical component of that wetware is the central nervous system. This paper will examine the evidence of changes in the central auditory system that contribute to changes in performance with a cochlear implant, and discuss how these changes relate to electrophysiological and functional imaging studies in humans. The relationship between the human data and evidence from animals of the remarkable capacity for plastic change of the central auditory system, even into adulthood, will then be examined. Finally, we will discuss the role of brain plasticity in neural prostheses in general.

  11. Interface mobility from interface random walk

    Science.gov (United States)

    Trautt, Zachary; Upmanyu, Moneesh; Karma, Alain

    2007-03-01

    Computational studies aimed at extracting interface mobilities require driving forces orders of magnitude higher than those occurring experimentally. We present a computational methodology that extracts the absolute interface mobility in the zero driving force limit by monitoring the one-dimensional random walk of the mean interface position along the interface normal. The method exploits a fluctuation-dissipation relation similar to the Stokes-Einstein relation, which relates the diffusion coefficient of this Brownian-like random walk to the interface mobility. Atomic-scale simulations of grain boundaries in model crystalline systems validate the theoretical predictions, and also highlight the profound effect of impurities. The generality of this technique combined with its inherent spatial-temporal efficiency should allow computational studies to effectively complement experiments in understanding interface kinetics in diverse material systems.

  12. Interface solutions for interface side effects?

    Directory of Open Access Journals (Sweden)

    Stoffregen Thomas A.

    2011-12-01

    Full Text Available Human-computer interfaces often give rise to a variety of side effects, including eyestrain, headache, fatigue, and motion sickness (aka cybersickness, simulator sickness. We might hope that improvements in interface design would tend to reduce these side effects. Unfortunately, history reveals just the opposite: The incidence and severity of motion sickness (for example is positively related to the progressive sophistication of display technology and systems. In this presentation, I enquire about the future of interface technologies in relation to side effects. I review the types of side effects that occur and what is known about the causes of interface side effects. I suggest new ways of understanding relations between interface technologies and side effects, and new ways to approach the problem of interface side effects.

  13. What will this do to me and my brain? Ethical issues in brain-to-brain interfacing

    Directory of Open Access Journals (Sweden)

    Elisabeth eHildt

    2015-02-01

    Full Text Available For several years now, brain-computer interfaces (BCIs in which brain signals are used to navigate a computer, a prostheses or a technical device, have been developed in various experimental contexts (Wolpaw & Wolpaw 2012; Grübler & Hildt 2014. Researchers have recently taken the next step and run experiments based on connections between two brains. These so-called brain-to-brain interfaces (abbreviation: BBIs or BTBIs involve not only a BCI component deriving information from a brain and sending it to a computer, but also a computer-brain interface (CBI component delivering information to another brain. What results is technology-mediated brain-to-brain communication (B2B communication, i.e. direct communication between two brains that does not involve any activity of the peripheral nervous system. In what follows, ethical issues that arise in neural interfacing will be discussed after a short introduction to recent BBI experiments. In this, the focus will be on the implications BBIs may have on the individual at the CBI side of the BBI, i.e. on the recipient.

  14. Syringe-Injectable Electronics with a Plug-and-Play Input/Output Interface.

    Science.gov (United States)

    Schuhmann, Thomas G; Yao, Jun; Hong, Guosong; Fu, Tian-Ming; Lieber, Charles M

    2017-09-13

    Syringe-injectable mesh electronics represent a new paradigm for brain science and neural prosthetics by virtue of the stable seamless integration of the electronics with neural tissues, a consequence of the macroporous mesh electronics structure with all size features similar to or less than individual neurons and tissue-like flexibility. These same properties, however, make input/output (I/O) connection to measurement electronics challenging, and work to-date has required methods that could be difficult to implement by the life sciences community. Here we present a new syringe-injectable mesh electronics design with plug-and-play I/O interfacing that is rapid, scalable, and user-friendly to nonexperts. The basic design tapers the ultraflexible mesh electronics to a narrow stem that routes all of the device/electrode interconnects to I/O pads that are inserted into a standard zero insertion force (ZIF) connector. Studies show that the entire plug-and-play mesh electronics can be delivered through capillary needles with precise targeting using microliter-scale injection volumes similar to the standard mesh electronics design. Electrical characterization of mesh electronics containing platinum (Pt) electrodes and silicon (Si) nanowire field-effect transistors (NW-FETs) demonstrates the ability to interface arbitrary devices with a contact resistance of only 3 Ω. Finally, in vivo injection into mice required only minutes for I/O connection and yielded expected local field potential (LFP) recordings from a compact head-stage compatible with chronic studies. Our results substantially lower barriers for use by new investigators and open the door for increasingly sophisticated and multifunctional mesh electronics designs for both basic and translational studies.

  15. Concentration device

    DEFF Research Database (Denmark)

    2013-01-01

    A concentration device (2) for filter filtration concentration of particles (4) from a volume of a fluid (6). The concentration device (2) comprises a filter (8) configured to filter particles (4) of a predefined size in the volume of the fluid (6). The concentration device (2) comprises...

  16. Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia

    Science.gov (United States)

    Kim, Sung-Phil; Simeral, John D.; Hochberg, Leigh R.; Donoghue, John P.; Black, Michael J.

    2008-12-01

    Computer-mediated connections between human motor cortical neurons and assistive devices promise to improve or restore lost function in people with paralysis. Recently, a pilot clinical study of an intracortical neural interface system demonstrated that a tetraplegic human was able to obtain continuous two-dimensional control of a computer cursor using neural activity recorded from his motor cortex. This control, however, was not sufficiently accurate for reliable use in many common computer control tasks. Here, we studied several central design choices for such a system including the kinematic representation for cursor movement, the decoding method that translates neuronal ensemble spiking activity into a control signal and the cursor control task used during training for optimizing the parameters of the decoding method. In two tetraplegic participants, we found that controlling a cursor's velocity resulted in more accurate closed-loop control than controlling its position directly and that cursor velocity control was achieved more rapidly than position control. Control quality was further improved over conventional linear filters by using a probabilistic method, the Kalman filter, to decode human motor cortical activity. Performance assessment based on standard metrics used for the evaluation of a wide range of pointing devices demonstrated significantly improved cursor control with velocity rather than position decoding. Disclosure. JPD is the Chief Scientific Officer and a director of Cyberkinetics Neurotechnology Systems (CYKN); he holds stock and receives compensation. JDS has been a consultant for CYKN. LRH receives clinical trial support from CYKN.

  17. Localizing Tortoise Nests by Neural Networks.

    Directory of Open Access Journals (Sweden)

    Roberto Barbuti

    Full Text Available The goal of this research is to recognize the nest digging activity of tortoises using a device mounted atop the tortoise carapace. The device classifies tortoise movements in order to discriminate between nest digging, and non-digging activity (specifically walking and eating. Accelerometer data was collected from devices attached to the carapace of a number of tortoises during their two-month nesting period. Our system uses an accelerometer and an activity recognition system (ARS which is modularly structured using an artificial neural network and an output filter. For the purpose of experiment and comparison, and with the aim of minimizing the computational cost, the artificial neural network has been modelled according to three different architectures based on the input delay neural network (IDNN. We show that the ARS can achieve very high accuracy on segments of data sequences, with an extremely small neural network that can be embedded in programmable low power devices. Given that digging is typically a long activity (up to two hours, the application of ARS on data segments can be repeated over time to set up a reliable and efficient system, called Tortoise@, for digging activity recognition.

  18. Brain Computer Interfaces, a Review

    Science.gov (United States)

    Nicolas-Alonso, Luis Fernando; Gomez-Gil, Jaime

    2012-01-01

    A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or ‘locked in’ by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Finally, the review provides an overview of various BCI applications that control a range of devices. PMID:22438708

  19. Brain computer interfaces, a review.

    Science.gov (United States)

    Nicolas-Alonso, Luis Fernando; Gomez-Gil, Jaime

    2012-01-01

    A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Finally, the review provides an overview of various BCI applications that control a range of devices.

  20. Brain Computer Interfaces, a Review

    Directory of Open Access Journals (Sweden)

    Luis Fernando Nicolas-Alonso

    2012-01-01

    Full Text Available A brain-computer interface (BCI is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or ‘locked in’ by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Finally, the review provides an overview of various BCI applications that control a range of devices.

  1. Interface Simulation Distances

    Directory of Open Access Journals (Sweden)

    Pavol Černý

    2012-10-01

    Full Text Available The classical (boolean notion of refinement for behavioral interfaces of system components is the alternating refinement preorder. In this paper, we define a distance for interfaces, called interface simulation distance. It makes the alternating refinement preorder quantitative by, intuitively, tolerating errors (while counting them in the alternating simulation game. We show that the interface simulation distance satisfies the triangle inequality, that the distance between two interfaces does not increase under parallel composition with a third interface, and that the distance between two interfaces can be bounded from above and below by distances between abstractions of the two interfaces. We illustrate the framework, and the properties of the distances under composition of interfaces, with two case studies.

  2. A novel flexible cuff-like microelectrode for dual purpose, acute and chronic electrical interfacing with the mouse cervical vagus nerve

    Science.gov (United States)

    Caravaca, A. S.; Tsaava, T.; Goldman, L.; Silverman, H.; Riggott, G.; Chavan, S. S.; Bouton, C.; Tracey, K. J.; Desimone, R.; Boyden, E. S.; Sohal, H. S.; Olofsson, P. S.

    2017-12-01

    Objective. Neural reflexes regulate immune responses and homeostasis. Advances in bioelectronic medicine indicate that electrical stimulation of the vagus nerve can be used to treat inflammatory disease, yet the understanding of neural signals that regulate inflammation is incomplete. Current interfaces with the vagus nerve do not permit effective chronic stimulation or recording in mouse models, which is vital to studying the molecular and neurophysiological mechanisms that control inflammation homeostasis in health and disease. We developed an implantable, dual purpose, multi-channel, flexible ‘microelectrode’ array, for recording and stimulation of the mouse vagus nerve. Approach. The array was microfabricated on an 8 µm layer of highly biocompatible parylene configured with 16 sites. The microelectrode was evaluated by studying the recording and stimulation performance. Mice were chronically implanted with devices for up to 12 weeks. Main results. Using the microelectrode in vivo, high fidelity signals were recorded during physiological challenges (e.g potassium chloride and interleukin-1β), and electrical stimulation of the vagus nerve produced the expected significant reduction of blood levels of tumor necrosis factor (TNF) in endotoxemia. Inflammatory cell infiltration at the microelectrode 12 weeks of implantation was limited according to radial distribution analysis of inflammatory cells. Significance. This novel device provides an important step towards a viable chronic interface for cervical vagus nerve stimulation and recording in mice.

  3. A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors.

    Science.gov (United States)

    Nageswaran, Jayram Moorkanikara; Dutt, Nikil; Krichmar, Jeffrey L; Nicolau, Alex; Veidenbaum, Alexander V

    2009-01-01

    Neural network simulators that take into account the spiking behavior of neurons are useful for studying brain mechanisms and for various neural engineering applications. Spiking Neural Network (SNN) simulators have been traditionally simulated on large-scale clusters, super-computers, or on dedicated hardware architectures. Alternatively, Compute Unified Device Architecture (CUDA) Graphics Processing Units (GPUs) can provide a low-cost, programmable, and high-performance computing platform for simulation of SNNs. In this paper we demonstrate an efficient, biologically realistic, large-scale SNN simulator that runs on a single GPU. The SNN model includes Izhikevich spiking neurons, detailed models of synaptic plasticity and variable axonal delay. We allow user-defined configuration of the GPU-SNN model by means of a high-level programming interface written in C++ but similar to the PyNN programming interface specification. PyNN is a common programming interface developed by the neuronal simulation community to allow a single script to run on various simulators. The GPU implementation (on NVIDIA GTX-280 with 1 GB of memory) is up to 26 times faster than a CPU version for the simulation of 100K neurons with 50 Million synaptic connections, firing at an average rate of 7 Hz. For simulation of 10 Million synaptic connections and 100K neurons, the GPU SNN model is only 1.5 times slower than real-time. Further, we present a collection of new techniques related to parallelism extraction, mapping of irregular communication, and network representation for effective simulation of SNNs on GPUs. The fidelity of the simulation results was validated on CPU simulations using firing rate, synaptic weight distribution, and inter-spike interval analysis. Our simulator is publicly available to the modeling community so that researchers will have easy access to large-scale SNN simulations.

  4. Organic semiconductor density of states controls the energy level alignment at electrode interfaces

    National Research Council Canada - National Science Library

    Oehzelt, Martin; Koch, Norbert; Heimel, Georg

    2014-01-01

    Minimizing charge carrier injection barriers and extraction losses at interfaces between organic semiconductors and metallic electrodes is critical for optimizing the performance of organic (opto-) electronic devices...

  5. Designing interfaces patterns for effective interaction design

    CERN Document Server

    Tidwell, Jenifer

    2005-01-01

    This convenient resource offers advice on creating user-friendly interface designs--whether they're delivered on the Web, a CD, or a smart" devices like a cell phone. Solutions to common UI design problems are expressed as a collection of patterns--each one containing concrete examples, recommendations, and warnings. Intended for designers with basic UI design knowledge

  6. An electronic structure perspective of graphene interfaces.

    Science.gov (United States)

    Schultz, Brian J; Dennis, Robert V; Lee, Vincent; Banerjee, Sarbajit

    2014-04-07

    The unusual electronic structure of graphene characterized by linear energy dispersion of bands adjacent to the Fermi level underpins its remarkable transport properties. However, for practical device integration, graphene will need to be interfaced with other materials: 2D layered structures, metals (as ad-atoms, nanoparticles, extended surfaces, and patterned metamaterial geometries), dielectrics, organics, or hybrid structures that in turn are constituted from various inorganic or organic components. The structural complexity at these nanoscale interfaces holds much promise for manifestation of novel emergent phenomena and provides a means to modulate the electronic structure of graphene. In this feature article, we review the modifications to the electronic structure of graphene induced upon interfacing with disparate types of materials with an emphasis on iterative learnings from theoretical calculations and electronic spectroscopy (X-ray absorption fine structure (XAFS) spectroscopy, scanning transmission X-ray microscopy (STXM), angle-resolved photoemission spectroscopy (ARPES), and X-ray magnetic circular dichroism (XMCD)). We discuss approaches for engineering and modulating a bandgap in graphene through interfacial hybridization, outline experimental methods for examining electronic structure at interfaces, and overview device implications of engineered interfaces. A unified view of how geometric and electronic structure are correlated at interfaces will provide a rational means for designing heterostructures exhibiting emergent physical phenomena with implications for plasmonics, photonics, spintronics, and engineered polymer and metal matrix composites.

  7. An optical brain computer interface for environmental control.

    Science.gov (United States)

    Ayaz, Hasan; Shewokis, Patricia A; Bunce, Scott; Onaral, Banu

    2011-01-01

    A brain computer interface (BCI) is a system that translates neurophysiological signals detected from the brain to supply input to a computer or to control a device. Volitional control of neural activity and its real-time detection through neuroimaging modalities are key constituents of BCI systems. The purpose of this study was to develop and test a new BCI design that utilizes intention-related cognitive activity within the dorsolateral prefrontal cortex using functional near infrared (fNIR) spectroscopy. fNIR is a noninvasive, safe, portable and affordable optical technique with which to monitor hemodynamic changes, in the brain's cerebral cortex. Because of its portability and ease of use, fNIR is amenable to deployment in ecologically valid natural working environments. We integrated a control paradigm in a computerized 3D virtual environment to augment interactivity. Ten healthy participants volunteered for a two day study in which they navigated a virtual environment with keyboard inputs, but were required to use the fNIR-BCI for interaction with virtual objects. Results showed that participants consistently utilized the fNIR-BCI with an overall success rate of 84% and volitionally increased their cerebral oxygenation level to trigger actions within the virtual environment.

  8. Boolean and brain-inspired computing using spin-transfer torque devices

    Science.gov (United States)

    Fan, Deliang

    Several completely new approaches (such as spintronic, carbon nanotube, graphene, TFETs, etc.) to information processing and data storage technologies are emerging to address the time frame beyond current Complementary Metal-Oxide-Semiconductor (CMOS) roadmap. The high speed magnetization switching of a nano-magnet due to current induced spin-transfer torque (STT) have been demonstrated in recent experiments. Such STT devices can be explored in compact, low power memory and logic design. In order to truly leverage STT devices based computing, researchers require a re-think of circuit, architecture, and computing model, since the STT devices are unlikely to be drop-in replacements for CMOS. The potential of STT devices based computing will be best realized by considering new computing models that are inherently suited to the characteristics of STT devices, and new applications that are enabled by their unique capabilities, thereby attaining performance that CMOS cannot achieve. The goal of this research is to conduct synergistic exploration in architecture, circuit and device levels for Boolean and brain-inspired computing using nanoscale STT devices. Specifically, we first show that the non-volatile STT devices can be used in designing configurable Boolean logic blocks. We propose a spin-memristor threshold logic (SMTL) gate design, where memristive cross-bar array is used to perform current mode summation of binary inputs and the low power current mode spintronic threshold device carries out the energy efficient threshold operation. Next, for brain-inspired computing, we have exploited different spin-transfer torque device structures that can implement the hard-limiting and soft-limiting artificial neuron transfer functions respectively. We apply such STT based neuron (or 'spin-neuron') in various neural network architectures, such as hierarchical temporal memory and feed-forward neural network, for performing "human-like" cognitive computing, which show more than

  9. Instantaneous Liquid Interfaces

    OpenAIRE

    Willard, Adam P.; Chandler, David

    2009-01-01

    We describe and illustrate a simple procedure for identifying a liquid interface from atomic coordinates. In particular, a coarse grained density field is constructed, and the interface is defined as a constant density surface for this coarse grained field. In applications to a molecular dynamics simulation of liquid water, it is shown that this procedure provides instructive and useful pictures of liquid-vapor interfaces and of liquid-protein interfaces.

  10. Microcomputer interfacing and applications

    CERN Document Server

    Mustafa, M A

    1990-01-01

    This is the applications guide to interfacing microcomputers. It offers practical non-mathematical solutions to interfacing problems in many applications including data acquisition and control. Emphasis is given to the definition of the objectives of the interface, then comparing possible solutions and producing the best interface for every situation. Dr Mustafa A Mustafa is a senior designer of control equipment and has written many technical articles and papers on the subject of computers and their application to control engineering.

  11. User Interface for Volume Rendering in Virtual Reality Environments

    OpenAIRE

    Klein, Jonathan; Reuling, Dennis; Grimm, Jan; Pfau, Andreas; Lefloch, Damien; Lambers, Martin; Kolb, Andreas

    2013-01-01

    Volume Rendering applications require sophisticated user interaction for the definition and refinement of transfer functions. Traditional 2D desktop user interface elements have been developed to solve this task, but such concepts do not map well to the interaction devices available in Virtual Reality environments. In this paper, we propose an intuitive user interface for Volume Rendering specifically designed for Virtual Reality environments. The proposed interface allows transfer function d...

  12. A Model-Based Approach for Distributed User Interfaces

    OpenAIRE

    Melchior, Jérémie; Vanderdonckt, Jean; Van Roy, Peter; 3rd ACM Symposium on Engineering Interactive Computing Systems EICS’2011

    2011-01-01

    This paper describes a model-based approach for designing Distributed User Interfaces (DUIs), i.e., graphical user interfaces that are distributed along the following dimensions: end user, display device, computing platform, and physical environment. The three pillars of this model-based approach are: (i) a Concrete User Interface model for DUIs incorporating the distribution dimensions and expressing any DUI element in a XML-compliant format until the granularity of an individual DUI element...

  13. Disposable world-to-chip interface for digital microfluidics

    Energy Technology Data Exchange (ETDEWEB)

    Van Dam, R. Michael; Shah, Gaurav; Keng, Pei-Yuin

    2017-05-16

    The present disclosure sets forth incorporating microfluidic chips interfaces for use with digital microfluidic processes. Methods and devices according to the present disclosure utilize compact, integrated platforms that interface with a chip upstream and downstream of the reaction, as well as between intermediate reaction steps if needed. In some embodiments these interfaces are automated, including automation of a multiple reagent process. Various reagent delivery systems and methods are also disclosed.

  14. Research Update: Platinum-elastomer mesocomposite as neural electrode coating

    Directory of Open Access Journals (Sweden)

    Ivan R. Minev

    2015-01-01

    Full Text Available Platinum is electrochemically stable and biocompatible, and remains the preferred material for the fabrication of implantable neural electrodes. In a foil or film format, platinum is mechanically stiff compared to interfaced biological tissue. We report a soft, highly stable platinum-elastomer composite that offers both mechanical compliance and the electrochemical properties of platinum. We demonstrate the high-performance of the novel mesocomposite printed on stretchable microelectrodes both in vitro and in vivo. The platinum-elastomer composite is a new promising coating for chronic neural interfaces.

  15. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  16. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  17. Water at Interfaces

    DEFF Research Database (Denmark)

    Björneholm, Olle; Hansen, Martin Hangaard; Hodgson, Andrew

    2016-01-01

    The interfaces of neat water and aqueous solutions play a prominent role in many technological processes and in the environment. Examples of aqueous interfaces are ultrathin water films that cover most hydrophilic surfaces under ambient relative humidities, the liquid/solid interface which drives...

  18. Optoelectronic adaptive neuro-device

    Science.gov (United States)

    Yonezu, H.; Kanamori, K.; Tsuji, K.; Himeno, T.; Takano, Y.; Pak, K.

    1992-04-01

    The development of a new adaptive neurodevice with a nonvolatile memory function is reported. The adaptive neurodevice is based on EEPROM technology and has additional control electrodes; the synaptic weights are varied during operation depending on target signals. The device can be used for implementing learning algorithms for self-organizing neural networks. It can also be used in hardware implementing learning algorithms without a teacher or in other adaptive circuits where the desired output varies according to reference signals.

  19. Neural prostheses and biomedical microsystems in neurological rehabilitation.

    Science.gov (United States)

    Koch, K P

    2007-01-01

    Interfaces between electrodes and the neural system differ with respect to material and shape depending on their intended application and fabrication method. This chapter will review the different electrode designs regarding the technological implementation and fabrication process. Furthermore this book chapter will describe electrodes for interfacing the peripheral nerves like cuff, book or helix as well as electrodes for interfacing the cortex like needle arrays. The implantation method and mechanical interaction between the electrode and the nervous tissue were taken into consideration. To develop appropriate microtechnological assembling strategies that ensure proper interfacing between the tiny electrodes and microelectronics or connectors is one of the major challenges. The integration of electronics into the system helps to improve the reliability of detecting neural signals and reduces the size of the implants. Promising results with these novel electrodes will pave the road for future developments such as visual prosthetics or improved control of artificial limbs in paralyzed patients.

  20. Bridges, Connections and Interfaces - Reflections over the Meso Theme

    Science.gov (United States)

    Svedin, Uno; Liljenström, Hans

    The following sections are included: * The grand bridge: From the very small to the very large * Life as phenomena at the meso level: The issue of reductionist couplings between levels * Neural systems, brains and sensation: The interface between realms of existence * The connection between nature and society: On linking apples and pears * On interdisciplinarity and the challenges for knowledge production * Notes * References