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

Surface and interface sciences of Li-ion batteries. -Research progress in electrode-electrolyte interface-

Science.gov (United States)

Minato, Taketoshi; Abe, Takeshi

2017-12-01

The application potential of Li-ion batteries is growing as demand increases in different fields at various stages in energy systems, in addition to their conventional role as power sources for portable devices. In particular, applications in electric vehicles and renewable energy storage are increasing for Li-ion batteries. For these applications, improvements in battery performance are necessary. The Li-ion battery produces and stores electric power from the electrochemical redox reactions between the electrode materials. The interface between the electrodes and electrolyte strongly affects the battery performance because the charge transfer causing the electrode redox reaction begins at this interface. Understanding of the surface structure, electronic structure, and chemical reactions at the electrode-electrolyte interface is necessary to improve battery performance. However, the interface is located between the electrode and electrolyte materials, hindering the experimental analysis of the interface; thus, the physical properties and chemical processes have remained poorly understood until recently. Investigations of the physical properties and chemical processes at the interface have been performed using advanced surface science techniques. In this review, current knowledge and future research prospects regarding the electrode-electrolyte interface are described for the further development of Li-ion batteries.

Control of a mobile robot through brain computer interface

Directory of Open Access Journals (Sweden)

Robinson Jimenez Moreno

2015-07-01

Full Text Available This paper poses a control interface to command the movement of a mobile robot according to signals captured from the user's brain. These signals are acquired and interpreted by Emotiv EPOC device, a 14-electrode type sensor which captures electroencephalographic (EEG signals with high resolution, which, in turn, are sent to a computer for processing. One brain-computer interface (BCI was developed based on the Emotiv software and SDK in order to command the mobile robot from a distance. Functionality tests are performed with the sensor to discriminate shift intentions of a user group, as well as with a fuzzy controller to hold the direction in case of concentration loss. As conclusion, it was possible to obtain an efficient system for robot movements by brain commands.

A hybrid clinical-research depth electrode for acute and chronic in vivo microelectrode recording of human brain neurons. Technical note.

Science.gov (United States)

Howard, M A; Volkov, I O; Granner, M A; Damasio, H M; Ollendieck, M C; Bakken, H E

1996-01-01

For several decades, important scientific information has been gained from in vivo microelectrode recordings of individual human cerebral cortical neurons in patients with epilepsy. The experimental methods used, however, are technically complex and require a highly skilled intraoperative team. There are also significant experimental time limitations, as well as constraints on the type of behavioral tests conducted, and the brain regions that may be safely studied. In this report, a new method is described for obtaining in vivo microelectrode recordings using a hybrid depth electrode (HDE). High-impedance research recording contacts are interspersed between low-impedance clinical electroencephalographic (EEG) contacts along the HDE shaft. The HDE has the same external physical properties as a standard clinical depth electrode (DE). Following preclinical laboratory testing, 15 HDEs were used in the evaluation of six patients with medically refractory epilepsy. High-quality EEG recordings were obtained in all cases (two acute intraoperative, four from the chronic epilepsy monitoring unit). Action potentials from individual neurons were successfully recorded during all experimental sessions; however, the chronic preparations were clearly superior. Chronic HDEs are placed using a standard stereotactic system, and the locations of recording contacts are documented on a postimplantation imaging study. The quality of the chronic research recordings was excellent over study periods ranging from 5 to 14 days. The patients rested comfortably on the ward and were able to cooperate with complex experimental instructions. Basic neuroscientists participated fully in all aspects of the chronic investigations. The use of an HDE in place of a standard clinical DE may now allow detailed physiological investigations of any brain region targeted for clinical DE implantation.

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.

Depth resolution and preferential sputtering in depth profiling of sharp interfaces

International Nuclear Information System (INIS)

Hofmann, S.; Han, Y.S.; Wang, J.Y.

2017-01-01

Highlights: • Interfacial depth resolution from MRI model depends on sputtering rate differences. • Depth resolution critically depends on the dominance of roughness or atomic mixing. • True (depth scale) and apparent (time scale) depth resolutions are different. • Average sputtering rate approximately yields true from apparent depth resolution. • Profiles by SIMS and XPS are different but similar to surface concentrations. - Abstract: The influence of preferential sputtering on depth resolution of sputter depth profiles is studied for different sputtering rates of the two components at an A/B interface. Surface concentration and intensity depth profiles on both the sputtering time scale (as measured) and the depth scale are obtained by calculations with an extended Mixing-Roughness-Information depth (MRI)-model. The results show a clear difference for the two extreme cases (a) preponderant roughness and (b) preponderant atomic mixing. In case (a), the interface width on the time scale (Δt(16–84%)) increases with preferential sputtering if the faster sputtering component is on top of the slower sputtering component, but the true resolution on the depth scale (Δz(16–84%)) stays constant. In case (b), the interface width on the time scale stays constant but the true resolution on the depth scale varies with preferential sputtering. For similar order of magnitude of the atomic mixing and the roughness parameters, a transition state between the two extremes is obtained. While the normalized intensity profile of SIMS represents that of the surface concentration, an additional broadening effect is encountered in XPS or AES by the influence of the mean electron escape depth which may even cause an additional matrix effect at the interface.

Depth resolution and preferential sputtering in depth profiling of sharp interfaces

Energy Technology Data Exchange (ETDEWEB)

Hofmann, S. [Max Planck Institute for Intelligent Systems (formerly MPI for Metals Research), Heisenbergstrasse 3, D-70569 Stuttgart (Germany); Han, Y.S. [Department of Physics, Shantou University, 243 Daxue Road, Shantou, 515063 Guangdong (China); Wang, J.Y., E-mail: wangjy@stu.edu.cn [Department of Physics, Shantou University, 243 Daxue Road, Shantou, 515063 Guangdong (China)

2017-07-15

Highlights: • Interfacial depth resolution from MRI model depends on sputtering rate differences. • Depth resolution critically depends on the dominance of roughness or atomic mixing. • True (depth scale) and apparent (time scale) depth resolutions are different. • Average sputtering rate approximately yields true from apparent depth resolution. • Profiles by SIMS and XPS are different but similar to surface concentrations. - Abstract: The influence of preferential sputtering on depth resolution of sputter depth profiles is studied for different sputtering rates of the two components at an A/B interface. Surface concentration and intensity depth profiles on both the sputtering time scale (as measured) and the depth scale are obtained by calculations with an extended Mixing-Roughness-Information depth (MRI)-model. The results show a clear difference for the two extreme cases (a) preponderant roughness and (b) preponderant atomic mixing. In case (a), the interface width on the time scale (Δt(16–84%)) increases with preferential sputtering if the faster sputtering component is on top of the slower sputtering component, but the true resolution on the depth scale (Δz(16–84%)) stays constant. In case (b), the interface width on the time scale stays constant but the true resolution on the depth scale varies with preferential sputtering. For similar order of magnitude of the atomic mixing and the roughness parameters, a transition state between the two extremes is obtained. While the normalized intensity profile of SIMS represents that of the surface concentration, an additional broadening effect is encountered in XPS or AES by the influence of the mean electron escape depth which may even cause an additional matrix effect at the interface.

Brain Computer Interface on Track to Home

OpenAIRE

Miralles, Felip; Vargiu, Eloisa; Dauwalder, Stefan; Solà, Marc; Müller-Putz, Gernot; Wriessnegger, Selina C.; Pinegger, Andreas; Kübler, Andrea; Halder, Sebastian; Käthner, Ivo; Martin, Suzanne; Daly, Jean; Armstrong, Elaine; Guger, Christoph; Hintermüller, Christoph

2015-01-01

The novel BackHome system offers individuals with disabilities a range of useful services available via brain-computer interfaces (BCIs), to help restore their independence. This is the time such technology is ready to be deployed in the real world, that is, at the target end users' home. This has been achieved by the development of practical electrodes, easy to use software, and delivering telemonitoring and home support capabilities which have been conceived, implemented, and tested within ...

Microfluidic electrochemical device and process for chemical imaging and electrochemical analysis at the electrode-liquid interface in-situ

Science.gov (United States)

Yu, Xiao-Ying; Liu, Bingwen; Yang, Li; Zhu, Zihua; Marshall, Matthew J.

2016-03-01

A microfluidic electrochemical device and process are detailed that provide chemical imaging and electrochemical analysis under vacuum at the surface of the electrode-sample or electrode-liquid interface in-situ. The electrochemical device allows investigation of various surface layers including diffuse layers at selected depths populated with, e.g., adsorbed molecules in which chemical transformation in electrolyte solutions occurs.

Multidimensional control using a mobile-phone based brain-muscle-computer interface.

Science.gov (United States)

Vernon, Scott; Joshi, Sanjay S

2011-01-01

Many well-known brain-computer interfaces measure signals at the brain, and then rely on the brain's ability to learn via operant conditioning in order to control objects in the environment. In our lab, we have been developing brain-muscle-computer interfaces, which measure signals at a single muscle and then rely on the brain's ability to learn neuromuscular skills via operant conditioning. Here, we report a new mobile-phone based brain-muscle-computer interface prototype for severely paralyzed persons, based on previous results from our group showing that humans may actively create specified power levels in two separate frequency bands of a single sEMG signal. Electromyographic activity on the surface of a single face muscle (Auricularis superior) is recorded with a standard electrode. This analog electrical signal is imported into an Android-based mobile phone. User-modulated power in two separate frequency band serves as two separate and simultaneous control channels for machine control. After signal processing, the Android phone sends commands to external devices via Bluetooth. Users are trained to use the device via biofeedback, with simple cursor-to-target activities on the phone screen.

A brain-computer interface to support functional recovery

DEFF Research Database (Denmark)

Kjaer, Troels W; Sørensen, Helge Bjarup Dissing

2013-01-01

Brain-computer interfaces (BCI) register changes in brain activity and utilize this to control computers. The most widely used method is based on registration of electrical signals from the cerebral cortex using extracranially placed electrodes also called electroencephalography (EEG). The features...... extracted from the EEG may, besides controlling the computer, also be fed back to the patient for instance as visual input. This facilitates a learning process. BCI allow us to utilize brain activity in the rehabilitation of patients after stroke. The activity of the cerebral cortex varies with the type...... of movement we imagine, and by letting the patient know the type of brain activity best associated with the intended movement the rehabilitation process may be faster and more efficient. The focus of BCI utilization in medicine has changed in recent years. While we previously focused on devices facilitating...

Thermoelectric energy recovery at ionic-liquid/electrode interface

Energy Technology Data Exchange (ETDEWEB)

Bonetti, Marco; Nakamae, Sawako; Huang, Bo Tao; Wiertel-Gasquet, Cécile; Roger, Michel [Service de Physique de l’Etat Condensé, CEA-IRAMIS-SPEC, CNRS-UMR 3680, CEA Saclay, F-91191 Gif-sur-Yvette Cedex (France); Salez, Thomas J. [Service de Physique de l’Etat Condensé, CEA-IRAMIS-SPEC, CNRS-UMR 3680, CEA Saclay, F-91191 Gif-sur-Yvette Cedex (France); École des Ponts ParisTech, 6 et 8 avenue Blaise Pascal, Champs-sur-Marne, F-77455 Marne-la-Vallée (France)

2015-06-28

A thermally chargeable capacitor containing a binary solution of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)-imide in acetonitrile is electrically charged by applying a temperature gradient to two ideally polarisable electrodes. The corresponding thermoelectric coefficient is −1.7 mV/K for platinum foil electrodes and −0.3 mV/K for nanoporous carbon electrodes. Stored electrical energy is extracted by discharging the capacitor through a resistor. The measured capacitance of the electrode/ionic-liquid interface is 5 μF for each platinum electrode while it becomes four orders of magnitude larger, ≈36 mF, for a single nanoporous carbon electrode. Reproducibility of the effect through repeated charging-discharging cycles under a steady-state temperature gradient demonstrates the robustness of the electrical charging process at the liquid/electrode interface. The acceleration of the charging by convective flows is also observed. This offers the possibility to convert waste-heat into electric energy without exchanging electrons between ions and electrodes, in contrast to what occurs in most thermogalvanic cells.

Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface

Science.gov (United States)

Clements, J. M.; Sellers, E. W.; Ryan, D. B.; Caves, K.; Collins, L. M.; Throckmorton, C. S.

2016-12-01

Objective. Dry electrodes have an advantage over gel-based ‘wet’ electrodes by providing quicker set-up time for electroencephalography recording; however, the potentially poorer contact can result in noisier recordings. We examine the impact that this may have on brain-computer interface communication and potential approaches for mitigation. Approach. We present a performance comparison of wet and dry electrodes for use with the P300 speller system in both healthy participants and participants with communication disabilities (ALS and PLS), and investigate the potential for a data-driven dynamic data collection algorithm to compensate for the lower signal-to-noise ratio (SNR) in dry systems. Main results. Performance results from sixteen healthy participants obtained in the standard static data collection environment demonstrate a substantial loss in accuracy with the dry system. Using a dynamic stopping algorithm, performance may have been improved by collecting more data in the dry system for ten healthy participants and eight participants with communication disabilities; however, the algorithm did not fully compensate for the lower SNR of the dry system. An analysis of the wet and dry system recordings revealed that delta and theta frequency band power (0.1-4 Hz and 4-8 Hz, respectively) are consistently higher in dry system recordings across participants, indicating that transient and drift artifacts may be an issue for dry systems. Significance. Using dry electrodes is desirable for reduced set-up time; however, this study demonstrates that online performance is significantly poorer than for wet electrodes for users with and without disabilities. We test a new application of dynamic stopping algorithms to compensate for poorer SNR. Dynamic stopping improved dry system performance; however, further signal processing efforts are likely necessary for full mitigation.

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

Science.gov (United States)

Huggins, Jane E; Guger, Christoph; Allison, Brendan; Anderson, Charles W; Batista, Aaron; Brouwer, Anne-Marie A-M; Brunner, Clemens; Chavarriaga, Ricardo; Fried-Oken, Melanie; Gunduz, Aysegul; Gupta, Disha; Kübler, Andrea; Leeb, Robert; Lotte, Fabien; Miller, Lee E; Müller-Putz, Gernot; Rutkowski, Tomasz; Tangermann, Michael; Thompson, David Edward

2014-01-01

The Fifth International Brain-Computer Interface (BCI) Meeting met June 3-7 th , 2013 at the Asilomar Conference Grounds, Pacific Grove, California. The conference included 19 workshops covering topics in brain-computer interface and brain-machine interface research. Topics included translation of BCIs into clinical use, standardization and certification, types of brain activity to use for BCI, recording methods, the effects of plasticity, special interest topics in BCIs applications, and future BCI directions. BCI research is well established and transitioning to practical use to benefit people with physical impairments. At the same time, new applications are being explored, both for people with physical impairments and beyond. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and high-lighting important issues for future research and development.

How Frequency of Electrosurgical Current and Electrode Size Affect the Depth of Electrocoagulation.

Science.gov (United States)

Taheri, Arash; Mansoori, Parisa; Bahrami, Naeim; Alinia, Hossein; Watkins, Casey E; Feldman, Steven R

2016-02-01

Many factors affect the depth of electrocoagulation. To evaluate the effect of current frequency and electrode size on the depth of electrocoagulation. In this in vitro study, 4 cylindrical electrodes (2, 2.3, 3, and 4 mm) were used to apply 3 electrosurgical currents (0.4, 1.5, and 3 MHz) to bovine liver. Each electrode was placed at different points on the surface of the liver, and energy at various levels and frequencies was delivered to the tissue. Subsequently, cross-sections of the liver were analyzed. Coagulation started at the periphery of the electrode-tissue contact area. With higher energy levels, coagulation spreads to involve the remainder of the contact area. Neither the frequency nor the electrode size had any effect on this coagulation pattern. The frequency of the current also did not show any relation with depth of coagulation; however, there was a direct correlation between the size of the electrode and the depth of coagulation. Larger-tip electrodes provided deeper coagulation compared with finer-tip electrodes.

A Wearable Channel Selection-Based Brain-Computer Interface for Motor Imagery Detection.

Science.gov (United States)

Lo, Chi-Chun; Chien, Tsung-Yi; Chen, Yu-Chun; Tsai, Shang-Ho; Fang, Wai-Chi; Lin, Bor-Shyh

2016-02-06

Motor imagery-based brain-computer interface (BCI) is a communication interface between an external machine and the brain. Many kinds of spatial filters are used in BCIs to enhance the electroencephalography (EEG) features related to motor imagery. The approach of channel selection, developed to reserve meaningful EEG channels, is also an important technique for the development of BCIs. However, current BCI systems require a conventional EEG machine and EEG electrodes with conductive gel to acquire multi-channel EEG signals and then transmit these EEG signals to the back-end computer to perform the approach of channel selection. This reduces the convenience of use in daily life and increases the limitations of BCI applications. In order to improve the above issues, a novel wearable channel selection-based brain-computer interface is proposed. Here, retractable comb-shaped active dry electrodes are designed to measure the EEG signals on a hairy site, without conductive gel. By the design of analog CAR spatial filters and the firmware of EEG acquisition module, the function of spatial filters could be performed without any calculation, and channel selection could be performed in the front-end device to improve the practicability of detecting motor imagery in the wearable EEG device directly or in commercial mobile phones or tablets, which may have relatively low system specifications. Finally, the performance of the proposed BCI is investigated, and the experimental results show that the proposed system is a good wearable BCI system prototype.

Brain-machine and brain-computer interfaces.

Science.gov (United States)

Friehs, Gerhard M; Zerris, Vasilios A; Ojakangas, Catherine L; Fellows, Mathew R; Donoghue, John P

2004-11-01

The idea of connecting the human brain to a computer or machine directly is not novel and its potential has been explored in science fiction. With the rapid advances in the areas of information technology, miniaturization and neurosciences there has been a surge of interest in turning fiction into reality. In this paper the authors review the current state-of-the-art of brain-computer and brain-machine interfaces including neuroprostheses. The general principles and requirements to produce a successful connection between human and artificial intelligence are outlined and the authors' preliminary experience with a prototype brain-computer interface is reported.

Insulating electrodes: a review on biopotential front ends for dielectric skin–electrode interfaces

International Nuclear Information System (INIS)

Spinelli, Enrique; Haberman, Marcelo

2010-01-01

Insulating electrodes, also known as capacitive electrodes, allow acquiring biopotentials without galvanic contact with the body. They operate with displacement currents instead of real charge currents, and the electrolytic electrode–skin interface is replaced by a dielectric film. The use of insulating electrodes is not the end of electrode interface problems but the beginning of new ones: coupling capacitances are of the order of pF calling for ultra-high input impedance amplifiers and careful biasing, guarding and shielding techniques. In this work, the general requirements of front ends for capacitive electrodes are presented and the different contributions to the overall noise are discussed and estimated. This analysis yields that noise bounds depend on features of the available devices as current and voltage noise, but the final noise level also depends on parasitic capacitances, requiring a careful shield and printed circuit design. When the dielectric layer is placed on the skin, the present-day amplifiers allow achieving noise levels similar to those provided by wet electrodes. Furthermore, capacitive electrode technology allows acquiring high quality ECG signals through thin clothes. A prototype front end for capacitive electrodes was built and tested. ECG signals were acquired with these electrodes in direct contact with the skin and also through cotton clothes 350 µm thick. They were compared with simultaneously acquired signals by means of wet electrodes and no significant differences were observed between both output signals

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.

PET Mapping for Brain-Computer Interface Stimulation of the Ventroposterior Medial Nucleus of the Thalamus in Rats with Implanted Electrodes.

Science.gov (United States)

Zhu, Yunqi; Xu, Kedi; Xu, Caiyun; Zhang, Jiacheng; Ji, Jianfeng; Zheng, Xiaoxiang; Zhang, Hong; Tian, Mei

2016-07-01

Brain-computer interface (BCI) technology has great potential for improving the quality of life for neurologic patients. This study aimed to use PET mapping for BCI-based stimulation in a rat model with electrodes implanted in the ventroposterior medial (VPM) nucleus of the thalamus. PET imaging studies were conducted before and after stimulation of the right VPM. Stimulation induced significant orienting performance. (18)F-FDG uptake increased significantly in the paraventricular thalamic nucleus, septohippocampal nucleus, olfactory bulb, left crus II of the ansiform lobule of the cerebellum, and bilaterally in the lateral septum, amygdala, piriform cortex, endopiriform nucleus, and insular cortex, but it decreased in the right secondary visual cortex, right simple lobule of the cerebellum, and bilaterally in the somatosensory cortex. This study demonstrated that PET mapping after VPM stimulation can identify specific brain regions associated with orienting performance. PET molecular imaging may be an important approach for BCI-based research and its clinical applications. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Evaluation of high-perimeter electrode designs for deep brain stimulation

Science.gov (United States)

Howell, Bryan; Grill, Warren M.

2014-08-01

Objective. Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, complications including infections and mis-programing following surgical replacement of the battery-powered implantable pulse generator adversely impact the safety profile of this therapy. We sought to decrease power consumption and extend battery life by modifying the electrode geometry to increase stimulation efficiency. The specific goal of this study was to determine whether electrode contact perimeter or area had a greater effect on increasing stimulation efficiency. Approach. Finite-element method (FEM) models of eight prototype electrode designs were used to calculate the electrode access resistance, and the FEM models were coupled with cable models of passing axons to quantify stimulation efficiency. We also measured in vitro the electrical properties of the prototype electrode designs and measured in vivo the stimulation efficiency following acute implantation in anesthetized cats. Main results. Area had a greater effect than perimeter on altering the electrode access resistance; electrode (access or dynamic) resistance alone did not predict stimulation efficiency because efficiency was dependent on the shape of the potential distribution in the tissue; and, quantitative assessment of stimulation efficiency required consideration of the effects of the electrode-tissue interface impedance. Significance. These results advance understanding of the features of electrode geometry that are important for designing the next generation of efficient DBS electrodes.

Energy band alignment at ferroelectric/electrode interface determined by photoelectron spectroscopy

International Nuclear Information System (INIS)

Chen Feng; Wu Wen-Bin; Li Shun-Yi; Klein Andreas

2014-01-01

The most important interface-related quantities determined by band alignment are the barrier heights for charge transport, given by the Fermi level position at the interface. Taking Pb(Zr,Ti)O 3 (PZT) as a typical ferroelectric material and applying X-ray photoelectron spectroscopy (XPS), we briefly review the interface formation and barrier heights at the interfaces between PZT and electrodes made of various metals or conductive oxides. Polarization dependence of the Schottky barrier height at a ferroelectric/electrode interface is also directly observed using XPS. (topical review - magnetism, magnetic materials, and interdisciplinary research)

Feasibility of imaging epileptic seizure onset with EIT and depth electrodes.

Science.gov (United States)

Witkowska-Wrobel, Anna; Aristovich, Kirill; Faulkner, Mayo; Avery, James; Holder, David

2018-06-01

Imaging ictal and interictal activity with Electrical Impedance Tomography (EIT) using intracranial electrode mats has been demonstrated in animal models of epilepsy. In human epilepsy subjects undergoing presurgical evaluation, depth electrodes are often preferred. The purpose of this work was to evaluate the feasibility of using EIT to localise epileptogenic areas with intracranial electrodes in humans. The accuracy of localisation of the ictal onset zone was evaluated in computer simulations using 9M element FEM models derived from three subjects. 5 mm radius perturbations imitating a single seizure onset event were placed in several locations forming two groups: under depth electrode coverage and in the contralateral hemisphere. Simulations were made for impedance changes of 1% expected for neuronal depolarisation over milliseconds and 10% for cell swelling over seconds. Reconstructions were compared with EEG source modelling for a radially orientated dipole with respect to the closest EEG recording contact. The best accuracy of EIT was obtained using all depth and 32 scalp electrodes, greater than the equivalent accuracy with EEG inverse source modelling. The localisation error was 5.2 ± 1.8, 4.3 ± 0 and 46.2 ± 25.8 mm for perturbations within the volume enclosed by depth electrodes and 29.6 ± 38.7, 26.1 ± 36.2, 54.0 ± 26.2 mm for those without (EIT 1%, 10% change, EEG source modelling, n = 15 in 3 subjects, p EIT was insensitive to source dipole orientation, all 15 perturbations within the volume enclosed by depth electrodes were localised, whereas the standard clinical method of visual inspection of EEG voltages, only localised 8 out of 15 cases. This suggests that adding EIT to SEEG measurements could be beneficial in localising the onset of seizures. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Identifying cochlear implant channels with poor electrode-neuron interfaces: electrically evoked auditory brain stem responses measured with the partial tripolar configuration.

Science.gov (United States)

Bierer, Julie Arenberg; Faulkner, Kathleen F; Tremblay, Kelly L

2011-01-01

The goal of this study was to compare cochlear implant behavioral measures and electrically evoked auditory brain stem responses (EABRs) obtained with a spatially focused electrode configuration. It has been shown previously that channels with high thresholds, when measured with the tripolar configuration, exhibit relatively broad psychophysical tuning curves. The elevated threshold and degraded spatial/spectral selectivity of such channels are consistent with a poor electrode-neuron interface, defined as suboptimal electrode placement or reduced nerve survival. However, the psychophysical methods required to obtain these data are time intensive and may not be practical during a clinical mapping session, especially for young children. Here, we have extended the previous investigation to determine whether a physiological approach could provide a similar assessment of channel functionality. We hypothesized that, in accordance with the perceptual measures, higher EABR thresholds would correlate with steeper EABR amplitude growth functions, reflecting a degraded electrode-neuron interface. Data were collected from six cochlear implant listeners implanted with the HiRes 90k cochlear implant (Advanced Bionics). Single-channel thresholds and most comfortable listening levels were obtained for stimuli that varied in presumed electrical field size by using the partial tripolar configuration, for which a fraction of current (σ) from a center active electrode returns through two neighboring electrodes and the remainder through a distant indifferent electrode. EABRs were obtained in each subject for the two channels having the highest and lowest tripolar (σ = 1 or 0.9) behavioral threshold. Evoked potentials were measured with both the monopolar (σ = 0) and a more focused partial tripolar (σ ≥ 0.50) configuration. Consistent with previous studies, EABR thresholds were highly and positively correlated with behavioral thresholds obtained with both the monopolar and partial

Brain-Computer Interfaces in Medicine

Science.gov (United States)

Shih, Jerry J.; Krusienski, Dean J.; Wolpaw, Jonathan R.

2012-01-01

Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroencephalography-based spelling and single-neuron-based device control, researchers have gone on to use electroencephalographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces may also prove useful for rehabilitation after stroke and for other disorders. In the future, they might augment the performance of surgeons or other medical professionals. Brain-computer interface technology is the focus of a rapidly growing research and development enterprise that is greatly exciting scientists, engineers, clinicians, and the public in general. Its future achievements will depend on advances in 3 crucial areas. Brain-computer interfaces need signal-acquisition hardware that is convenient, portable, safe, and able to function in all environments. Brain-computer interface systems need to be validated in long-term studies of real-world use by people with severe disabilities, and effective and viable models for their widespread dissemination must be implemented. Finally, the day-to-day and moment-to-moment reliability of BCI performance must be improved so that it approaches the reliability of natural muscle-based function. PMID:22325364

Electrode replacement does not affect classification accuracy in dual-session use of a passive brain-computer interface for assessing cognitive workload.

Science.gov (United States)

Estepp, Justin R; Christensen, James C

2015-01-01

The passive brain-computer interface (pBCI) framework has been shown to be a very promising construct for assessing cognitive and affective state in both individuals and teams. There is a growing body of work that focuses on solving the challenges of transitioning pBCI systems from the research laboratory environment to practical, everyday use. An interesting issue is what impact methodological variability may have on the ability to reliably identify (neuro)physiological patterns that are useful for state assessment. This work aimed at quantifying the effects of methodological variability in a pBCI design for detecting changes in cognitive workload. Specific focus was directed toward the effects of replacing electrodes over dual sessions (thus inducing changes in placement, electromechanical properties, and/or impedance between the electrode and skin surface) on the accuracy of several machine learning approaches in a binary classification problem. In investigating these methodological variables, it was determined that the removal and replacement of the electrode suite between sessions does not impact the accuracy of a number of learning approaches when trained on one session and tested on a second. This finding was confirmed by comparing to a control group for which the electrode suite was not replaced between sessions. This result suggests that sensors (both neurological and peripheral) may be removed and replaced over the course of many interactions with a pBCI system without affecting its performance. Future work on multi-session and multi-day pBCI system use should seek to replicate this (lack of) effect between sessions in other tasks, temporal time courses, and data analytic approaches while also focusing on non-stationarity and variable classification performance due to intrinsic factors.

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

Description of corrections on electrode polarization impedance using isopotential interface factor

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John Alexander Gomez Sanchez

2012-08-01

Full Text Available In this paper, we propose an equation and define the Isopotential Interface Factor (IIF to quantify the contribution of electrode polarization impedance in two tetrapolar electrode shapes. The first tetrapolar electrode geometry shape was adjacent and the second axial concentric, both probes were made of stainless steel (AISI 304. The experiments were carried out with an impedance analyzer (Solartron 1260 using a frequency range between 0.1 Hz and 8 MHz. Based on a theoretical simplification, the experimental results show a lower value of the IIF in the axial concentric tetrapolar electrode system which caused a lower correction of interface value. The higher value of the IIF in the adjacent electrode system was KEEI (1Hz, 0.28 mS/cm = 1.41 and decreased when the frequency and conductance were increased, whereas in the axial concentric electrode system was KEEI (1Hz, 0.28 mS/cm = 0.08. The average isopotential interface factor throughout the whole range of conductivities and frequencies was 0.23 in the adjacent electrode system and 0.02 in the axial concentric electrode system. The index of inherent electrical anisotropy (IEA was used to present an analysis of electrical anisotropy of biceps brachii muscle in vitro using the corrections of both tetrapolar electrode systems. A higher IEA was present in lower frequency where the variation below 1 kHz was 15 % in adjacent electrode configuration and 26 % in the axial concentric probe with respect to full range. The IIF is then shown that it can be used to describe the quality of an electrode system.

A brain-computer interface to support functional recovery.

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Kjaer, Troels W; Sørensen, Helge B

2013-01-01

Brain-computer interfaces (BCI) register changes in brain activity and utilize this to control computers. The most widely used method is based on registration of electrical signals from the cerebral cortex using extracranially placed electrodes also called electroencephalography (EEG). The features extracted from the EEG may, besides controlling the computer, also be fed back to the patient for instance as visual input. This facilitates a learning process. BCI allow us to utilize brain activity in the rehabilitation of patients after stroke. The activity of the cerebral cortex varies with the type of movement we imagine, and by letting the patient know the type of brain activity best associated with the intended movement the rehabilitation process may be faster and more efficient. The focus of BCI utilization in medicine has changed in recent years. While we previously focused on devices facilitating communication in the rather few patients with locked-in syndrome, much interest is now devoted to the therapeutic use of BCI in rehabilitation. For this latter group of patients, the device is not intended to be a lifelong assistive companion but rather a 'teacher' during the rehabilitation period. Copyright © 2013 S. Karger AG, Basel.

Brain-computer interfaces

DEFF Research Database (Denmark)

Treder, Matthias S.; Miklody, Daniel; Blankertz, Benjamin

quality measure'. We were able to show that for stimuli close to the perceptual threshold, there was sometimes a discrepancy between overt responses and brain responses, shedding light on subjects using different response criteria (e.g., more liberal or more conservative). To conclude, brain-computer...... of perceptual and cognitive biases. Furthermore, subjects can only report on stimuli if they have a clear percept of them. On the other hand, the electroencephalogram (EEG), the electrical brain activity measured with electrodes on the scalp, is a more direct measure. It allows us to tap into the ongoing neural...... auditory processing stream. In particular, it can tap brain processes that are pre-conscious or even unconscious, such as the earliest brain responses to sounds stimuli in primary auditory cortex. In a series of studies, we used a machine learning approach to show that the EEG can accurately reflect...

Brain machine interfaces combining microelectrode arrays with nanostructured optical biochemical sensors

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Hajj-Hassan, Mohamad; Gonzalez, Timothy; Ghafer-Zadeh, Ebrahim; Chodavarapu, Vamsy; Musallam, Sam; Andrews, Mark

2009-02-01

Neural microelectrodes are an important component of neural prosthetic systems which assist paralyzed patients by allowing them to operate computers or robots using their neural activity. These microelectrodes are also used in clinical settings to localize the locus of seizure initiation in epilepsy or to stimulate sub-cortical structures in patients with Parkinson's disease. In neural prosthetic systems, implanted microelectrodes record the electrical potential generated by specific thoughts and relay the signals to algorithms trained to interpret these thoughts. In this paper, we describe novel elongated multi-site neural electrodes that can record electrical signals and specific neural biomarkers and that can reach depths greater than 8mm in the sulcus of non-human primates (monkeys). We hypothesize that additional signals recorded by the multimodal probes will increase the information yield when compared to standard probes that record just electropotentials. We describe integration of optical biochemical sensors with neural microelectrodes. The sensors are made using sol-gel derived xerogel thin films that encapsulate specific biomarker responsive luminophores in their nanostructured pores. The desired neural biomarkers are O2, pH, K+, and Na+ ions. As a prototype, we demonstrate direct-write patterning to create oxygen-responsive xerogel waveguide structures on the neural microelectrodes. The recording of neural biomarkers along with electrical activity could help the development of intelligent and more userfriendly neural prosthesis/brain machine interfaces as well as aid in providing answers to complex brain diseases and disorders.

Electrode replacement does not affect classification accuracy in dual-session use of a passive brain-computer interface for assessing cognitive workload

Directory of Open Access Journals (Sweden)

Justin Ronald Estepp

2015-03-01

Full Text Available The passive brain-computer interface (pBCI framework has been shown to be a very promising construct for assessing cognitive and affective state in both individuals and teams. There is a growing body of work that focuses on solving the challenges of transitioning pBCI systems from the research laboratory environment to practical, everyday use. An interesting issue is what impact methodological variability may have on the ability to reliably identify (neurophysiological patterns that are useful for state assessment. This work aimed at quantifying the effects of methodological variability in a pBCI design for detecting changes in cognitive workload. Specific focus was directed toward the effects of replacing electrodes over dual sessions (thus inducing changes in placement, electromechanical properties, and/or impedance between the electrode and skin surface on the accuracy of several machine learning approaches in a binary classification problem. In investigating these methodological variables, it was determined that the removal and replacement of the electrode suite between sessions does not impact the accuracy of a number of learning approaches when trained on one session and tested on a second. This finding was confirmed by comparing to a control group for which the electrode suite was not replaced between sessions. This result suggests that sensors (both neurological and peripheral may be removed and replaced over the course of many interactions with a pBCI system without affecting its performance. Future work on multi-session and multi-day pBCI system use should seek to replicate this (lack of effect between sessions in other tasks, temporal time courses, and data analytic approaches while also focusing on non-stationarity and variable classification performance due to intrinsic factors.

A Multifunctional Brain-Computer Interface Intended for Home Use: An Evaluation with Healthy Participants and Potential End Users with Dry and Gel-Based Electrodes

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Käthner, Ivo; Halder, Sebastian; Hintermüller, Christoph; Espinosa, Arnau; Guger, Christoph; Miralles, Felip; Vargiu, Eloisa; Dauwalder, Stefan; Rafael-Palou, Xavier; Solà, Marc; Daly, Jean M.; Armstrong, Elaine; Martin, Suzanne; Kübler, Andrea

2017-01-01

Current brain-computer interface (BCIs) software is often tailored to the needs of scientists and technicians and therefore complex to allow for versatile use. To facilitate home use of BCIs a multifunctional P300 BCI with a graphical user interface intended for non-expert set-up and control was designed and implemented. The system includes applications for spelling, web access, entertainment, artistic expression and environmental control. In addition to new software, it also includes new hardware for the recording of electroencephalogram (EEG) signals. The EEG system consists of a small and wireless amplifier attached to a cap that can be equipped with gel-based or dry contact electrodes. The system was systematically evaluated with a healthy sample, and targeted end users of BCI technology, i.e., people with a varying degree of motor impairment tested the BCI in a series of individual case studies. Usability was assessed in terms of effectiveness, efficiency and satisfaction. Feedback of users was gathered with structured questionnaires. Two groups of healthy participants completed an experimental protocol with the gel-based and the dry contact electrodes (N = 10 each). The results demonstrated that all healthy participants gained control over the system and achieved satisfactory to high accuracies with both gel-based and dry electrodes (average error rates of 6 and 13%). Average satisfaction ratings were high, but certain aspects of the system such as the wearing comfort of the dry electrodes and design of the cap, and speed (in both groups) were criticized by some participants. Six potential end users tested the system during supervised sessions. The achieved accuracies varied greatly from no control to high control with accuracies comparable to that of healthy volunteers. Satisfaction ratings of the two end-users that gained control of the system were lower as compared to healthy participants. The advantages and disadvantages of the BCI and its applications

Future developments in brain-machine interface research.

Science.gov (United States)

Lebedev, Mikhail A; Tate, Andrew J; Hanson, Timothy L; Li, Zheng; O'Doherty, Joseph E; Winans, Jesse A; Ifft, Peter J; Zhuang, Katie Z; Fitzsimmons, Nathan A; Schwarz, David A; Fuller, Andrew M; An, Je Hi; Nicolelis, Miguel A L

2011-01-01

Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade, considerable progress has been achieved in this multidisciplinary research, mainly in the brain-machine interface that enacts upper-limb functionality. However, a considerable number of problems need to be resolved before fully functional limb neuroprostheses can be built. To move towards developing neuroprosthetic devices for humans, brain-machine interface research has to address a number of issues related to improving the quality of neuronal recordings, achieving stable, long-term performance, and extending the brain-machine interface approach to a broad range of motor and sensory functions. Here, we review the future steps that are part of the strategic plan of the Duke University Center for Neuroengineering, and its partners, the Brazilian National Institute of Brain-Machine Interfaces and the École Polytechnique Fédérale de Lausanne (EPFL) Center for Neuroprosthetics, to bring this new technology to clinical fruition.

Future developments in brain-machine interface research

Directory of Open Access Journals (Sweden)

Mikhail A. Lebedev

2011-01-01

Full Text Available Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade, considerable progress has been achieved in this multidisciplinary research, mainly in the brain-machine interface that enacts upper-limb functionality. However, a considerable number of problems need to be resolved before fully functional limb neuroprostheses can be built. To move towards developing neuroprosthetic devices for humans, brain-machine interface research has to address a number of issues related to improving the quality of neuronal recordings, achieving stable, long-term performance, and extending the brain-machine interface approach to a broad range of motor and sensory functions. Here, we review the future steps that are part of the strategic plan of the Duke University Center for Neuroengineering, and its partners, the Brazilian National Institute of Brain-Machine Interfaces and the École Polytechnique Fédérale de Lausanne (EPFL Center for Neuroprosthetics, to bring this new technology to clinical fruition.

Finite difference time domain (FDTD) modeling of implanted deep brain stimulation electrodes and brain tissue.

Science.gov (United States)

Gabran, S R I; Saad, J H; Salama, M M A; Mansour, R R

2009-01-01

This paper demonstrates the electromagnetic modeling and simulation of an implanted Medtronic deep brain stimulation (DBS) electrode using finite difference time domain (FDTD). The model is developed using Empire XCcel and represents the electrode surrounded with brain tissue assuming homogenous and isotropic medium. The model is created to study the parameters influencing the electric field distribution within the tissue in order to provide reference and benchmarking data for DBS and intra-cortical electrode development.

Electron transfer reactions to probe the electrode/solution interface

Energy Technology Data Exchange (ETDEWEB)

Capitanio, F.; Guerrini, E.; Colombo, A.; Trasatti, S. [Milan Univ., Milan (Italy). Dept. of Physical Chemistry and Electrochemistry

2008-07-01

The reactions that occur at the interface between an electrode and an electrolyte were examined with particular reference to the interaction of different electrode surfaces with redox couples. A semi-integration or convolution technique was used to study the kinetics of electron transfer on different electrode materials with different hydrophilic behaviour, such as Boron-Doped-Diamond (BDD), Au and Pt. Standard reversible redox couples were also investigated, including (Fe3+/2+, Fe(CN)63-/4-, Ru(NH3)63+/2+, Co(NH3)63+/2+, Ir4+/3+, V4+/5+ and V3+/2+). The proposed method proved to be simple, straightforward and reliable since the obtained kinetic information was in good agreement with data in the literature. It was concluded that the kinetics of the electrode transfer reactions depend on the chemical nature of the redox couple and electrode material. The method should be further extended to irreversible couples and other electrode materials such as mixed oxide electrodes. 3 refs., 2 figs.

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.

An implantable integrated low-power amplifier-microelectrode array for Brain-Machine Interfaces.

Science.gov (United States)

Patrick, Erin; Sankar, Viswanath; Rowe, William; Sanchez, Justin C; Nishida, Toshikazu

2010-01-01

One of the important challenges in designing Brain-Machine Interfaces (BMI) is to build implantable systems that have the ability to reliably process the activity of large ensembles of cortical neurons. In this paper, we report the design, fabrication, and testing of a polyimide-based microelectrode array integrated with a low-power amplifier as part of the Florida Wireless Integrated Recording Electrode (FWIRE) project at the University of Florida developing a fully implantable neural recording system for BMI applications. The electrode array was fabricated using planar micromachining MEMS processes and hybrid packaged with the amplifier die using a flip-chip bonding technique. The system was tested both on bench and in-vivo. Acute and chronic neural recordings were obtained from a rodent for a period of 42 days. The electrode-amplifier performance was analyzed over the chronic recording period with the observation of a noise floor of 4.5 microVrms, and an average signal-to-noise ratio of 3.8.

Impedance spectroscopy of tripolar concentric ring electrodes with Ten20 and TD246 pastes.

Science.gov (United States)

Nasrollaholhosseini, Seyed Hadi; Herrera, Daniel Salazar; Besio, Walter G

2017-07-01

Electrodes are used to transform ionic currents to electrical currents in biological systems. Modeling the electrode-electrolyte interface could help to optimize the performance of the electrode interface to achieve higher signal to noise ratios. There are previous reports of accurate models for single-element biomedical electrodes. In this paper, we measured the impedance on both tripolar concentric ring electrodes and standard cup electrodes by electrochemical impedance spectroscopy (EIS) using both Ten20 and TD246 electrode paste. Furthermore, we applied the model to prove that the model can predict the performance of the electrode-electrolyte interface for tripolar concentric ring electrodes (TCRE) that are used to record brain signals.

Assessing the Electrode-Neuron Interface with the Electrically Evoked Compound Action Potential, Electrode Position, and Behavioral Thresholds.

Science.gov (United States)

DeVries, Lindsay; Scheperle, Rachel; Bierer, Julie Arenberg

2016-06-01

Variability in speech perception scores among cochlear implant listeners may largely reflect the variable efficacy of implant electrodes to convey stimulus information to the auditory nerve. In the present study, three metrics were applied to assess the quality of the electrode-neuron interface of individual cochlear implant channels: the electrically evoked compound action potential (ECAP), the estimation of electrode position using computerized tomography (CT), and behavioral thresholds using focused stimulation. The primary motivation of this approach is to evaluate the ECAP as a site-specific measure of the electrode-neuron interface in the context of two peripheral factors that likely contribute to degraded perception: large electrode-to-modiolus distance and reduced neural density. Ten unilaterally implanted adults with Advanced Bionics HiRes90k devices participated. ECAPs were elicited with monopolar stimulation within a forward-masking paradigm to construct channel interaction functions (CIF), behavioral thresholds were obtained with quadrupolar (sQP) stimulation, and data from imaging provided estimates of electrode-to-modiolus distance and scalar location (scala tympani (ST), intermediate, or scala vestibuli (SV)) for each electrode. The width of the ECAP CIF was positively correlated with electrode-to-modiolus distance; both of these measures were also influenced by scalar position. The ECAP peak amplitude was negatively correlated with behavioral thresholds. Moreover, subjects with low behavioral thresholds and large ECAP amplitudes, averaged across electrodes, tended to have higher speech perception scores. These results suggest a potential clinical role for the ECAP in the objective assessment of individual cochlear implant channels, with the potential to improve speech perception outcomes.

Faradic resistance of the electrode/electrolyte interface.

Science.gov (United States)

Mayer, S; Geddes, L A; Bourland, J D; Ogborn, L

1992-09-01

A new method is used to measure the direct-current (Faradic) resistance of a single electrode/electrolyte interface. The method employs a constant-current pulse and a potential-sensing electrode. By choosing a sufficiently long pulse duration, the voltage between the test and potential-sensing electrode exhibits a three-phase response. In the steady-state phase, the voltage measured is equal to the current flowing through the electrode Faradic resistance and the resistance of the electrolyte between the test and potential-sensing electrode. By measuring this latter resistance with a high-frequency sinusoidal alternating current, the voltage drop in the electrolyte is calculated and subtracted from the voltage measured between the test and potential-sensing electrode, thereby allowing calculation of the Faradic resistance. By plotting the reciprocal of the Faradic resistance against current density and fitting the data points to a third-order polynomial, it is possible to determine the zero-current density (Faradic) resistance. This technique was used to determine the Faradic resistance of electrodes (0.1 cm2) of stainless-steel, platinum, platinum-iridium and rhodium in 0.9 per cent NaCl at 25 degrees. The zero current Faradic resistance is lowest for platinum (30.3 k omega), slightly higher for platinum-iridium (47.6k omega), much higher for rhodium (111k omega) and highest for type 316 stainless-steel (345k omega). In all cases, the Faradic resistance decreases dramatically with increasing current density.

Development of a Compact Wireless Laplacian Electrode Module for Electromyograms and Its Human Interface Applications

Directory of Open Access Journals (Sweden)

Akira Ichikawa

2013-02-01

Full Text Available In this study, we developed a compact wireless Laplacian electrode module for electromyograms (EMGs. One of the advantages of the Laplacian electrode configuration is that EMGs obtained with it are expected to be sensitive to the firing of the muscle directly beneath the measurement site. The performance of the developed electrode module was investigated in two human interface applications: character-input interface and detection of finger movement during finger Braille typing. In the former application, the electrode module was combined with an EMG-mouse click converter circuit. In the latter, four electrode modules were used for detection of finger movements during finger Braille typing. Investigation on the character-input interface indicated that characters could be input stably by contraction of (a the masseter, (b trapezius, (c anterior tibialis and (d flexor carpi ulnaris muscles. This wide applicability is desirable when the interface is applied to persons with physical disabilities because the disability differs one to another. The investigation also demonstrated that the electrode module can work properly without any skin preparation. Finger movement detection experiments showed that each finger movement was more clearly detectable when comparing to EMGs recorded with conventional electrodes, suggesting that the Laplacian electrode module is more suitable for detecting the timing of finger movement during typing. This could be because the Laplacian configuration enables us to record EMGs just beneath the electrode. These results demonstrate the advantages of the Laplacian electrode module.

Universal electrode interface for electrocatalytic oxidation of liquid fuels.

Science.gov (United States)

Liao, Hualing; Qiu, Zhipeng; Wan, Qijin; Wang, Zhijie; Liu, Yi; Yang, Nianjun

2014-10-22

Electrocatalytic oxidations of liquid fuels from alcohols, carboxylic acids, and aldehydes were realized on a universal electrode interface. Such an interface was fabricated using carbon nanotubes (CNTs) as the catalyst support and palladium nanoparticles (Pd NPs) as the electrocatalysts. The Pd NPs/CNTs nanocomposite was synthesized using the ethylene glycol reduction method. It was characterized using transmission electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, voltammetry, and impedance. On the Pd NPs/CNTs nanocomposite coated electrode, the oxidations of those liquid fuels occur similarly in two steps: the oxidations of freshly chemisorbed species in the forward (positive-potential) scan and then, in the reverse scan (negative-potential), the oxidations of the incompletely oxidized carbonaceous species formed during the forward scan. The oxidation charges were adopted to study their oxidation mechanisms and oxidation efficiencies. The oxidation efficiency follows the order of aldehyde (formaldehyde) > carboxylic acid (formic acid) > alcohols (ethanol > methanol > glycol > propanol). Such a Pd NPs/CNTs nanocomposite coated electrode is thus promising to be applied as the anode for the facilitation of direct fuel cells.

Simultaneous recording of fluorescence and electrical signals by photometric patch electrode in deep brain regions in vivo.

Science.gov (United States)

Hirai, Yasuharu; Nishino, Eri; Ohmori, Harunori

2015-06-01

Despite its widespread use, high-resolution imaging with multiphoton microscopy to record neuronal signals in vivo is limited to the surface of brain tissue because of limited light penetration. Moreover, most imaging studies do not simultaneously record electrical neural activity, which is, however, crucial to understanding brain function. Accordingly, we developed a photometric patch electrode (PME) to overcome the depth limitation of optical measurements and also enable the simultaneous recording of neural electrical responses in deep brain regions. The PME recoding system uses a patch electrode to excite a fluorescent dye and to measure the fluorescence signal as a light guide, to record electrical signal, and to apply chemicals to the recorded cells locally. The optical signal was analyzed by either a spectrometer of high light sensitivity or a photomultiplier tube depending on the kinetics of the responses. We used the PME in Oregon Green BAPTA-1 AM-loaded avian auditory nuclei in vivo to monitor calcium signals and electrical responses. We demonstrated distinct response patterns in three different nuclei of the ascending auditory pathway. On acoustic stimulation, a robust calcium fluorescence response occurred in auditory cortex (field L) neurons that outlasted the electrical response. In the auditory midbrain (inferior colliculus), both responses were transient. In the brain-stem cochlear nucleus magnocellularis, calcium response seemed to be effectively suppressed by the activity of metabotropic glutamate receptors. In conclusion, the PME provides a powerful tool to study brain function in vivo at a tissue depth inaccessible to conventional imaging devices. Copyright © 2015 the American Physiological Society.

Nanoscale heterogeneity at the aqueous electrolyte-electrode interface

Science.gov (United States)

Limmer, David T.; Willard, Adam P.

2015-01-01

Using molecular dynamics simulations, we reveal emergent properties of hydrated electrode interfaces that while molecular in origin are integral to the behavior of the system across long times scales and large length scales. Specifically, we describe the impact of a disordered and slowly evolving adsorbed layer of water on the molecular structure and dynamics of the electrolyte solution adjacent to it. Generically, we find that densities and mobilities of both water and dissolved ions are spatially heterogeneous in the plane parallel to the electrode over nanosecond timescales. These and other recent results are analyzed in the context of available experimental literature from surface science and electrochemistry. We speculate on the implications of this emerging microscopic picture on the catalytic proficiency of hydrated electrodes, offering a new direction for study in heterogeneous catalysis at the nanoscale.

A Fast Inspection of Tool Electrode and Drilling Depth in EDM Drilling by Detection Line Algorithm.

Science.gov (United States)

Huang, Kuo-Yi

2008-08-21

The purpose of this study was to develop a novel measurement method using a machine vision system. Besides using image processing techniques, the proposed system employs a detection line algorithm that detects the tool electrode length and drilling depth of a workpiece accurately and effectively. Different boundaries of areas on the tool electrode are defined: a baseline between base and normal areas, a ND-line between normal and drilling areas (accumulating carbon area), and a DD-line between drilling area and dielectric fluid droplet on the electrode tip. Accordingly, image processing techniques are employed to extract a tool electrode image, and the centroid, eigenvector, and principle axis of the tool electrode are determined. The developed detection line algorithm (DLA) is then used to detect the baseline, ND-line, and DD-line along the direction of the principle axis. Finally, the tool electrode length and drilling depth of the workpiece are estimated via detected baseline, ND-line, and DD-line. Experimental results show good accuracy and efficiency in estimation of the tool electrode length and drilling depth under different conditions. Hence, this research may provide a reference for industrial application in EDM drilling measurement.

Competing and collaborating brains: multi-brain computer interfacing

NARCIS (Netherlands)

Nijholt, Antinus; Hassanieu, Aboul Ella; Azar, Ahmad Taher

2015-01-01

In this chapter we survey the possibilities of brain-computer interface applications that assume two or more users, where at least one of the users’ brain activity is used as input to the application. Such ‘applications’ were already explored by artists who introduced artistic EEG applications in

Improved ceramic anodes for SOFCs with modified electrode/electrolyte interface

DEFF Research Database (Denmark)

Abdul Jabbar, Mohammed Hussain; Høgh, Jens Valdemar Thorvald; Zhang, Wei

2012-01-01

The electrode performance of solid oxide fuel cell anode with Pd nanoparticles at the interface of ScYSZ electrolyte and Sr0.94Ti0.9Nb0.1O3 (STN) electrode introduced in the form of metal functional layer have been investigated at temperatures below 600 °C. A metal functional layer consisting of Pd...... was deposited by magnetron sputtering. Effecting from heat treatments, Pd nanoparticles with particle sizes in the range of 5–20 nm were distributed at the interface, and throughout the backbone. The polarization resistance of the modified STN reduced to 30 Ωcm2 at 600 °C, which is three times less than...... an unmodified STN backbone. In order to improve the anode performance further, Pd and Gd-doped CeO2 electrocatalysts were infiltrated into the STN backbone. The modified interface with Pd nanoparticles in combination with nanostructured electrocatalyst by infiltration resulted in polarisation resistances of 0...

Experiencing Brain-Computer Interface Control

NARCIS (Netherlands)

van de Laar, B.L.A.

2016-01-01

Brain-Computer Interfaces (BCIs) are systems that extract information from the user’s brain activity and employ it in some way in an interactive system. While historically BCIs were mainly catered towards paralyzed or otherwise physically handicapped users, the last couple of years applications with

Control of a visual keyboard using an electrocorticographic brain-computer interface.

Science.gov (United States)

Krusienski, Dean J; Shih, Jerry J

2011-05-01

Brain-computer interfaces (BCIs) are devices that enable severely disabled people to communicate and interact with their environments using their brain waves. Most studies investigating BCI in humans have used scalp EEG as the source of electrical signals and focused on motor control of prostheses or computer cursors on a screen. The authors hypothesize that the use of brain signals obtained directly from the cortical surface will more effectively control a communication/spelling task compared to scalp EEG. A total of 6 patients with medically intractable epilepsy were tested for the ability to control a visual keyboard using electrocorticographic (ECOG) signals. ECOG data collected during a P300 visual task paradigm were preprocessed and used to train a linear classifier to subsequently predict the intended target letters. The classifier was able to predict the intended target character at or near 100% accuracy using fewer than 15 stimulation sequences in 5 of the 6 people tested. ECOG data from electrodes outside the language cortex contributed to the classifier and enabled participants to write words on a visual keyboard. This is a novel finding because previous invasive BCI research in humans used signals exclusively from the motor cortex to control a computer cursor or prosthetic device. These results demonstrate that ECOG signals from electrodes both overlying and outside the language cortex can reliably control a visual keyboard to generate language output without voice or limb movements.

Non-invasive brain-to-brain interface (BBI: establishing functional links between two brains.

Directory of Open Access Journals (Sweden)

Seung-Schik Yoo

Full Text Available Transcranial focused ultrasound (FUS is capable of modulating the neural activity of specific brain regions, with a potential role as a non-invasive computer-to-brain interface (CBI. In conjunction with the use of brain-to-computer interface (BCI techniques that translate brain function to generate computer commands, we investigated the feasibility of using the FUS-based CBI to non-invasively establish a functional link between the brains of different species (i.e. human and Sprague-Dawley rat, thus creating a brain-to-brain interface (BBI. The implementation was aimed to non-invasively translate the human volunteer's intention to stimulate a rat's brain motor area that is responsible for the tail movement. The volunteer initiated the intention by looking at a strobe light flicker on a computer display, and the degree of synchronization in the electroencephalographic steady-state-visual-evoked-potentials (SSVEP with respect to the strobe frequency was analyzed using a computer. Increased signal amplitude in the SSVEP, indicating the volunteer's intention, triggered the delivery of a burst-mode FUS (350 kHz ultrasound frequency, tone burst duration of 0.5 ms, pulse repetition frequency of 1 kHz, given for 300 msec duration to excite the motor area of an anesthetized rat transcranially. The successful excitation subsequently elicited the tail movement, which was detected by a motion sensor. The interface was achieved at 94.0±3.0% accuracy, with a time delay of 1.59±1.07 sec from the thought-initiation to the creation of the tail movement. Our results demonstrate the feasibility of a computer-mediated BBI that links central neural functions between two biological entities, which may confer unexplored opportunities in the study of neuroscience with potential implications for therapeutic applications.

Fractal Interfaces for Stimulating and Recording Neural Implants

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Watterson, William James

From investigating movement in an insect to deciphering cognition in a human brain to treating Parkinson's disease, hearing loss, or even blindness, electronic implants are an essential tool for understanding the brain and treating neural diseases. Currently, the stimulating and recording resolution of these implants remains low. For instance, they can record all the neuron activity associated with movement in an insect, but are quite far from recording, at an individual neuron resolution, the large volumes of brain tissue associated with cognition. Likewise, there is remarkable success in the cochlear implant restoring hearing due to the relatively simple anatomy of the auditory nerves, but are failing to restore vision to the blind due to poor signal fidelity and transmission in stimulating the more complex anatomy of the visual nerves. The critically important research needed to improve the resolution of these implants is to optimize the neuron-electrode interface. This thesis explores geometrical and material modifications to both stimulating and recording electrodes which can improve the neuron-electrode interface. First, we introduce a fractal electrode geometry which radically improves the restored visual acuity achieved by retinal implants and leads to safe, long-term operation of the implant. Next, we demonstrate excellent neuron survival and neurite outgrowth on carbon nanotube electrodes, thus providing a safe biomaterial which forms a strong connection between the electrode and neurons. Additional preliminary evidence suggests carbon nanotubes patterned into a fractal geometry will provide further benefits in improving the electrode-neuron interface. Finally, we propose a novel implant based off field effect transistor technology which utilizes an interconnecting fractal network of semiconducting carbon nanotubes to record from thousands of neurons simutaneously at an individual neuron resolution. Taken together, these improvements have the potential to

Incorporating modern neuroscience findings to improve brain-computer interfaces: tracking auditory attention.

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Wronkiewicz, Mark; Larson, Eric; Lee, Adrian Kc

2016-10-01

Brain-computer interface (BCI) technology allows users to generate actions based solely on their brain signals. However, current non-invasive BCIs generally classify brain activity recorded from surface electroencephalography (EEG) electrodes, which can hinder the application of findings from modern neuroscience research. In this study, we use source imaging-a neuroimaging technique that projects EEG signals onto the surface of the brain-in a BCI classification framework. This allowed us to incorporate prior research from functional neuroimaging to target activity from a cortical region involved in auditory attention. Classifiers trained to detect attention switches performed better with source imaging projections than with EEG sensor signals. Within source imaging, including subject-specific anatomical MRI information (instead of using a generic head model) further improved classification performance. This source-based strategy also reduced accuracy variability across three dimensionality reduction techniques-a major design choice in most BCIs. Our work shows that source imaging provides clear quantitative and qualitative advantages to BCIs and highlights the value of incorporating modern neuroscience knowledge and methods into BCI systems.

Modeling the electrode-neuron interface of cochlear implants: effects of neural survival, electrode placement, and the partial tripolar configuration.

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Goldwyn, Joshua H; Bierer, Steven M; Bierer, Julie Arenberg

2010-09-01

The partial tripolar electrode configuration is a relatively novel stimulation strategy that can generate more spatially focused electric fields than the commonly used monopolar configuration. Focused stimulation strategies should improve spectral resolution in cochlear implant users, but may also be more sensitive to local irregularities in the electrode-neuron interface. In this study, we develop a practical computer model of cochlear implant stimulation that can simulate neural activation in a simplified cochlear geometry and we relate the resulting patterns of neural activity to basic psychophysical measures. We examine how two types of local irregularities in the electrode-neuron interface, variations in spiral ganglion nerve density and electrode position within the scala tympani, affect the simulated neural activation patterns and how these patterns change with electrode configuration. The model shows that higher partial tripolar fractions activate more spatially restricted populations of neurons at all current levels and require higher current levels to excite a given number of neurons. We find that threshold levels are more sensitive at high partial tripolar fractions to both types of irregularities, but these effects are not independent. In particular, at close electrode-neuron distances, activation is typically more spatially localized which leads to a greater influence of neural dead regions. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Engineering the Membrane/Electrode Interface To Improve the Performance of Solid-State Supercapacitors.

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Huang, Chun; Zhang, Jin; Snaith, Henry J; Grant, Patrick S

2016-08-17

This paper investigates the effect of adding a 450 nm layer based on porous TiO2 at the interface between a 4.5 μm carbon/TiO2 nanoparticle-based electrode and a polymer electrolyte membrane as a route to improve energy storage performance in solid-state supercapacitors. Electrochemical characterization showed that adding the interface layer reduced charge transfer resistance, promoted more efficient ion transfer across the interface, and significantly improved charge/discharge dynamics in a solid-state supercapacitor, resulting in an increased areal capacitance from 45.3 to 111.1 mF cm(-2) per electrode at 0.4 mA cm(-2).

Robot-assisted placement of depth electrodes along the long Axis of the amygdalohippocampal complex

Directory of Open Access Journals (Sweden)

Alvin Y. Chan

2016-12-01

Conclusions: We have developed the Robot-Assisted Lateral Transoccipital Approach (RALTA, which is an advantageous technique for placing bilateral amygdalohippocampal depth electrodes using robotic guidance. Benefits of this technique include fewer electrodes required per patient and ease of positioning compared with seated or prone positioning.

Fermi level pinning by integer charge transfer at electrode-organic semiconductor interfaces

NARCIS (Netherlands)

Bokdam, Menno; Cakir, Deniz; Brocks, G.

2011-01-01

The atomic structure of interfaces between conducting electrodes and molecular organic materials varies considerably. Yet experiments show that pinning of the Fermi level, which is observed at such interfaces, does not depend upon the structural details. In this letter, we develop a general model to

To what extent can dry and water-based EEG electrodes replace conductive gel ones?: A Steady State Visual Evoked Potential Brain-Computer Interface Case Study

NARCIS (Netherlands)

Mihajlovic, V.; Garcia Molina, G.; Peuscher, J

2011-01-01

Recent technological advances in the field of skin electrodes and on-body sensors indicate a possibility of having an alternative to the traditionally used conductive gel electrodes for measuring electrical signals of the brain (electroencephalogram, EEG). This paper evaluates whether water-based

Brain-muscle-computer interface: mobile-phone prototype development and testing.

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Vernon, Scott; Joshi, Sanjay S

2011-07-01

We report prototype development and testing of a new mobile-phone-based brain-muscle-computer interface for severely paralyzed persons, based on previous results from our group showing that humans may actively create specified power levels in two separate frequency bands of a single surface electromyography (sEMG) signal. EMG activity on the surface of a single face muscle site (auricularis superior) is recorded with a standard electrode. This analog electrical signal is imported into an Android-based mobile phone and digitized via an internal A/D converter. The digital signal is split, and then simultaneously filtered with two band-pass filters to extract total power within two separate frequency bands. The user-modulated power in each frequency band serves as two separate control channels for machine control. After signal processing, the Android phone sends commands to external devices via a Bluetooth interface. Users are trained to use the device via visually based operant conditioning, with simple cursor-to-target activities on the phone screen. The mobile-phone prototype interface is formally evaluated on a single advanced Spinal Muscle Atrophy subject, who has successfully used the interface in his home in evaluation trials and for remote control of a television. Development of this new device will not only guide future interface design for community use, but will also serve as an information technology bridge for in situ data collection to quantify human sEMG manipulation abilities for a relevant population.

Phenomenological theory of current-producing processes at the solid oxide electrolyte/gas electrode interface: steady-state polarization of fuel-cell electrodes

International Nuclear Information System (INIS)

Murygin, I.V.; Chebotin, V.N.

1979-01-01

The polarization of fuel-cell electrodes (mixtures CO + CO 2 and H 2 + H 2 O) in systems with solid oxide electrolytes is discussed. The theory is based upon a process model where the electrode reaction zone can spread along the line of three-phase contact by diffusion of reaction partners and products across the electrolyte/electrode and electrolyte/gas interface

A foldable electrode array for 3D recording of deep-seated abnormal brain cavities

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Kil, Dries; De Vloo, Philippe; Fierens, Guy; Ceyssens, Frederik; Hunyadi, Borbála; Bertrand, Alexander; Nuttin, Bart; Puers, Robert

2018-06-01

Objective. This study describes the design and microfabrication of a foldable thin-film neural implant and investigates its suitability for electrical recording of deep-lying brain cavity walls. Approach. A new type of foldable neural electrode array is presented, which can be inserted through a cannula. The microfabricated electrode is specifically designed for electrical recording of the cavity wall of thalamic lesions resulting from stroke. The proof-of-concept is demonstrated by measurements in rat brain cavities. On implantation, the electrode array unfolds in the brain cavity, contacting the cavity walls and allowing recording at multiple anatomical locations. A three-layer microfabrication process based on UV-lithography and Reactive Ion Etching is described. Electrochemical characterization of the electrode is performed in addition to an in vivo experiment in which the implantation procedure and the unfolding of the electrode are tested and visualized. Main results. Electrochemical characterization validated the suitability of the electrode for in vivo use. CT imaging confirmed the unfolding of the electrode in the brain cavity and analysis of recorded local field potentials showed the ability to record neural signals of biological origin. Significance. The conducted research confirms that it is possible to record neural activity from the inside wall of brain cavities at various anatomical locations after a single implantation procedure. This opens up possibilities towards research of abnormal brain cavities and the clinical conditions associated with them, such as central post-stroke pain.

Activity patterns of cultured neural networks on micro electrode arrays

NARCIS (Netherlands)

Rutten, Wim; van Pelt, J.

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 (ventral motor region or dorsal sensory region). It consists of an array of micro electrodes on

Brain Computer Interfaces for Enhanced Interaction with Mobile Robot Agents

Science.gov (United States)

2016-07-27

SECURITY CLASSIFICATION OF: Brain Computer Interfaces (BCIs) show great potential in allowing humans to interact with computational environments in a...Distribution Unlimited UU UU UU UU 27-07-2016 17-Sep-2013 16-Sep-2014 Final Report: Brain Computer Interfaces for Enhanced Interactions with Mobile Robot...published in peer-reviewed journals: Number of Papers published in non peer-reviewed journals: Final Report: Brain Computer Interfaces for Enhanced

A dry EEG-system for scientific research and brain-computer interfaces

Directory of Open Access Journals (Sweden)

Thorsten Oliver Zander

2011-05-01

Full Text Available Although it ranks among the oldest tools in neuroscientific research, electroencephalography (EEG still forms the method of choice in a wide variety of clinical and research applications. In the context of Brain-Computer Interfacing (BCI, EEG recently has become a tool to enhance Human-Machine Interaction (HMI. EEG could be employed in a wider range of environments, especially for the use of BCI systems in a clinical context or at the homes of patients. However, the application of EEG in these contexts is impeded by the cumbersome preparation of the electrodes with conductive gel that is necessary to lower the impedance between electrodes and scalp. Dry electrodes could provide a solution to this barrier and allow for EEG applications outside the laboratory. In addition, dry electrodes may reduce the time needed for neurological exams in clinical practice. This study evaluates a prototype of a three-channel dry electrode EEG system, comparing it to state-of-the-art conventional EEG electrodes. Two experimental paradigms were used: first, Event-Related Potentials (ERP were investigated with a variant of the oddball paradigm. Second, features of the frequency domain were compared by a paradigm inducing occipital alpha. Furthermore, both paradigms were used to evaluate BCI classification accuracies of both EEG systems. Amplitude and temporal structure of ERPs as well as features in the frequency domain did not differ significantly between the EEG systems. BCI classification accuracies were equally high in both systems when the frequency domain was considered. With respect to the oddball classification accuracy, there were slight differences between the wet and dry electrode systems. We conclude that the tested dry electrodes were capable to detect EEG signals with good quality and that these signals can be used for research or BCI applications. Easy to handle electrodes may help to foster the use of EEG among a wider range of potential users.

Brain-computer interfaces increase whole-brain signal to noise.

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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.

Brain Computer Interface on Track to Home.

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Miralles, Felip; Vargiu, Eloisa; Dauwalder, Stefan; Solà, Marc; Müller-Putz, Gernot; Wriessnegger, Selina C; Pinegger, Andreas; Kübler, Andrea; Halder, Sebastian; Käthner, Ivo; Martin, Suzanne; Daly, Jean; Armstrong, Elaine; Guger, Christoph; Hintermüller, Christoph; Lowish, Hannah

2015-01-01

The novel BackHome system offers individuals with disabilities a range of useful services available via brain-computer interfaces (BCIs), to help restore their independence. This is the time such technology is ready to be deployed in the real world, that is, at the target end users' home. This has been achieved by the development of practical electrodes, easy to use software, and delivering telemonitoring and home support capabilities which have been conceived, implemented, and tested within a user-centred design approach. The final BackHome system is the result of a 3-year long process involving extensive user engagement to maximize effectiveness, reliability, robustness, and ease of use of a home based BCI system. The system is comprised of ergonomic and hassle-free BCI equipment; one-click software services for Smart Home control, cognitive stimulation, and web browsing; and remote telemonitoring and home support tools to enable independent home use for nonexpert caregivers and users. BackHome aims to successfully bring BCIs to the home of people with limited mobility to restore their independence and ultimately improve their quality of life.

Biofuel Cell Based on Microscale Nanostructured Electrodes with Inductive Coupling to Rat Brain Neurons

Science.gov (United States)

Andoralov, Viktor; Falk, Magnus; Suyatin, Dmitry B.; Granmo, Marcus; Sotres, Javier; Ludwig, Roland; Popov, Vladimir O.; Schouenborg, Jens; Blum, Zoltan; Shleev, Sergey

2013-11-01

Miniature, self-contained biodevices powered by biofuel cells may enable a new generation of implantable, wireless, minimally invasive neural interfaces for neurophysiological in vivo studies and for clinical applications. Here we report on the fabrication of a direct electron transfer based glucose/oxygen enzymatic fuel cell (EFC) from genuinely three-dimensional (3D) nanostructured microscale gold electrodes, modified with suitable biocatalysts. We show that the process underlying the simple fabrication method of 3D nanostructured electrodes is based on an electrochemically driven transformation of physically deposited gold nanoparticles. We experimentally demonstrate that mediator-, cofactor-, and membrane-less EFCs do operate in cerebrospinal fluid and in the brain of a rat, producing amounts of electrical power sufficient to drive a self-contained biodevice, viz. 7 μW cm-2 in vitro and 2 μW cm-2 in vivo at an operating voltage of 0.4 V. Last but not least, we also demonstrate an inductive coupling between 3D nanobioelectrodes and living neurons.

Navigation with a passive brain based interface

NARCIS (Netherlands)

Erp, J.B.F. van; Werkhoven, P.J.; Thurlings, M.E.; Brouwer, A.-M.

2009-01-01

In this paper, we describe a Brain Computer Interface (BCI) for navigation. The system is based on detecting brain signals that are elicited by tactile stimulation on the torso indicating the desired direction.

Numerical Characterization of Intraoperative and Chronic Electrodes in Deep Brain Stimulation

Directory of Open Access Journals (Sweden)

Alessandra ePaffi

2015-02-01

Full Text Available Intraoperative electrode is used in the Deep Brain stimulation (DBS technique to pinpoint the brain target and to choose the best parameters for the stimulating signal. However, when the intraoperative electrode is replaced with the chronic one, the observed effects do not always coincide with predictions.To investigate the causes of such discrepancies, in this work, a 3D model of the basal ganglia has been considered and realistic models of both intraoperative and chronic electrodes have been developed and numerically solved.Results of simulations on the electric potential and the activating function along neuronal fibers show that the different geometries and sizes of the two electrodes do not change shapes and polarities of these functions, but only the amplitudes. A similar effect is caused by the presence of different tissue layers (edema or glial tissue in the peri-electrode space. On the contrary, a not accurate positioning of the chronic electrode with respect to the intraoperative one (electric centers not coincident may induce a complete different electric stimulation on some groups of fibers.

A low-power portable ECG sensor interface with dry electrodes

International Nuclear Information System (INIS)

Pu Xiaofei; Wan Lei; Zhang Hui; Qin Yajie; Hong Zhiliang

2013-01-01

This paper describes a low-power portable sensor interface dedicated to sensing and processing electrocardiogram (ECG) signals. Dry electrodes were employed in this ECG sensor, which eliminates the need of conductive gel and avoids complicated and mandatory skin preparation before electrode attachment. This ECG sensor system consists of two ICs, an analog front-end (AFE) and a successive approximation register analog-to-digital converter (SAR ADC) containing a relaxation oscillator. This proposed design was fabricated in a 0.18 μm 1P6M standard CMOS process. The AFE for extracting the biopotential signals is essential in this ECG sensor. In measurements, the AFE obtains a mid-band gain of 45 dB, a bandwidth from 0.6 to 160 Hz, and a total input referred noise of 2.8 μV rms while consuming 1 μW from the 1.8 V supply. The noise efficiency factor (NEF) of our design is 3.4. After conditioning, the amplified ECG signal is digitized by a 12-bit SAR ADC with 61.8 dB SNDR and 220 fJ/conversion-step. Finally, a complete ECG sensor interface with three dry copper electrodes is demonstrated in real-word setting, showing successful recordings of a capture ECG waveform. (semiconductor integrated circuits)

Near infrared spectroscopy based brain-computer interface

Science.gov (United States)

Ranganatha, Sitaram; Hoshi, Yoko; Guan, Cuntai

2005-04-01

A brain-computer interface (BCI) provides users with an alternative output channel other than the normal output path of the brain. BCI is being given much attention recently as an alternate mode of communication and control for the disabled, such as patients suffering from Amyotrophic Lateral Sclerosis (ALS) or "locked-in". BCI may also find applications in military, education and entertainment. Most of the existing BCI systems which rely on the brain's electrical activity use scalp EEG signals. The scalp EEG is an inherently noisy and non-linear signal. The signal is detrimentally affected by various artifacts such as the EOG, EMG, ECG and so forth. EEG is cumbersome to use in practice, because of the need for applying conductive gel, and the need for the subject to be immobile. There is an urgent need for a more accessible interface that uses a more direct measure of cognitive function to control an output device. The optical response of Near Infrared Spectroscopy (NIRS) denoting brain activation can be used as an alternative to electrical signals, with the intention of developing a more practical and user-friendly BCI. In this paper, a new method of brain-computer interface (BCI) based on NIRS is proposed. Preliminary results of our experiments towards developing this system are reported.

Electrode-tissues interface: modeling and experimental validation

International Nuclear Information System (INIS)

Sawan, M; Laaziri, Y; Mounaim, F; Elzayat, E; Corcos, J; Elhilali, M M

2007-01-01

The electrode-tissues interface (ETI) is one of the key issues in implantable devices such as stimulators and sensors. Once the stimulator is implanted, safety and reliability become more and more critical. In this case, modeling and monitoring of the ETI are required. We propose an empirical model for the ETI and a dedicated integrated circuit to measure its corresponding complex impedance. These measurements in the frequency range of 1 Hz to 100 kHz were achieved in acute dog experiments. The model demonstrates a closer fitting with experimental measurements. In addition, a custom monitoring device based on a stimuli current generator has been completed to evaluate the phase shift and voltage across the electrodes and to transmit wirelessly the values to an external controller. This integrated circuit has been fabricated in a CMOS 0.18 μm process, which consumes 4 mW only during measurements and occupies an area of 1 mm 2 . (review article)

Connections that Count: Brain-Computer Interface Enables the Profoundly Paralyzed to Communicate

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... Home Current Issue Past Issues Connections that Count: Brain-Computer Interface Enables the Profoundly Paralyzed to Communicate Past Issues / ... of this page please turn Javascript on. A brain-computer interface (BCI) system This brain-computer interface (BCI) system ...

Spectroscopic Analysis of Ion Concentration Profile at Electrode/Electrolyte Interface by Interferometry

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Moore, David; Saraf, Ravi

2014-03-01

Owing to the difference in Fermi levels at an electrode/electrolyte interface, ions form an electrical double layer (EDL) with ion concentrations well over 10-fold compared to bulk. The concentration profile of the EDL intrinsically affects the electrochemical reaction rates at the electrode, which is of great significance in many applications, such as batteries and biosensors. Conventionally, using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), the electrical properties of the EDL are represented as ``equivalent circuits'' consisting of the resistance to charge transfer (Rct), the double layer capacitance (Cdl) and a ``Warburg (constant phase) diffusion element'' that represents the long range diffusion of ions to the electrode. The translation to the well-understood physical structure can be lost as complicated effects are often lumped together. For example, the effect of subtle modification of the electrode surface by say, redox compounds, enzymes, or polymers is not directly measured, and must be inferred by capacitance changes. An interferometer method will be described to directly measure changes in concentration at the interface during redox process. This method in concert with CV or EIS performed concomitantly will lead to more information to model the diffuse layer for improved understanding of the kinetics of the reaction at different distances from the electrode. Applications to DNA and polymer adsorption binding will be discussed.

Engineering brain-computer interfaces: past, present and future.

Science.gov (United States)

Hughes, M A

2014-06-01

Electricity governs the function of both nervous systems and computers. Whilst ions move in polar fluids to depolarize neuronal membranes, electrons move in the solid-state lattices of microelectronic semiconductors. Joining these two systems together, to create an iono-electric brain-computer interface, is an immense challenge. However, such interfaces offer (and in select clinical contexts have already delivered) a method of overcoming disability caused by neurological or musculoskeletal pathology. To fulfill their theoretical promise, several specific challenges demand consideration. Rate-limiting steps cover a diverse range of disciplines including microelectronics, neuro-informatics, engineering, and materials science. As those who work at the tangible interface between brain and outside world, neurosurgeons are well placed to contribute to, and inform, this cutting edge area of translational research. This article explores the historical background, status quo, and future of brain-computer interfaces; and outlines the challenges to progress and opportunities available to the clinical neurosciences community.

Virtual reality hardware and graphic display options for brain-machine interfaces.

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Marathe, Amar R; Carey, Holle L; Taylor, Dawn M

2008-01-15

Virtual reality hardware and graphic displays are reviewed here as a development environment for brain-machine interfaces (BMIs). Two desktop stereoscopic monitors and one 2D monitor were compared in a visual depth discrimination task and in a 3D target-matching task where able-bodied individuals used actual hand movements to match a virtual hand to different target hands. Three graphic representations of the hand were compared: a plain sphere, a sphere attached to the fingertip of a realistic hand and arm, and a stylized pacman-like hand. Several subjects had great difficulty using either stereo monitor for depth perception when perspective size cues were removed. A mismatch in stereo and size cues generated inappropriate depth illusions. This phenomenon has implications for choosing target and virtual hand sizes in BMI experiments. Target-matching accuracy was about as good with the 2D monitor as with either 3D monitor. However, users achieved this accuracy by exploring the boundaries of the hand in the target with carefully controlled movements. This method of determining relative depth may not be possible in BMI experiments if movement control is more limited. Intuitive depth cues, such as including a virtual arm, can significantly improve depth perception accuracy with or without stereo viewing.

Brain-Computer Interfacing Embedded in Intelligent and Affective Systems

NARCIS (Netherlands)

Nijholt, Antinus

In this talk we survey recent research views on non-traditional brain-computer interfaces (BCI). That is, interfaces that can process brain activity input, but that are designed for the ‘general population’, rather than for clinical purposes. Control of applications can be made more robust by fusing

Leveraging anatomical information to improve transfer learning in brain-computer interfaces

Science.gov (United States)

Wronkiewicz, Mark; Larson, Eric; Lee, Adrian K. C.

2015-08-01

Objective. Brain-computer interfaces (BCIs) represent a technology with the potential to rehabilitate a range of traumatic and degenerative nervous system conditions but require a time-consuming training process to calibrate. An area of BCI research known as transfer learning is aimed at accelerating training by recycling previously recorded training data across sessions or subjects. Training data, however, is typically transferred from one electrode configuration to another without taking individual head anatomy or electrode positioning into account, which may underutilize the recycled data. Approach. We explore transfer learning with the use of source imaging, which estimates neural activity in the cortex. Transferring estimates of cortical activity, in contrast to scalp recordings, provides a way to compensate for variability in electrode positioning and head morphologies across subjects and sessions. Main results. Based on simulated and measured electroencephalography activity, we trained a classifier using data transferred exclusively from other subjects and achieved accuracies that were comparable to or surpassed a benchmark classifier (representative of a real-world BCI). Our results indicate that classification improvements depend on the number of trials transferred and the cortical region of interest. Significance. These findings suggest that cortical source-based transfer learning is a principled method to transfer data that improves BCI classification performance and provides a path to reduce BCI calibration time.

Improvement of interface property for membrane electrode assembly in fuel cell

International Nuclear Information System (INIS)

Fujii, K.; Sato, Y.; Kakigi, T.; Matsuura, A.; Mitani, N.; Muto, F.; Li Jingye; Miura, T.; Oshima, A.; Washio, M.

2006-01-01

Membrane electrode assembly (MEA) in polymer electrolyte fuel cells (PEFC) is consisted of proton exchange membrane (PEM), binder and Pt/C electrodes. In our previous work, partial-fluorinated sulfonic acid membranes were synthesized for PEMs using pre-EB grafting method. In the fuel cell (FC) operation, the dispersion of per-fluorinated sulfonic acid such as Nafion (DuPont de Nemours LTD.) was used for binder material. So, it is found that the trouble on conditions at three phase interface would occur at high temperature FC operation due to the differences of thermal properties. Thus, the control of interface property is important. In this study, in order to improve the interface properties, proton exchange membrane was synthesized from poly (tetrafluoroethylene-co-perfluoroalkylvinylether) (PFA), and then the obtained sulfonated PFA (s-PFA) was applied for binder material. PFA membranes were grafted in liquid styrene after EB irradiation under nitrogen atmosphere, and then sulfonated by chlorosulfonic acid solutions. The s-PFA membranes were milled to the powder in the mortar, and the average diameter was about 13 μm. S-PFA / Nafion blend dispersion was prepared by s-PFA mixed with Nafion dispersion with various ratios. MEAs were fabricated by using obtained binders, s-PFA membranes and Pt / C electrodes, followed by hot pressing at 110 degree C and at 8 MPa during 3 min. The properties of MEAs were measured by electrochemical analyses. In consequence, ion conductivities in MEA using obtained binders were about 1.3 times higher than those using Nafion dispersion. And, both power densities at 500 mA/cm 2 and maximum power densities were 1.1 times higher than those of Nafion dispersion. These are due to the improvement of the proton transfer at interface. (authors)

Enhanced inter-subject brain computer interface with associative sensorimotor oscillations.

Science.gov (United States)

Saha, Simanto; Ahmed, Khawza I; Mostafa, Raqibul; Khandoker, Ahsan H; Hadjileontiadis, Leontios

2017-02-01

Electroencephalography (EEG) captures electrophysiological signatures of cortical events from the scalp with high-dimensional electrode montages. Usually, excessive sources produce outliers and potentially affect the actual event related sources. Besides, EEG manifests inherent inter-subject variability of the brain dynamics, at the resting state and/or under the performance of task(s), caused probably due to the instantaneous fluctuation of psychophysiological states. A wavelet coherence (WC) analysis for optimally selecting associative inter-subject channels is proposed here and is being used to boost performances of motor imagery (MI)-based inter-subject brain computer interface (BCI). The underlying hypothesis is that optimally associative inter-subject channels can reduce the effects of outliers and, thus, eliminate dissimilar cortical patterns. The proposed approach has been tested on the dataset IVa from BCI competition III, including EEG data acquired from five healthy subjects who were given visual cues to perform 280 trials of MI for the right hand and right foot. Experimental results have shown increased classification accuracy (81.79%) using the WC-based selected 16 channels compared to the one (56.79%) achieved using all the available 118 channels. The associative channels lie mostly around the sensorimotor regions of the brain, reinforced by the previous literature, describing spatial brain dynamics during sensorimotor oscillations. Apparently, the proposed approach paves the way for optimised EEG channel selection that could boost further the efficiency and real-time performance of BCI systems.

Intraoperative definition of bottom-of-sulcus dysplasia using intraoperative ultrasound and single depth electrode recording - A technical note.

Science.gov (United States)

Miller, Dorothea; Carney, Patrick; Archer, John S; Fitt, Gregory J; Jackson, Graeme D; Bulluss, Kristian J

2018-02-01

Bottom of sulcus dysplasias (BOSDs) are localized focal cortical dysplasias (FCDs) centred on the bottom of a sulcus that can be highly epileptogenic, but difficult to delineate intraoperatively. We report on a patient with refractory epilepsy due to a BOSD, successfully resected with the aid of a multimodal surgical approach using neuronavigation based on MRI and PET, intraoperative ultrasound (iUS) and electrocorticography (ECoG) using depth electrodes. The lesion could be visualized on iUS showing an increase in echogenicity at the grey-white matter junction. IUS demonstrated the position of the depth electrode in relation to the lesion. Depth electrode recording showed almost continuous spiking. Thus, intraoperative imaging and electrophysiology helped confirm the exact location of the lesion. Post-resection ultrasound demonstrated the extent of the resection and depth electrode recording did not show any epileptiform activity. Thus, both techniques helped assess completeness of resection. The patient has been seizure free since surgery. Using a multimodal approach including iUS and ECoG is a helpful adjunct in surgery for BOSD and may improve seizure outcome. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation and use of regenerative multi electrode interfaces in peripheral nerves

Science.gov (United States)

Desai, Vidhi

Peripheral nerves offer unique accessibility to the innate motor and sensory pathways that can be interfaced with high degree of selectivity for intuitive and bidirectional control of advanced upper extremity prosthetic limbs. Several peripheral nerve interfaces have been proposed and investigated over the last few decades with significant progress made in the area of sensory feedback. However, clinical translation still remains a formidable challenge due to the lack of long term recordings. Prominent causes include signal degradation, eventual interface failures, and lack of specificity in the low amplitude nerve signals. This dissertation evaluates the capabilities of the newly developed Regenerative Multi-electrode Interface (REMI) by the characterization of signal quality progression, the identification of interfaced axon types, and the demonstration of "functional linkage" between acquired signals and target organs. Chapter 2 details the chronic recording of high quality signals from REMI in sciatic nerve which remained stable over a 120 day implantation period indicative of minimal ongoing tissue response with no detrimental effects on the recording ability. The dominant cause of failures was attributable to abiotic factors pertaining to the connector/wire breakage, observed in 76% of REMI implants. Also, the REMI implants had 20% higher success rate and significantly larger Signal to Noise Ratio (SNR) in comparison to the Utah Slanted Electrode Array (USEA). Chapter 3 describes the successful feasibility of interfacing with motor and sensory axons by REMI implantation in the tibial and sural fascicles of the sciatic nerve. A characteristic sampling bias towards recording signals from medium-to-large diameter axons that are primarily involved in mechanoception and proprioception sensory functions was uncovered. Specific bursting units (Inter Spike Interval of 30-70ms) were observed most frequently from the tibial fascicle during bipedal locomotion. Chapter 4

Molecular scale structure and dynamics at an ionic liquid/electrode interface

DEFF Research Database (Denmark)

Reichert, Peter; Kjær, Kasper Skov; Brandt van Driel, Tim

2018-01-01

After a century of research, the potential-dependent ion distribution at electrode/electrolyte interfaces is still under debate. In particular for solvent-free electrolytes such as room-temperature ionic liquids, classical theories for the electrical double layer are not applicable. Using a combi...

Evaluation of a Compact Hybrid Brain-Computer Interface System

Directory of Open Access Journals (Sweden)

Jaeyoung Shin

2017-01-01

Full Text Available We realized a compact hybrid brain-computer interface (BCI system by integrating a portable near-infrared spectroscopy (NIRS device with an economical electroencephalography (EEG system. The NIRS array was located on the subjects’ forehead, covering the prefrontal area. The EEG electrodes were distributed over the frontal, motor/temporal, and parietal areas. The experimental paradigm involved a Stroop word-picture matching test in combination with mental arithmetic (MA and baseline (BL tasks, in which the subjects were asked to perform either MA or BL in response to congruent or incongruent conditions, respectively. We compared the classification accuracies of each of the modalities (NIRS or EEG with that of the hybrid system. We showed that the hybrid system outperforms the unimodal EEG and NIRS systems by 6.2% and 2.5%, respectively. Since the proposed hybrid system is based on portable platforms, it is not confined to a laboratory environment and has the potential to be used in real-life situations, such as in neurorehabilitation.

Detection of spreading depolarization with intraparenchymal electrodes in the injured human brain

DEFF Research Database (Denmark)

Jeffcote, Toby; Hinzman, Jason M; Jewell, Sharon L

2014-01-01

be detected using intra-cortical electrodes, opening the way for electrode insertion via burr hole. METHODS: Animal work was carried out on adult Sprague-Dawley rats in a laboratory setting to investigate the feasibility of recording depolarization events. Subsequently, 8 human patients requiring craniotomy...... for craniotomy. The method provides a new investigative tool for the evaluation of the contribution of these events to secondary brain injury in human patients.......BACKGROUND: Spreading depolarization events following ischemic and traumatic brain injury are associated with poor patient outcome. Currently, monitoring these events is limited to patients in whom subdural electrodes can be placed at open craniotomy. This study examined whether these events can...

Virus-Assembled Flexible Electrode-Electrolyte Interfaces for Enhanced Polymer-Based Battery Applications

Directory of Open Access Journals (Sweden)

Ayan Ghosh

2012-01-01

Full Text Available High-aspect-ratio cobalt-oxide-coated Tobacco mosaic virus (TMV- assembled polytetrafluoroethylene (PTFE nonstick surfaces were integrated with a solvent-free polymer electrolyte to create an anode-electrolyte interface for use in lithium-ion batteries. The virus-assembled PTFE surfaces consisted primarily of cobalt oxide and were readily intercalated with a low-molecular-weight poly (ethylene oxide (PEO based diblock copolymer electrolyte to produce a solid anode-electrolyte system. The resulting polymer-coated virus-based system was then peeled from the PTFE backing to produce a flexible electrode-electrolyte component. Electrochemical studies indicated the virus-structured metal-oxide PEO-based interface was stable and displayed robust charge transfer kinetics. Combined, these studies demonstrate the development of a novel solid-state electrode architecture with a unique peelable and flexible processing attribute.

3D Printed Dry EEG Electrodes.

Science.gov (United States)

Krachunov, Sammy; Casson, Alexander J

2016-10-02

Electroencephalography (EEG) is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI). A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise.

3D Printed Dry EEG Electrodes

Directory of Open Access Journals (Sweden)

Sammy Krachunov

2016-10-01

Full Text Available Electroencephalography (EEG is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI. A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise.

Postoperative Displacement of Deep Brain Stimulation Electrodes Related to Lead-Anchoring Technique

NARCIS (Netherlands)

Contarino, M. Fiorella; Bot, Maarten; Speelman, Johannes D.; de Bie, Rob M. A.; Tijssen, Marina A.; Denys, Damiaan; Bour, Lo J.; Schuurman, P. Richard; van den Munckhof, Pepijn

2013-01-01

BACKGROUND: Displacement of deep brain stimulation (DBS) electrodes may occur after surgery, especially due to large subdural air collections, but other factors might contribute. OBJECTIVE: To investigate factors potentially contributing to postoperative electrode displacement, in particular,

Brain Computer Interface on Track to Home

Directory of Open Access Journals (Sweden)

Felip Miralles

2015-01-01

Full Text Available The novel BackHome system offers individuals with disabilities a range of useful services available via brain-computer interfaces (BCIs, to help restore their independence. This is the time such technology is ready to be deployed in the real world, that is, at the target end users’ home. This has been achieved by the development of practical electrodes, easy to use software, and delivering telemonitoring and home support capabilities which have been conceived, implemented, and tested within a user-centred design approach. The final BackHome system is the result of a 3-year long process involving extensive user engagement to maximize effectiveness, reliability, robustness, and ease of use of a home based BCI system. The system is comprised of ergonomic and hassle-free BCI equipment; one-click software services for Smart Home control, cognitive stimulation, and web browsing; and remote telemonitoring and home support tools to enable independent home use for nonexpert caregivers and users. BackHome aims to successfully bring BCIs to the home of people with limited mobility to restore their independence and ultimately improve their quality of life.

Interface-Engineered Charge-Transport Properties in Benzenedithiol Molecular Electronic Junctions via Chemically p-Doped Graphene Electrodes.

Science.gov (United States)

Jang, Yeonsik; Kwon, Sung-Joo; Shin, Jaeho; Jeong, Hyunhak; Hwang, Wang-Taek; Kim, Junwoo; Koo, Jeongmin; Ko, Taeg Yeoung; Ryu, Sunmin; Wang, Gunuk; Lee, Tae-Woo; Lee, Takhee

2017-12-06

In this study, we fabricated and characterized vertical molecular junctions consisting of self-assembled monolayers of benzenedithiol (BDT) with a p-doped multilayer graphene electrode. The p-type doping of a graphene film was performed by treating pristine graphene (work function of ∼4.40 eV) with trifluoromethanesulfonic (TFMS) acid, producing a significantly increased work function (∼5.23 eV). The p-doped graphene-electrode molecular junctions statistically showed an order of magnitude higher current density and a lower charge injection barrier height than those of the pristine graphene-electrode molecular junctions, as a result of interface engineering. This enhancement is due to the increased work function of the TFMS-treated p-doped graphene electrode in the highest occupied molecular orbital-mediated tunneling molecular junctions. The validity of these results was proven by a theoretical analysis based on a coherent transport model that considers asymmetric couplings at the electrode-molecule interfaces.

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.

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

Hacking the brain: Brain-computer interfacing technology and the ethics of neurosecurity

NARCIS (Netherlands)

Ienca, M.; Haselager, W.F.G.

2016-01-01

Brain-computer interfacing technologies are used as assistive technologies for patients as well as healthy subjects to control devices solely by brain activity. Yet the risks associated with the misuse of these technologies remain largely unexplored. Recent findings have shown that BCIs are

A study of the electrode/solution interface during electrochemical reactions by digital holography

Directory of Open Access Journals (Sweden)

SHENHAO CHEN

2006-10-01

Full Text Available Digital holography was used to study in situ the dynamic changes of the electrode/solution interface and the solution near the electrode during the anodic process of iron in a sulfuric acid solution. The effects of chloride, bromide and iodine ions on this process were also investigated. The magnetic field also has effects on the process. The effects are discussed in combination with SEM results.

The Brain-Computer Interface Cycle

NARCIS (Netherlands)

Gerven, Marcel; Farquhar, Jason; Schaefer, Rebecca; Vlek, Rutger; Geuze, Jeroen; Nijholt, Antinus; Ramsay, Nick; Haselager, Pim; Vuurpijl, Louis; Gielen, Stan; Desain, Peter

2009-01-01

Brain–computer interfaces (BCIs) have attracted much attention recently, triggered by new scientific progress in understanding brain function and by impressive applications. The aim of this review is to give an overview of the various steps in the BCI cycle, i.e., the loop from the measurement of

Legal Aspects of Brain-Computer Interfaces

Czech Academy of Sciences Publication Activity Database

Krausová, Alžběta

2014-01-01

Roč. 8, č. 2 (2014) ISSN 1802-5951 Institutional support: RVO:68378122 Keywords : brain-computer interface * human rights * right to privacy, Subject RIV: AG - Legal Sciences http://mujlt.law.muni.cz/index.php

Brain-computer interface

DEFF Research Database (Denmark)

2014-01-01

A computer-implemented method of providing an interface between a user and a processing unit, the method comprising : presenting one or more stimuli to a user, each stimulus varying at a respective stimulation frequency, each stimulation frequency being associated with a respective user......-selectable input; receiving at least one signal indicative of brain activity of the user; and determining, from the received signal, which of the one or more stimuli the user attends to and selecting the user-selectable input associated with the stimulation frequency of the determined stimuli as being a user...

Big data challenges in decoding cortical activity in a human with quadriplegia to inform a brain computer interface.

Science.gov (United States)

Friedenberg, David A; Bouton, Chad E; Annetta, Nicholas V; Skomrock, Nicholas; Mingming Zhang; Schwemmer, Michael; Bockbrader, Marcia A; Mysiw, W Jerry; Rezai, Ali R; Bresler, Herbert S; Sharma, Gaurav

2016-08-01

Recent advances in Brain Computer Interfaces (BCIs) have created hope that one day paralyzed patients will be able to regain control of their paralyzed limbs. As part of an ongoing clinical study, we have implanted a 96-electrode Utah array in the motor cortex of a paralyzed human. The array generates almost 3 million data points from the brain every second. This presents several big data challenges towards developing algorithms that should not only process the data in real-time (for the BCI to be responsive) but are also robust to temporal variations and non-stationarities in the sensor data. We demonstrate an algorithmic approach to analyze such data and present a novel method to evaluate such algorithms. We present our methodology with examples of decoding human brain data in real-time to inform a BCI.

Verbal memory decline from hippocampal depth electrodes in temporal lobe surgery for epilepsy.

Science.gov (United States)

Ljung, Hanna; Nordlund, Arto; Strandberg, Maria; Bengzon, Johan; Källén, Kristina

2017-12-01

To explore whether patients with refractory mesial temporal lobe epilepsy risk aggravated verbal memory loss from intracranial electroencephalography (EEG) recording with longitudinal hippocampal electrodes in the language-dominant hemisphere. A long-term neuropsychological follow-up (mean 61.5 months, range 22-111 months) was performed in 40 patients after ictal registration with left hippocampal depth electrodes (study group, n = 16) or no invasive EEG, only extracranial registration (reference group, n = 24). The groups were equal with respect to education, age at seizure onset, epilepsy duration, and prevalence of pharmacoresistant temporal lobe epilepsy (TLE; 75%) versus seizure freedom (25%). Retrospective neuropsychological data from preoperative surgical workup (T1) and prospective follow-up neuropsychological data (T2) were compared. A ≥1 SD intrapatient decline was considered as clinically relevant deterioration of verbal memory. Significant decline in verbal memory was seen in 56% of the patients in the study group compared to 21% in the reference group. At T1, there were no statistical between-group differences in memory performance. At T2, between-group comparison showed significantly greater verbal memory decline for the study group (Claeson Dahl Learning and Retention Test, Verbal Learning: p = 0.05; Rey Auditory Verbal Learning Test, Total Learning: p = 0.04; Claeson Dahl Learning and Retention Test, Verbal Retention: p = 0.04). An odds ratio (OR) of 7.1 (90% confidence interval [CI] 1.3-37.7) for verbal memory decline was seen if right temporal lobe resection (R TLR) had been performed between T1 and T2. The difference between groups remained unchanged when patients who had undergone R TLR were excluded from the analysis, with a remaining aggravated significant decline in verbal memory performance for the study group compared to the reference group. Our results suggest a risk of verbal memory deterioration after the use of depth electrodes along

Finite element modeling of the neuron-electrode interface: stimulus transfer and geometry

NARCIS (Netherlands)

Buitenweg, Jan R.; Rutten, Wim; Marani, Enrico

1999-01-01

The relation between stimulus transfer and the geometry of the neuron-electrode interface can not be determined properly using electrical equivalent circuits, since current that flows from the sealing gap through the neuronal membrane is difficult to model in these circuits. Therefore, finite

EPES information depth for an overlayer/substrate system with a diffuse interface

International Nuclear Information System (INIS)

Zommer, L.

2009-01-01

The information depth (ID) of elastic peak electron spectroscopy (EPES) was considered for an overlayer/substrate system with a diffuse interface. The interface was assumed to have an exponential concentration profile. The paradox previously found by Zommer and Jablonski for the Rh/Al and Al/Rh systems with sharp interfaces also occurs for these systems with diffuse interfaces. We compared IDs for diffuse and sharp interfaces. Deviations between the IDs depend on the interface width, overlayer thickness, and selected system for a given primary energy (here 2000 eV). The deviations for the Rh/Al and Al/Rh systems differ profoundly. These results are of importance when interpreting EPES measurements of layered system

Touch-based Brain Computer Interfaces: State of the art

NARCIS (Netherlands)

Erp, J.B.F. van; Brouwer, A.M.

2014-01-01

Brain Computer Interfaces (BCIs) rely on the user's brain activity to control equipment or computer devices. Many BCIs are based on imagined movement (called active BCIs) or the fact that brain patterns differ in reaction to relevant or attended stimuli in comparison to irrelevant or unattended

A reliable method for intracranial electrode implantation and chronic electrical stimulation in the mouse brain.

Science.gov (United States)

Jeffrey, Melanie; Lang, Min; Gane, Jonathan; Wu, Chiping; Burnham, W McIntyre; Zhang, Liang

2013-08-06

Electrical stimulation of brain structures has been widely used in rodent models for kindling or modeling deep brain stimulation used clinically. This requires surgical implantation of intracranial electrodes and subsequent chronic stimulation in individual animals for several weeks. Anchoring screws and dental acrylic have long been used to secure implanted intracranial electrodes in rats. However, such an approach is limited when carried out in mouse models as the thin mouse skull may not be strong enough to accommodate the anchoring screws. We describe here a screw-free, glue-based method for implanting bipolar stimulating electrodes in the mouse brain and validate this method in a mouse model of hippocampal electrical kindling. Male C57 black mice (initial ages of 6-8 months) were used in the present experiments. Bipolar electrodes were implanted bilaterally in the hippocampal CA3 area for electrical stimulation and electroencephalographic recordings. The electrodes were secured onto the skull via glue and dental acrylic but without anchoring screws. A daily stimulation protocol was used to induce electrographic discharges and motor seizures. The locations of implanted electrodes were verified by hippocampal electrographic activities and later histological assessments. Using the glue-based implantation method, we implanted bilateral bipolar electrodes in 25 mice. Electrographic discharges and motor seizures were successfully induced via hippocampal electrical kindling. Importantly, no animal encountered infection in the implanted area or a loss of implanted electrodes after 4-6 months of repetitive stimulation/recording. We suggest that the glue-based, screw-free method is reliable for chronic brain stimulation and high-quality electroencephalographic recordings in mice. The technical aspects described this study may help future studies in mouse models.

Use of a mid-scala and a lateral wall electrode in children: insertion depth and hearing preservation.

Science.gov (United States)

Benghalem, Abdelhamid; Gazibegovic, Dzemal; Saadi, Fatima; Tazi-Chaoui, Zakia

2017-01-01

Atraumatic insertion of the HiFocus TM Mid-Scala (HFMS) electrode via the round window was successfully achieved in seven children. Residual hearing 6 months post-operatively was preserved to within 10 dB HL of the pre-operative audiogram at 500 Hz for six children, indicating minimal initial insertion trauma to the cochlea. The objectives were to document the clinical experience and evaluate differences between HFMS and HiFocus TM 1j (HF1j) by means of insertion depth and hearing preservation results. Nineteen children were prospectively recruited and consecutively implanted with the HF1j electrode (n = 12) or the HFMS electrode (n = 7) via the round window. Average median angular insertion depths and the amount of residual hearing preserved at 6 months post-operatively were compared between the two electrode groups. The median angular insertion depth for the HF1j was 439° and for the HFMS 435°. Preservation of residual hearing at 500 Hz was assessed in seven HFMS subjects and 11 HF1j subjects. Based on the Skarzynski formula, three out of seven subjects (42%) in the HFMS group had their residual hearing completely preserved at 500 Hz. In the control group, no subjects had complete hearing preservation and five subjects had a complete loss of residual hearing.

Boron-doped nanocrystalline diamond electrodes for neural interfaces: in vivo biocompatibility evaluation

Czech Academy of Sciences Publication Activity Database

Alcaide, M.; Taylor, Andrew; Fjorback, M.; Zachar, V.; Pennisi, C.P.

2016-01-01

Roč. 10, Mar (2016), 1-9, č. článku 87. ISSN 1662-453X Institutional support: RVO:68378271 Keywords : nanocrystalline diamond * neuroprosthetic interfaces * neural electrodes * boron-doped diamond * titanium nitride * foreign body reaction Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 3.566, year: 2016

Electroluminescence and electrical degradation of insulating polymers at electrode interfaces under divergent fields

Science.gov (United States)

Zhang, Shuai; Li, Qi; Hu, Jun; Zhang, Bo; He, Jinliang

2018-04-01

Electrical degradation of insulating polymers at electrode interfaces is an essential factor in determining long-term reliability. A critical challenge is that the exact mechanism of degradation is not fully understood, either experimentally or theoretically, due to the inherent complex processes. Consequently, in this study, we investigate electroluminescence (EL) at the interface of an electrode and insulator, and determine the relationship between EL and electrical degradation. Using a tip-plate electrode structure, the unique features of EL under a highly divergent field are investigated. The voltage type (alternating or direct current), the polymer matrix, and the time of pressing are also investigated separately. A study of EL from insulators under a divergent field is provided, and the relationship between EL spectra and degradation is discussed. It is shown that EL spectra under a divergent field have unique characteristics compared with EL spectra from polymer films under a uniform field and the most obvious one is the UV emission. The results obtained in the current investigation bring us a step closer to understanding the process of electrical degradation and provide a potential way to diagnose insulator defects.

Sensorimotor rhythm-based brain-computer interface training: the impact on motor cortical responsiveness

Science.gov (United States)

Pichiorri, F.; De Vico Fallani, F.; Cincotti, F.; Babiloni, F.; Molinari, M.; Kleih, S. C.; Neuper, C.; Kübler, A.; Mattia, D.

2011-04-01

The main purpose of electroencephalography (EEG)-based brain-computer interface (BCI) technology is to provide an alternative channel to support communication and control when motor pathways are interrupted. Despite the considerable amount of research focused on the improvement of EEG signal detection and translation into output commands, little is known about how learning to operate a BCI device may affect brain plasticity. This study investigated if and how sensorimotor rhythm-based BCI training would induce persistent functional changes in motor cortex, as assessed with transcranial magnetic stimulation (TMS) and high-density EEG. Motor imagery (MI)-based BCI training in naïve participants led to a significant increase in motor cortical excitability, as revealed by post-training TMS mapping of the hand muscle's cortical representation; peak amplitude and volume of the motor evoked potentials recorded from the opponens pollicis muscle were significantly higher only in those subjects who develop a MI strategy based on imagination of hand grasping to successfully control a computer cursor. Furthermore, analysis of the functional brain networks constructed using a connectivity matrix between scalp electrodes revealed a significant decrease in the global efficiency index for the higher-beta frequency range (22-29 Hz), indicating that the brain network changes its topology with practice of hand grasping MI. Our findings build the neurophysiological basis for the use of non-invasive BCI technology for monitoring and guidance of motor imagery-dependent brain plasticity and thus may render BCI a viable tool for post-stroke rehabilitation.

A tactile P300 brain-computer interface

NARCIS (Netherlands)

Brouwer, A.M.; Erp, J.B.F. van

2010-01-01

De werking van de eerste Brain-Computer-Interface gebaseerd op tactiele EEG response wordt gedemonstreerd en het effect van het aantal gebruikte vibro-tactiele tactoren en stimulus-timing parameters wordt onderzocht

Using brain-computer interfaces and brain-state dependent stimulation as tools in cognitive neuroscience

NARCIS (Netherlands)

Jensen, O.; Bahramisharif, A.; Oostenveld, R.; Klanke, S.; Hadjipapas, A.; Okazaki, Y.O.; Gerven, M.A.J. van

2011-01-01

Large efforts are currently being made to develop and improve online analysis of brain activity which can be used, e.g., for brain-computer interfacing (BCI). A BCI allows a subject to control a device by willfully changing his/her own brain activity. BCI therefore holds the promise as a tool for

Impact of metal artefacts due to EEG electrodes in brain PET/CT imaging

International Nuclear Information System (INIS)

Lemmens, Catherine; Nuyts, Johan; Dupont, Patrick; Montandon, Marie-Louise; Ratib, Osman; Zaidi, Habib

2008-01-01

The goal of this study is to investigate the impact of electroencephalogram (EEG) electrodes on the visual quality and quantification of 18 F-FDG PET images in neurological PET/CT examinations. For this purpose, the scans of 20 epilepsy patients with EEG monitoring were used. The CT data were reconstructed with filtered backprojection (FBP) and with a metal artefact reduction (MAR) algorithm. Both data sets were used for CT-based attenuation correction (AC) of the PET data. Also, a calculated AC (CALC) technique was considered. A volume of interest (VOI)-based analysis and a voxel-based quantitative analysis were performed to compare the different AC methods. Images were also evaluated visually by two observers. It was shown with simulations and phantom measurements that from the considered AC methods, the MAR-AC can be used as the reference in this setting. The visual assessment of PET images showed local hot spots outside the brain corresponding to the locations of the electrodes when using FBP-AC. In the brain, no abnormalities were observed. The quantitative analysis showed a very good correlation between PET-FBP-AC and PET-MAR-AC, with a statistically significant positive bias in the PET-FBP-AC images of about 5-7% in most brain voxels. There was also good correlation between PET-CALC-AC and PET-MAR-AC, but in the PET-CALC-AC images, regions with both a significant positive and negative bias were observed. EEG electrodes give rise to local hot spots outside the brain and a positive quantification bias in the brain. However, when diagnosis is made by mere visual assessment, the presence of EEG electrodes does not seem to alter the diagnosis. When quantification is performed, the bias becomes an issue especially when comparing brain images with and without EEG monitoring

Impact of metal artefacts due to EEG electrodes in brain PET/CT imaging

Energy Technology Data Exchange (ETDEWEB)

Lemmens, Catherine; Nuyts, Johan; Dupont, Patrick [Department of Nuclear Medicine and Medical Imaging Center, University Hospital Gasthuisberg and Katholieke Universiteit Leuven, Leuven (Belgium); Montandon, Marie-Louise; Ratib, Osman; Zaidi, Habib [Division of Nuclear Medicine, Geneva University Hospital, CH-1211 Geneva (Switzerland)], E-mail: catherine.lemmens@uz.kuleuven.be

2008-08-21

The goal of this study is to investigate the impact of electroencephalogram (EEG) electrodes on the visual quality and quantification of {sup 18}F-FDG PET images in neurological PET/CT examinations. For this purpose, the scans of 20 epilepsy patients with EEG monitoring were used. The CT data were reconstructed with filtered backprojection (FBP) and with a metal artefact reduction (MAR) algorithm. Both data sets were used for CT-based attenuation correction (AC) of the PET data. Also, a calculated AC (CALC) technique was considered. A volume of interest (VOI)-based analysis and a voxel-based quantitative analysis were performed to compare the different AC methods. Images were also evaluated visually by two observers. It was shown with simulations and phantom measurements that from the considered AC methods, the MAR-AC can be used as the reference in this setting. The visual assessment of PET images showed local hot spots outside the brain corresponding to the locations of the electrodes when using FBP-AC. In the brain, no abnormalities were observed. The quantitative analysis showed a very good correlation between PET-FBP-AC and PET-MAR-AC, with a statistically significant positive bias in the PET-FBP-AC images of about 5-7% in most brain voxels. There was also good correlation between PET-CALC-AC and PET-MAR-AC, but in the PET-CALC-AC images, regions with both a significant positive and negative bias were observed. EEG electrodes give rise to local hot spots outside the brain and a positive quantification bias in the brain. However, when diagnosis is made by mere visual assessment, the presence of EEG electrodes does not seem to alter the diagnosis. When quantification is performed, the bias becomes an issue especially when comparing brain images with and without EEG monitoring.

Power Conditioning and Stimulation for Wireless Neural Interface ICs

OpenAIRE

Biederman, William

2014-01-01

Brain machine interfaces have the potential to revolutionize our understanding of the brain, restore motor function, and improve the quality of life to patients with neurological con- ditions. In recent human trials, control of robotic prostheses has been demonstrated using micro-electrode arrays, which provide high spatio-temporal resolution and an electrical feed- back path to the brain. However, after implantation, scar tissue degrades the recording signal-to-noise ratio and limits the use...

Brain-computer interfaces in neurological rehabilitation.

Science.gov (United States)

Daly, Janis J; Wolpaw, Jonathan R

2008-11-01

Recent advances in analysis of brain signals, training patients to control these signals, and improved computing capabilities have enabled people with severe motor disabilities to use their brain signals for communication and control of objects in their environment, thereby bypassing their impaired neuromuscular system. Non-invasive, electroencephalogram (EEG)-based brain-computer interface (BCI) technologies can be used to control a computer cursor or a limb orthosis, for word processing and accessing the internet, and for other functions such as environmental control or entertainment. By re-establishing some independence, BCI technologies can substantially improve the lives of people with devastating neurological disorders such as advanced amyotrophic lateral sclerosis. BCI technology might also restore more effective motor control to people after stroke or other traumatic brain disorders by helping to guide activity-dependent brain plasticity by use of EEG brain signals to indicate to the patient the current state of brain activity and to enable the user to subsequently lower abnormal activity. Alternatively, by use of brain signals to supplement impaired muscle control, BCIs might increase the efficacy of a rehabilitation protocol and thus improve muscle control for the patient.

In vivo monitoring of glial scar proliferation on chronically implanted neural electrodes by fiber optical coherence tomography

Science.gov (United States)

Xie, Yijing; Martini, Nadja; Hassler, Christina; Kirch, Robert D.; Stieglitz, Thomas; Seifert, Andreas; Hofmann, Ulrich G.

2014-01-01

In neural prosthetics and stereotactic neurosurgery, intracortical electrodes are often utilized for delivering therapeutic electrical pulses, and recording neural electrophysiological signals. Unfortunately, neuroinflammation impairs the neuron-electrode-interface by developing a compact glial encapsulation around the implants in long term. At present, analyzing this immune reaction is only feasible with post-mortem histology; currently no means for specific in vivo monitoring exist and most applicable imaging modalities can not provide information in deep brain regions. Optical coherence tomography (OCT) is a well established imaging modality for in vivo studies, providing cellular resolution and up to 1.2 mm imaging depth in brain tissue. A fiber based spectral domain OCT was shown to be capable of minimally invasive brain imaging. In the present study, we propose to use a fiber based spectral domain OCT to monitor the progression of the tissue's immune response through scar encapsulation progress in a rat animal model. A fine fiber catheter was implanted in rat brain together with a flexible polyimide microelectrode in sight both of which acts as a foreign body and induces the brain tissue immune reaction. OCT signals were collected from animals up to 12 weeks after implantation and thus gliotic scarring in vivo monitored for that time. Preliminary data showed a significant enhancement of the OCT backscattering signal during the first 3 weeks after implantation, and increased attenuation factor of the sampled tissue due to the glial scar formation. PMID:25191264

Adsorption of asparagine on the gold electrode and air/solution interface

International Nuclear Information System (INIS)

Slojkowska, R.; Palys, B.; Jurkiewicz-Herbich, M.

2004-01-01

The adsorption of asparagine (Asn) on a gold electrode from 0.1 M LiClO 4 aqueous solutions was investigated. The experimental data obtained from ac impedance measurements were analyzed to determine the dependence of adsorption parameters, i.e. the standard Gibbs energy of adsorption (ΔG 0 ), maximal value of surface excess concentration (Γ max ) of Asn and parameter of interactions in the adsorbed layer (A) on the electrode potential. The relatively large value of Gibbs energy of adsorption (∼ -47 kJ mol -1 ) gives the evidence of a very strong adsorption of Asn at the polycrystalline Au electrode. The comparison of the adsorption behavior of Asn at the air/solution and the Au/solution interfaces points out to the significant electronic interactions of adsorbate molecules with the Au electrode, since the adsorption of Asn on a free surface (from the same solutions) is very week. The analysis of the electrochemical data as well as the infrared reflection absorption spectroscopy (IRAS) results reveal that Asn molecules are anchored to the Au surface through oxygen atoms of the carboxylate group COO - and through the amide carbonyl group

Elucidating the Polymeric Binder Distribution within Lithium-ion Battery Electrodes Using SAICAS.

Science.gov (United States)

Kim, Kyuman; Byun, Seoungwoo; Choi, Jaecheol; Hong, Seungbum; Ryou, Myung-Hyun; Lee, Yong Min

2018-03-30

Polymeric binder distribution within electrodes is crucial to guarantee the electrochemical performance of lithium-ion batteries (LIBs) for their long-term use in applications such as electric vehicles and energy-storage systems. However, due to limited analytical tools, such analyses have not been conducted so far. Herein, the adhesion properties of LIB electrodes at different depths are measured using a surface and interfacial cutting analysis system (SAICAS). Moreover, two LiCoO 2 electrodes, dried at 130 and 230 °C, are carefully prepared and used to obtain the adhesion properties at every 10 μm of depth as well as the interface between the electrode composite and the current collector. At high drying temperatures, more of the polymeric binder material and conductive agent appears adjacent to the electrode surface, resulting in different adhesion properties as a function of depth. When the electrochemical properties are evaluated at different temperatures, the LiCoO 2 electrode dried at 130 °C shows a much better high-temperature cycling performance than does the electrode dried at 230 °C due to the uniform adhesion properties and the higher interfacial adhesion strength. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The brain-computer interface cycle.

Science.gov (United States)

van Gerven, Marcel; Farquhar, Jason; Schaefer, Rebecca; Vlek, Rutger; Geuze, Jeroen; Nijholt, Anton; Ramsey, Nick; Haselager, Pim; Vuurpijl, Louis; Gielen, Stan; Desain, Peter

2009-08-01

Brain-computer interfaces (BCIs) have attracted much attention recently, triggered by new scientific progress in understanding brain function and by impressive applications. The aim of this review is to give an overview of the various steps in the BCI cycle, i.e., the loop from the measurement of brain activity, classification of data, feedback to the subject and the effect of feedback on brain activity. In this article we will review the critical steps of the BCI cycle, the present issues and state-of-the-art results. Moreover, we will develop a vision on how recently obtained results may contribute to new insights in neurocognition and, in particular, in the neural representation of perceived stimuli, intended actions and emotions. Now is the right time to explore what can be gained by embracing real-time, online BCI and by adding it to the set of experimental tools already available to the cognitive neuroscientist. We close by pointing out some unresolved issues and present our view on how BCI could become an important new tool for probing human cognition.

Fabrication of Polymer Microneedle Electrodes Coated with Nanoporous Parylene

Science.gov (United States)

Nishinaka, Yuya; Jun, Rina; Setia Prihandana, Gunawan; Miki, Norihisa

2013-06-01

In this study, we demonstrate the fabrication of polymer microneedle electrodes covered with a nanoporous parylene film that can serve as flexible electrodes for a brain-machine interface. In brain wave measurement, the electric impedance of electrodes should be below 10 kΩ at 15 Hz, and the conductive layer needs to be protected to survive its insertion into the stratum corneum. Polymer microneedles can be used as substrates for flexible electrodes, which can compensate for the movement of the skin; however, the adhesion between a conductive metal film, such as a silver film, and a polymer, such as poly(dimethylsiloxane) (PDMS), is weak. Therefore, we coated the electrode surface with a nanoporous parylene film, following the vapor deposition of a silver film. When the porosity of the parylene film is appropriate, it protects the silver film while allowing the electrode to have sufficient conductivity. The porosity can be controlled by adjusting the amount of the parylene dimer used for the deposition or the parylene film thickness. We experimentally verified that a conductive membrane was successfully protected while maintaining a conductivity below 10 kΩ when the thickness of the parylene film was between 25 and 38 nm.

Evaluation of different EEG acquisition systems concerning their suitability for building a brain-computer interface

Directory of Open Access Journals (Sweden)

Andreas Pinegger

2016-09-01

Full Text Available One important aspect in non-invasive brain-computer interface (BCI research is to acquire the electroencephalogram (EEG in a proper way. From an end-user perspective this means with maximum comfort and without any extra inconveniences (e.g., washing the hair. Whereas from a technical perspective, the signal quality has to be optimal to make the BCI work effectively and efficiently.In this work we evaluated three different commercially available EEG acquisition systems that differ in the type of electrode (gel-, water-, and dry-based, the amplifier technique, and the data transmission method. Every system was tested regarding three different aspects, namely, technical, BCI effectiveness and efficiency (P300 communication and control, and user satisfaction (comfort.We found that the water-based system had the lowest short circuit noise level, the hydrogel-based system had the highest P300 spelling accuracies, and the dry electrode system caused the least inconveniences.Therefore, building a reliable BCI is possible with all evaluated systems and it is on the user to decide which system meets the given requirements best.

Tailoring the electrode-electrolyte interface of Solid Oxide Fuel Cells (SOFC) by laser micro-patterning to improve their electrochemical performance

Science.gov (United States)

Cebollero, J. A.; Lahoz, R.; Laguna-Bercero, M. A.; Larrea, A.

2017-08-01

Cathode activation polarisation is one of the main contributions to the losses of a Solid Oxide Fuel Cell. To reduce this loss we use a pulsed laser to modify the surface of yttria stabilized zirconia (YSZ) electrolytes to make a corrugated micro-patterning in the mesoscale. The beam of the laser source, 5 ns pulse width and emitting at λ = 532 nm (green region), is computer-controlled to engrave the selected micro-pattern on the electrolyte surface. Several laser scanning procedures and geometries have been tested. Finally, we engrave a square array with 28 μm of lattice parameter and 7 μm in depth on YSZ plates. With these plates we prepare LSM-YSZ/YSZ/LSM-YSZ symmetrical cells (LSM: La1-xSrxMnO3) and determine their activation polarisation by Electrochemical Impedance Spectroscopy (EIS). To get good electrode-electrolyte contact after sintering it is necessary to use pressure-assisted sintering with low loads (about 5 kPa), which do not modify the electrode microstructure. The decrease in polarisation with respect to an unprocessed cell is about 30%. EIS analysis confirms that the reason for this decrease is an improvement in the activation processes at the electrode-electrolyte interface.

Organic semiconductor density of states controls the energy level alignment at electrode interfaces

Science.gov (United States)

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. Here, we implement a detailed electrostatic model, capable of reproducing the alignment between the electrode Fermi energy and the transport states in the organic semiconductor both qualitatively and quantitatively. Covering the full phenomenological range of interfacial energy level alignment regimes within a single, consistent framework and continuously connecting the limiting cases described by previously proposed models allows us to resolve conflicting views in the literature. Our results highlight the density of states in the organic semiconductor as a key factor. Its shape and, in particular, the energy distribution of electronic states tailing into the fundamental gap is found to determine both the minimum value of practically achievable injection barriers as well as their spatial profile, ranging from abrupt interface dipoles to extended band-bending regions. PMID:24938867

Design and in vivo evaluation of more efficient and selective deep brain stimulation electrodes

Science.gov (United States)

Howell, Bryan; Huynh, Brian; Grill, Warren M.

2015-08-01

Objective. Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, the efficiency and selectivity of DBS can be improved. Our objective was to design electrode geometries that increased the efficiency and selectivity of DBS. Approach. We coupled computational models of electrodes in brain tissue with cable models of axons of passage (AOPs), terminating axons (TAs), and local neurons (LNs); we used engineering optimization to design electrodes for stimulating these neural elements; and the model predictions were tested in vivo. Main results. Compared with the standard electrode used in the Medtronic Model 3387 and 3389 arrays, model-optimized electrodes consumed 45-84% less power. Similar gains in selectivity were evident with the optimized electrodes: 50% of parallel AOPs could be activated while reducing activation of perpendicular AOPs from 44 to 48% with the standard electrode to 0-14% with bipolar designs; 50% of perpendicular AOPs could be activated while reducing activation of parallel AOPs from 53 to 55% with the standard electrode to 1-5% with an array of cathodes; and, 50% of TAs could be activated while reducing activation of AOPs from 43 to 100% with the standard electrode to 2-15% with a distal anode. In vivo, both the geometry and polarity of the electrode had a profound impact on the efficiency and selectivity of stimulation. Significance. Model-based design is a powerful tool that can be used to improve the efficiency and selectivity of DBS electrodes.

Orientation-modulated attention effect on visual evoked potential: Application for PIN system using brain-computer interface.

Science.gov (United States)

Wilaiprasitporn, Theerawit; Yagi, Tohru

2015-01-01

This research demonstrates the orientation-modulated attention effect on visual evoked potential. We combined this finding with our previous findings about the motion-modulated attention effect and used the result to develop novel visual stimuli for a personal identification number (PIN) application based on a brain-computer interface (BCI) framework. An electroencephalography amplifier with a single electrode channel was sufficient for our application. A computationally inexpensive algorithm and small datasets were used in processing. Seven healthy volunteers participated in experiments to measure offline performance. Mean accuracy was 83.3% at 13.9 bits/min. Encouraged by these results, we plan to continue developing the BCI-based personal identification application toward real-time systems.

Comparison of the HiFocus Mid-Scala and HiFocus 1J Electrode Array: Angular Insertion Depths and Speech Perception Outcomes.

Science.gov (United States)

van der Jagt, M Annerie; Briaire, Jeroen J; Verbist, Berit M; Frijns, Johan H M

2016-01-01

The HiFocus Mid-Scala (MS) electrode array has recently been introduced onto the market. This precurved design with a targeted mid-scalar intracochlear position pursues an atraumatic insertion and optimal distance for neural stimulation. In this study we prospectively examined the angular insertion depth achieved and speech perception outcomes resulting from the HiFocus MS electrode array for 6 months after implantation, and retrospectively compared these with the HiFocus 1J lateral wall electrode array. The mean angular insertion depth within the MS population (n = 96) was found at 470°. This was 50° shallower but more consistent than the 1J electrode array (n = 110). Audiological evaluation within a subgroup, including only postlingual, unilaterally implanted, adult cochlear implant recipients who were matched on preoperative speech perception scores and the duration of deafness (MS = 32, 1J = 32), showed no difference in speech perception outcomes between the MS and 1J groups. Furthermore, speech perception outcome was not affected by the angular insertion depth or frequency mismatch. © 2016 S. Karger AG, Basel.

Non-linear response of electrode-electrolyte interface at high current density

International Nuclear Information System (INIS)

Ruiz, G.A.; Felice, C.J.; Valentinuzzi, M.E.

2005-01-01

A distributed parameter non-linear circuit is presented as fractal model of an electrode-electrolyte interface. It includes the charge transfer resistance and the double layer capacitance at each fractal level. The circuit explains the linear behavior of its series equivalent resistance R eq with signals of amplitudes eq Fourier spectrum. As a consequence, both the equivalent resistance and reactance drop with voltage, facts reported experimentally by other authors

Tutorial: Signal Processing in Brain-Computer Interfaces

NARCIS (Netherlands)

Garcia Molina, G.

2010-01-01

Research in Electroencephalogram (EEG) based Brain-Computer Interfaces (BCIs) has been considerably expanding during the last few years. Such an expansion owes to a large extent to the multidisciplinary and challenging nature of BCI research. Signal processing undoubtedly constitutes an essential

Fiber-based tissue identification for electrode placement in deep brain stimulation neurosurgery (Conference Presentation)

Science.gov (United States)

DePaoli, Damon T.; Lapointe, Nicolas; Goetz, Laurent; Parent, Martin; Prudhomme, Michel; Cantin, Léo.; Galstian, Tigran; Messaddeq, Younès.; Côté, Daniel C.

2016-03-01

Deep brain stimulation's effectiveness relies on the ability of the stimulating electrode to be properly placed within a specific target area of the brain. Optical guidance techniques that can increase the accuracy of the procedure, without causing any additional harm, are therefore of great interest. We have designed a cheap optical fiber-based device that is small enough to be placed within commercially available DBS stimulating electrodes' hollow cores and that is capable of sensing biological information from the surrounding tissue, using low power white light. With this probe we have shown the ability to distinguish white and grey matter as well as blood vessels, in vitro, in human brain samples and in vivo, in rats. We have also repeated the in vitro procedure with the probe inserted in a DBS stimulating electrode and found the results were in good agreement. We are currently validating a second fiber optic device, with micro-optical components, that will result in label free, molecular level sensing capabilities, using CARS spectroscopy. The final objective will be to use this data in real time, during deep brain stimulation neurosurgery, to increase the safety and accuracy of the procedure.

High-performance all-printed amorphous oxide FETs and logics with electronically compatible electrode/ channel interface.

Science.gov (United States)

Sharma, Bhupendra Kumar; Stoesser, Anna; Mondal, Sandeep Kumar; Garlapati, Suresh K; Fawey, Mohammed H; Chakravadhanula, Venkata Sai Kiran; Kruk, Robert; Hahn, Horst; Dasgupta, Subho

2018-06-12

Oxide semiconductors typically show superior device performance compared to amorphous silicon or organic counterparts, especially, when they are physical vapor deposited. However, it is not easy to reproduce identical device characteristics when the oxide field-effect transistors (FETs) are solution-processed/ printed; the level of complexity further intensifies with the need to print the passive elements as well. Here, we developed a protocol for designing the most electronically compatible electrode/ channel interface based on the judicious material selection. Exploiting this newly developed fabrication schemes, we are now able to demonstrate high-performance all-printed FETs and logic circuits using amorphous indium-gallium-zinc oxide (a-IGZO) semiconductor, indium tin oxide (ITO) as electrodes and composite solid polymer electrolyte as the gate insulator. Interestingly, all-printed FETs demonstrate an optimal electrical performance in terms of threshold voltages and device mobility and may very well be compared with devices fabricated using sputtered ITO electrodes. This observation originates from the selection of electrode/ channel materials from the same transparent semiconductor oxide family, resulting in the formation of In-Sn-Zn-O (ITZO) based diffused a-IGZO/ ITO interface that controls doping density while ensuring high electrical performance. Compressive spectroscopic studies reveal that Sn doping mediated excellent band alignment of IGZO with ITO electrodes is responsible for the excellent device performance observed. All-printed n-MOS based logic circuits have also been demonstrated towards new-generation portable electronics.

Papers from the Fifth International Brain-Computer Interface Meeting

Science.gov (United States)

Huggins, Jane E.; Wolpaw, Jonathan R.

2014-06-01

Brain-computer interfaces (BCIs), also known as brain-machine interfaces (BMIs), translate brain activity into new outputs that replace, restore, enhance, supplement or improve natural brain outputs. BCI research and development has grown rapidly for the past two decades. It is beginning to provide useful communication and control capacities to people with severe neuromuscular disabilities; and it is expanding into new areas such as neurorehabilitation that may greatly increase its clinical impact. At the same time, significant challenges remain, particularly in regard to translating laboratory advances into clinical use. The papers in this special section report some of the work presented at the Fifth International BCI Meeting held on 3-7 June 2013 at the Asilomar Conference Center in Pacific Grove, California, USA. Like its predecessors over the past 15 years, this meeting was supported by the National Institutes of Health, the National Science Foundation, and a variety of other governmental and private sponsors [1]. This fifth meeting was organized and managed by a program committee of BCI researchers from throughout the world [2]. It retained the distinctive retreat-style format developed by the Wadsworth Center researchers who organized and managed the first four meetings. The 301 attendees came from 165 research groups in 29 countries; 37% were students or postdoctoral fellows. Of more than 200 extended abstracts submitted for peer review, 25 were selected for oral presentation [3], and 181 were presented as posters [4] and published in the open-access conference proceedings [5]. The meeting featured 19 highly interactive workshops [6] covering the broad spectrum of BCI research and development, as well as many demonstrations of BCI systems and associated technology. Like the first four meetings, this one included attendees and embraced topics from across the broad spectrum of disciplines essential to effective BCI research and development, including

A comparison of recording modalities of P300 event-related potentials (ERP) for brain-computer interface (BCI) paradigm.

Science.gov (United States)

Mayaud, L; Congedo, M; Van Laghenhove, A; Orlikowski, D; Figère, M; Azabou, E; Cheliout-Heraut, F

2013-10-01

A brain-computer interface aims at restoring communication and control in severely disabled people by identification and classification of EEG features such as event-related potentials (ERPs). The aim of this study is to compare different modalities of EEG recording for extraction of ERPs. The first comparison evaluates the performance of six disc electrodes with that of the EMOTIV headset, while the second evaluates three different electrode types (disc, needle, and large squared electrode). Ten healthy volunteers gave informed consent and were randomized to try the traditional EEG system (six disc electrodes with gel and skin preparation) or the EMOTIV Headset first. Together with the six disc electrodes, a needle and a square electrode of larger surface were simultaneously recording near lead Cz. Each modality was evaluated over three sessions of auditory P300 separated by one hour. No statically significant effect was found for the electrode type, nor was the interaction between electrode type and session number. There was no statistically significant difference of performance between the EMOTIV and the six traditional EEG disc electrodes, although there was a trend showing worse performance of the EMOTIV headset. However, the modality-session interaction was highly significant (P<0.001) showing that, while the performance of the six disc electrodes stay constant over sessions, the performance of the EMOTIV headset drops dramatically between 2 and 3h of use. Finally, the evaluation of comfort by participants revealed an increasing discomfort with the EMOTIV headset starting with the second hour of use. Our study does not recommend the use of one modality over another based on performance but suggests the choice should be made on more practical considerations such as the expected length of use, the availability of skilled labor for system setup and above all, the patient comfort. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Materials Science of Electrodes and Interfaces for High-Performance Organic Photovoltaics

Energy Technology Data Exchange (ETDEWEB)

Marks, Tobin [Northwestern Univ., Evanston, IL (United States)

2016-11-18

The science of organic photovoltaic (OPV) cells has made dramatic advances over the past three years with power conversion efficiencies (PCEs) now reaching ~12%. The upper PCE limit of light-to-electrical power conversion for single-junction OPVs as predicted by theory is ~23%. With further basic research, the vision of such devices, composed of non-toxic, earth-abundant, readily easily processed materials replacing/supplementing current-generation inorganic solar cells may become a reality. Organic cells offer potentially low-cost, roll-to-roll manufacturable, and durable solar power for diverse in-door and out-door applications. Importantly, further gains in efficiency and durability, to that competitive with inorganic PVs, will require fundamental, understanding-based advances in transparent electrode and interfacial materials science and engineering. This team-science research effort brought together an experienced and highly collaborative interdisciplinary group with expertise in hard and soft matter materials chemistry, materials electronic structure theory, solar cell fabrication and characterization, microstructure characterization, and low temperature materials processing. We addressed in unconventional ways critical electrode-interfacial issues underlying OPV performance -- controlling band offsets between transparent electrodes and organic active-materials, addressing current loss/leakage phenomena at interfaces, and new techniques in cost-effective low temperature and large area cell fabrication. The research foci were: 1) Theory-guided design and synthesis of advanced crystalline and amorphous transparent conducting oxide (TCO) layers which test our basic understanding of TCO structure-transport property relationships, and have high conductivity, transparency, and tunable work functions but without (or minimizing) the dependence on indium. 2) Development of theory-based understanding of optimum configurations for the interfaces between oxide electrodes

PEDOT:PSS interfaces support the development of neuronal synaptic networks with reduced neuroglia response in vitro

Directory of Open Access Journals (Sweden)

Giada eCellot

2016-01-01

Full Text Available The design of electrodes based on conductive polymers in brain-machine interface technology offers the opportunity to exploit variably manufactured materials to reduce gliosis, indeed the most common brain response to chronically implanted neural electrodes. In fact, the use of conductive polymers, finely tailored in their physical-chemical properties, might result in electrodes with improved adaptability to the brain tissue and increased charge-transfer efficiency. Here we interfaced poly(3,4-ethylenedioxythiophene:poly(styrene sulfonate (PEDOT:PSS doped with different amounts of ethylene glycol (EG with rat hippocampal primary cultures grown for 3 weeks on these synthetic substrates. We used immunofluorescence and scanning electron microscopy combined to single cell electrophysiology to assess the biocompatibility of PEDOT:PSS in terms of neuronal growth and synapse formation. We investigated neuronal morphology, density and electrical activity. We reported the novel observation that opposite to neurons, glial cell density was progressively reduced, hinting at the ability of this material to down regulate glial reaction. Thus PEDOT:PSS is an attractive candidate for the design of new implantable electrodes, controlling the extent of glial reactivity without affecting neuronal viability and function.

Motor outcome and electrode location in deep brain stimulation in Parkinson's disease.

Science.gov (United States)

Koivu, Maija; Huotarinen, Antti; Scheperjans, Filip; Laakso, Aki; Kivisaari, Riku; Pekkonen, Eero

2018-05-30

To evaluate the efficacy and adverse effects of subthalamic deep brain stimulation (STN-DBS) in patients with advanced Parkinson's disease (PD) and the possible correlation between electrode location and clinical outcome. We retrospectively reviewed 87 PD-related STN-DBS operations at Helsinki University Hospital (HUH) from 2007 to 2014. The changes of Unified Parkinson's Disease Rating Scale (UPDRS) part III score, Hoehn & Yahr stage, antiparkinson medication, and adverse effects were studied. We estimated the active electrode location in three different coordinate systems: direct visual analysis of MRI correlated to brain atlas, location in relation to the nucleus borders and location in relation to the midcommisural point. At 6 months after operation, both levodopa equivalent doses (LEDs; 35%, Wilcoxon signed-rank test = 0.000) and UPDRS part III scores significantly decreased (38%, Wilcoxon signed-rank test = 0.000). Four patients (5%) suffered from moderate DBS-related dysarthria. The generator and electrodes had to be removed in one patient due to infection (1%). Electrode coordinates in the three coordinate systems correlated well with each other. On the left side, more ventral location of the active contact was associated with greater LED decrease. STN-DBS improves motor function and enables the reduction in antiparkinson medication with an acceptable adverse effect profile. More ventral location of the active contact may allow stronger LED reduction. Further research on the correlation between contact location, clinical outcome, and LED reduction is warranted. © 2018 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.

Evaluating brain-computer interface performance using color in the P300 checkerboard speller.

Science.gov (United States)

Ryan, D B; Townsend, G; Gates, N A; Colwell, K; Sellers, E W

2017-10-01

Current Brain-Computer Interface (BCI) systems typically flash an array of items from grey to white (GW). The objective of this study was to evaluate BCI performance using uniquely colored stimuli. In addition to the GW stimuli, the current study tested two types of color stimuli (grey to color [GC] and color intensification [CI]). The main hypotheses were that in a checkboard paradigm, unique color stimuli will: (1) increase BCI performance over the standard GW paradigm; (2) elicit larger event-related potentials (ERPs); and, (3) improve offline performance with an electrode selection algorithm (i.e., Jumpwise). Online results (n=36) showed that GC provides higher accuracy and information transfer rate than the CI and GW conditions. Waveform analysis showed that GC produced higher amplitude ERPs than CI and GW. Information transfer rate was improved by the Jumpwise-selected channel locations in all conditions. Unique color stimuli (GC) improved BCI performance and enhanced ERPs. Jumpwise-selected electrode locations improved offline performance. These results show that in a checkerboard paradigm, unique color stimuli increase BCI performance, are preferred by participants, and are important to the design of end-user applications; thus, could lead to an increase in end-user performance and acceptance of BCI technology. Copyright © 2017 International Federation of Clinical Neurophysiology. All rights reserved.

Post-breakdown secondary discharges at the electrode/dielectric interface of a cylindrical barrier discharge

Science.gov (United States)

Carman, Robert; Ward, Barry; Kane, Deborah

2011-10-01

The electrical breakdown characteristics of a double-walled cylindrical dielectric barrier discharge (DBD) lamp with a neon buffer gas under pulsed voltage excitation have been investigated. Following the formation of plasma in the main discharge gap, we have observed secondary breakdown phenomena at the inner and outer mesh electrode/dielectric interfaces under specific operating conditions. Plasma formation at these interfaces is investigated by monitoring the Ozone production rate in controlled flows of ultra high purity oxygen together with the overall electrical voltage-charge characteristics of the lamp. The results show that this secondary breakdown only occurs after the main discharge plasma has been established, and that significant electrical power may be dissipated in generating these spurious secondary plasmas. The results are important with regards to optimising the design and identifying efficient operating regimes of DBD based devices that employ mesh-type or wire/strip electrodes.

Optimizing the Usability of Brain-Computer Interfaces.

Science.gov (United States)

Zhang, Yin; Chase, Steve M

2018-03-22

Brain-computer interfaces are in the process of moving from the laboratory to the clinic. These devices act by reading neural activity and using it to directly control a device, such as a cursor on a computer screen. An open question in the field is how to map neural activity to device movement in order to achieve the most proficient control. This question is complicated by the fact that learning, especially the long-term skill learning that accompanies weeks of practice, can allow subjects to improve performance over time. Typical approaches to this problem attempt to maximize the biomimetic properties of the device in order to limit the need for extensive training. However, it is unclear if this approach would ultimately be superior to performance that might be achieved with a nonbiomimetic device once the subject has engaged in extended practice and learned how to use it. Here we approach this problem using ideas from optimal control theory. Under the assumption that the brain acts as an optimal controller, we present a formal definition of the usability of a device and show that the optimal postlearning mapping can be written as the solution of a constrained optimization problem. We then derive the optimal mappings for particular cases common to most brain-computer interfaces. Our results suggest that the common approach of creating biomimetic interfaces may not be optimal when learning is taken into account. More broadly, our method provides a blueprint for optimal device design in general control-theoretic contexts.

Fluctuations at electrode-YSZ interfaces

DEFF Research Database (Denmark)

Jacobsen, Torben; Hansen, Karin Vels; Skou, Eivind

2005-01-01

Current fluctuations at potentiostatically controlled point electrodes of Pt, La$_{0.85}$Sr$_{0.15}$MnO$_3$ and Ni on YSZ surfaces are determined at 1000$^\\circ$C. For the oxygen reduction process on Pt electrodes characteristic sawtooth shaped low frequency fluctuations are observed. At temperat......Current fluctuations at potentiostatically controlled point electrodes of Pt, La$_{0.85}$Sr$_{0.15}$MnO$_3$ and Ni on YSZ surfaces are determined at 1000$^\\circ$C. For the oxygen reduction process on Pt electrodes characteristic sawtooth shaped low frequency fluctuations are observed....../water atmosphere are presented for discussion. The origin of the observations is not known at present but it appears likely that they are related to the activation/deactivation mechanism of SOFCs....

Using brain-computer interfaces and brain-state dependent stimulation as tools in cognitive neuroscience

NARCIS (Netherlands)

Jensen, O.; Bahramisharif, A.; Oostenveld, R.; Klanke, S.; Hadjipapas, A.; Okazaki, Y.O.; Gerven, M.A.J. van

2011-01-01

Large efforts are currently being made to develop and improve online analysis of brain activity which can be used, e.g., for brain–computer interfacing (BCI). A BCI allows a subject to control a device by willfully changing his/her own brain activity. BCI therefore holds the promise as a tool for

A wireless brain-machine interface for real-time speech synthesis.

Directory of Open Access Journals (Sweden)

Frank H Guenther

2009-12-01

Full Text Available Brain-machine interfaces (BMIs involving electrodes implanted into the human cerebral cortex have recently been developed in an attempt to restore function to profoundly paralyzed individuals. Current BMIs for restoring communication can provide important capabilities via a typing process, but unfortunately they are only capable of slow communication rates. In the current study we use a novel approach to speech restoration in which we decode continuous auditory parameters for a real-time speech synthesizer from neuronal activity in motor cortex during attempted speech.Neural signals recorded by a Neurotrophic Electrode implanted in a speech-related region of the left precentral gyrus of a human volunteer suffering from locked-in syndrome, characterized by near-total paralysis with spared cognition, were transmitted wirelessly across the scalp and used to drive a speech synthesizer. A Kalman filter-based decoder translated the neural signals generated during attempted speech into continuous parameters for controlling a synthesizer that provided immediate (within 50 ms auditory feedback of the decoded sound. Accuracy of the volunteer's vowel productions with the synthesizer improved quickly with practice, with a 25% improvement in average hit rate (from 45% to 70% and 46% decrease in average endpoint error from the first to the last block of a three-vowel task.Our results support the feasibility of neural prostheses that may have the potential to provide near-conversational synthetic speech output for individuals with severely impaired speech motor control. They also provide an initial glimpse into the functional properties of neurons in speech motor cortical areas.

A brain electrophysiological correlate of depth perception

International Nuclear Information System (INIS)

Akay, Ahmet; Celebi, Gurbuz

2009-01-01

To investigate brain electrical activity accompanying depth perception using random-dot stereograms. Additional experiments were conducted to ascertain the specificity of this potential to depth perception. In the present study, we performed 3 different and independent experiments on 34 subjects to establish the relationship between depth perception and its cortical electrophysiological correlate. Visual evoked potentials in response to visual stimulation by random-dot stereograms were recorded. To achieve this goal, a data acquisition and analysis system, different from common visual evoked potential recording systems, consisting of 2 personal computers, was used. One of the computers was used to generate the visual stimulus patterns and the other to record and digitally average the potentials evoked by the stimuli. This study was carried out at the Department of Biophysics of Ege University Medical School, Izmir, Turkey, from April to December, 2006. A negative potential component, which is thought to arise in association with depth perception, was recorded from the occipital region from 30 of the 34 subjects. Typically, it had a mean latency of 211.46 ms and 6.40 micron V amplitude. The negative potential is related to depth perception, as this component is present in the responses to stimulus, which carries disparity information but is absent when the stimulus is switched to no disparity information. Additional experiments also showed that the specificity of this component to depth perception becomes evident beyond doubt. (author)

Brain-Computer Interface Games: Towards a Framework.

NARCIS (Netherlands)

Gürkök, Hayrettin; Nijholt, Antinus; Poel, Mannes; Herrlich, Marc; Malaka, Rainer; Masuch, Maic

2012-01-01

The brain-computer interface (BCI) community started to consider games as potential applications while the games community started to consider BCI as a game controller. However, there is a discrepancy between the BCI games developed by the two communities. In this paper, we propose a preliminary BCI

Brain-Computer Interfaces Revolutionizing Human-Computer Interaction

CERN Document Server

Graimann, Bernhard; Allison, Brendan

2010-01-01

A brain-computer interface (BCI) establishes a direct output channel between the human brain and external devices. BCIs infer user intent via direct measures of brain activity and thus enable communication and control without movement. This book, authored by experts in the field, provides an accessible introduction to the neurophysiological and signal-processing background required for BCI, presents state-of-the-art non-invasive and invasive approaches, gives an overview of current hardware and software solutions, and reviews the most interesting as well as new, emerging BCI applications. The book is intended not only for students and young researchers, but also for newcomers and other readers from diverse backgrounds keen to learn about this vital scientific endeavour.

Dynamic impedance model of the skin-electrode interface for transcutaneous electrical stimulation.

Directory of Open Access Journals (Sweden)

José Luis Vargas Luna

Full Text Available Transcutaneous electrical stimulation can depolarize nerve or muscle cells applying impulses through electrodes attached on the skin. For these applications, the electrode-skin impedance is an important factor which influences effectiveness. Various models describe the interface using constant or current-depending resistive-capacitive equivalent circuit. Here, we develop a dynamic impedance model valid for a wide range stimulation intensities. The model considers electroporation and charge-dependent effects to describe the impedance variation, which allows to describe high-charge pulses. The parameters were adjusted based on rectangular, biphasic stimulation pulses generated by a stimulator, providing optionally current or voltage-controlled impulses, and applied through electrodes of different sizes. Both control methods deliver a different electrical field to the tissue, which is constant throughout the impulse duration for current-controlled mode or have a very current peak for voltage-controlled. The results show a predominant dependence in the current intensity in the case of both stimulation techniques that allows to keep a simple model. A verification simulation using the proposed dynamic model shows coefficient of determination of around 0.99 in both stimulation types. The presented method for fitting electrode-skin impedance can be simple extended to other stimulation waveforms and electrode configuration. Therefore, it can be embedded in optimization algorithms for designing electrical stimulation applications even for pulses with high charges and high current spikes.

Spatial co-adaptation of cortical control columns in a micro-ECoG brain-computer interface

Science.gov (United States)

Rouse, A. G.; Williams, J. J.; Wheeler, J. J.; Moran, D. W.

2016-10-01

Objective. Electrocorticography (ECoG) has been used for a range of applications including electrophysiological mapping, epilepsy monitoring, and more recently as a recording modality for brain-computer interfaces (BCIs). Studies that examine ECoG electrodes designed and implanted chronically solely for BCI applications remain limited. The present study explored how two key factors influence chronic, closed-loop ECoG BCI: (i) the effect of inter-electrode distance on BCI performance and (ii) the differences in neural adaptation and performance when fixed versus adaptive BCI decoding weights are used. Approach. The amplitudes of epidural micro-ECoG signals between 75 and 105 Hz with 300 μm diameter electrodes were used for one-dimensional and two-dimensional BCI tasks. The effect of inter-electrode distance on BCI control was tested between 3 and 15 mm. Additionally, the performance and cortical modulation differences between constant, fixed decoding using a small subset of channels versus adaptive decoding weights using the entire array were explored. Main results. Successful BCI control was possible with two electrodes separated by 9 and 15 mm. Performance decreased and the signals became more correlated when the electrodes were only 3 mm apart. BCI performance in a 2D BCI task improved significantly when using adaptive decoding weights (80%-90%) compared to using constant, fixed weights (50%-60%). Additionally, modulation increased for channels previously unavailable for BCI control under the fixed decoding scheme upon switching to the adaptive, all-channel scheme. Significance. Our results clearly show that neural activity under a BCI recording electrode (which we define as a ‘cortical control column’) readily adapts to generate an appropriate control signal. These results show that the practical minimal spatial resolution of these control columns with micro-ECoG BCI is likely on the order of 3 mm. Additionally, they show that the combination and

Brain-Computer Interface Games: Towards a Framework

NARCIS (Netherlands)

Gürkök, Hayrettin; Nijholt, Antinus; Poel, Mannes; Nakatsu, Ryohei; Rauterberg, Matthias; Ciancarini, Paolo

2015-01-01

The brain-computer interface (BCI) community has started to consider games as potential applications, while the game community has started to consider BCI as a game controller. However, there is a discrepancy between the BCI games developed by the two communities. This not only adds to the workload

Stretchable Transparent Electrode Arrays for Simultaneous Electrical and Optical Interrogation of Neural Circuits in Vivo.

Science.gov (United States)

Zhang, Jing; Liu, Xiaojun; Xu, Wenjing; Luo, Wenhan; Li, Ming; Chu, Fangbing; Xu, Lu; Cao, Anyuan; Guan, Jisong; Tang, Shiming; Duan, Xiaojie

2018-04-09

Recent developments of transparent electrode arrays provide a unique capability for simultaneous optical and electrical interrogation of neural circuits in the brain. However, none of these electrode arrays possess the stretchability highly desired for interfacing with mechanically active neural systems, such as the brain under injury, the spinal cord, and the peripheral nervous system (PNS). Here, we report a stretchable transparent electrode array from carbon nanotube (CNT) web-like thin films that retains excellent electrochemical performance and broad-band optical transparency under stretching and is highly durable under cyclic stretching deformation. We show that the CNT electrodes record well-defined neuronal response signals with negligible light-induced artifacts from cortical surfaces under optogenetic stimulation. Simultaneous two-photon calcium imaging through the transparent CNT electrodes from cortical surfaces of GCaMP-expressing mice with epilepsy shows individual activated neurons in brain regions from which the concurrent electrical recording is taken, thus providing complementary cellular information in addition to the high-temporal-resolution electrical recording. Notably, the studies on rats show that the CNT electrodes remain operational during and after brain contusion that involves the rapid deformation of both the electrode array and brain tissue. This enables real-time, continuous electrophysiological monitoring of cortical activity under traumatic brain injury. These results highlight the potential application of the stretchable transparent CNT electrode arrays in combining electrical and optical modalities to study neural circuits, especially under mechanically active conditions, which could potentially provide important new insights into the local circuit dynamics of the spinal cord and PNS as well as the mechanism underlying traumatic injuries of the nervous system.

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.

Theory of bulk and interface constant phase elements in electrode- electrolyte systems

International Nuclear Information System (INIS)

Liu, S.H.

1991-01-01

This paper summarizes the progress gained in the last few years in our understanding of bulk and interface constant-phase-angle (CPA) behavior in electrode-electrolyte systems. It is now fairly well established that the interface constant-phase element originates from the fractal nature of the interface. The complex geometry gives rise to a fractal distribution of parallel current paths, and the competition between these paths results in the fractional power law behavior of the impedance across the interface. On the other hand, the early hope of relating the CPA exponent to the fractal dimension of the interface has been shown to be unattainable. Our understanding of the bulk CPA behavior, which is most prevalent in solid electrolytes, is only tentative. It is illustrated using a simple model that, under nonlinear dynamical laws that govern the flow of ions in the electrolyte, a current in the solid can generate a fractal distribution of vacancies which tend to impede the flow. The current is forced to negotiate a complex path through the solid, and the resulting fluctuation in path length and flow rate could be a source of the CPA behavior. 32 refs., 18 figs

The Self-Paced Graz Brain-Computer Interface: Methods and Applications

Directory of Open Access Journals (Sweden)

Reinhold Scherer

2007-01-01

Full Text Available We present the self-paced 3-class Graz brain-computer interface (BCI which is based on the detection of sensorimotor electroencephalogram (EEG rhythms induced by motor imagery. Self-paced operation means that the BCI is able to determine whether the ongoing brain activity is intended as control signal (intentional control or not (non-control state. The presented system is able to automatically reduce electrooculogram (EOG artifacts, to detect electromyographic (EMG activity, and uses only three bipolar EEG channels. Two applications are presented: the freeSpace virtual environment (VE and the Brainloop interface. The freeSpace is a computer-game-like application where subjects have to navigate through the environment and collect coins by autonomously selecting navigation commands. Three subjects participated in these feedback experiments and each learned to navigate through the VE and collect coins. Two out of the three succeeded in collecting all three coins. The Brainloop interface provides an interface between the Graz-BCI and Google Earth.

On robust parameter estimation in brain-computer interfacing

Science.gov (United States)

Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert

2017-12-01

Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.

A split microdrive for simultaneous multi-electrode recordings from two brain areas in awake small animals.

NARCIS (Netherlands)

Lansink, C.S.; Bakker, M.; Buster, W.; Lankelma, J.; van der Blom, R.; Westdorp, R.; Joosten, R.N.J.M.A.; Mc.Naughton, B.L.; Pennartz, C.M.A.

2007-01-01

Complex cognitive operations such as memory formation and decision-making are thought to be mediated not by single, isolated brain structures but by multiple, connected brain areas. To facilitate studies on the neural communication between connected brain structures, we developed a multi-electrode

A comprehensive survey of brain interface technology designs.

Science.gov (United States)

Mason, S G; Bashashati, A; Fatourechi, M; Navarro, K F; Birch, G E

2007-02-01

In this work we present the first comprehensive survey of Brain Interface (BI) technology designs published prior to January 2006. Detailed results from this survey, which was based on the Brain Interface Design Framework proposed by Mason and Birch, are presented and discussed to address the following research questions: (1) which BI technologies are directly comparable, (2) what technology designs exist, (3) which application areas (users, activities and environments) have been targeted in these designs, (4) which design approaches have received little or no research and are possible opportunities for new technology, and (5) how well are designs reported. The results of this work demonstrate that meta-analysis of high-level BI design attributes is possible and informative. The survey also produced a valuable, historical cross-reference where BI technology designers can identify what types of technology have been proposed and by whom.

Mind the Sheep! User Experience Evaluation & Brain-Computer Interface Games

NARCIS (Netherlands)

Gürkök, Hayrettin

2012-01-01

A brain-computer interface (BCI) infers our actions (e.g. a movement), intentions (e.g. preparation for a movement) and psychological states (e.g. emotion, attention) by interpreting our brain signals. It uses the inferences it makes to manipulate a computer. Although BCIs have long been used

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 believe

Brain barriers and functional interfaces with sequential appearance of ABC efflux transporters during human development

DEFF Research Database (Denmark)

Møllgård, Kjeld; Dziegielewska, Katarzyna M.; Holst, Camilla B.

2017-01-01

Adult brain is protected from entry of drugs and toxins by specific mechanisms such as ABC (ATP-binding Cassette) efflux transporters. Little is known when these appear in human brain during development. Cellular distribution of three main ABC transporters (ABCC1, ABCG2, ABCB1) was determined...... at blood-brain barriers and interfaces in human embryos and fetuses in first half of gestation. Antibodies against claudin-5 and-11 and antibodies to α-fetoprotein were used to describe morphological and functional aspects of brain barriers. First exchange interfaces to be established, probably at 4...... three transporters. Results provide evidence for sequential establishment of brain exchange interfaces and spatial and temporal timetable for three main ABC transporters in early human brain....

A covert attention P300-based brain-computer interface: Geospell.

Science.gov (United States)

Aloise, Fabio; Aricò, Pietro; Schettini, Francesca; Riccio, Angela; Salinari, Serenella; Mattia, Donatella; Babiloni, Fabio; Cincotti, Febo

2012-01-01

The Farwell and Donchin P300 speller interface is one of the most widely used brain-computer interface (BCI) paradigms for writing text. Recent studies have shown that the recognition accuracy of the P300 speller decreases significantly when eye movement is impaired. This report introduces the GeoSpell interface (Geometric Speller), which implements a stimulation framework for a P300-based BCI that has been optimised for operation in covert visual attention. We compared the Geospell with the P300 speller interface under overt attention conditions with regard to effectiveness, efficiency and user satisfaction. Ten healthy subjects participated in the study. The performance of the GeoSpell interface in covert attention was comparable with that of the P300 speller in overt attention. As expected, the effectiveness of the spelling decreased with the new interface in covert attention. The NASA task load index (TLX) for workload assessment did not differ significantly between the two modalities. This study introduces and evaluates a gaze-independent, P300-based brain-computer interface, the efficacy and user satisfaction of which were comparable with those off the classical P300 speller. Despite a decrease in effectiveness due to the use of covert attention, the performance of the GeoSpell far exceeded the threshold of accuracy with regard to effective spelling.

A diamond-based electrode for detection of neurochemicals in the human brain

Directory of Open Access Journals (Sweden)

Kevin E. Bennet

2016-03-01

Full Text Available Deep brain stimulation (DBS, a surgical technique to treat certain neurologic and psychiatric conditions, relies on pre-determined stimulation parameters in an open-loop configuration. The major advancement in DBS devices is a closed-loop system that uses neurophysiologic feedback to dynamically adjust stimulation frequency and amplitude. Stimulation-driven neurochemical release can be measured by fast-scan cyclic voltammetry (FSCV, but existing FSCV electrodes rely on carbon fiber, which degrades quickly during use and is therefore unsuitable for chronic neurochemical recording. To address this issue, we developed durable, synthetic boron-doped diamond-based electrodes capable of measuring neurochemical release in humans. Compared to carbon fiber electrodes, they were more than two orders-of-magnitude more physically-robust and demonstrated longevity in vitro without deterioration. Applied for the first time in humans, diamond electrode recordings from thalamic targets in patients (n=4 undergoing DBS for tremor produced signals consistent with adenosine release at a sensitivity comparable to carbon fiber electrodes.

Third Workshop on Affective Brain-Computer Interfaces: introduction

NARCIS (Netherlands)

Mühl, C.; Chanel, G.; Allison, B.; Nijholt, Antinus

2013-01-01

Following the first and second workshop on affective brain-computer interfaces, held in conjunction with ACII in Amsterdam (2009) and Memphis (2011), the third workshop explores the advantages and limitations of using neurophysiological signals for the automatic recognition of affective and

Time to address the problems at the neural interface

Science.gov (United States)

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

2014-04-01

Neural engineers have made significant, if not remarkable, progress in interfacing with the nervous system in the last ten years. In particular, neuromodulation of the brain has generated significant therapeutic benefits [1-5]. EEG electrodes can be used to communicate with patients with locked-in syndrome [6]. In the central nervous system (CNS), electrode arrays placed directly over or within the cortex can record neural signals related to the intent of the subject or patient [7, 8]. A similar technology has allowed paralyzed patients to control an otherwise normal skeletal system with brain signals [9, 10]. This technology has significant potential to restore function in these and other patients with neural disorders such as stroke [11]. Although there are several multichannel arrays described in the literature, the workhorse for these cortical interfaces has been the Utah array [12]. This 100-channel electrode array has been used in most studies on animals and humans since the 1990s and is commercially available. This array and other similar microelectrode arrays can record neural signals with high quality (high signal-to-noise ratio), but these signals fade and disappear after a few months and therefore the current technology is not reliable for extended periods of time. Therefore, despite these major advances in communicating with the brain, clinical translation cannot be implemented. The reasons for this failure are not known but clearly involve the interface between the electrode and the neural tissue. The Defense Advanced Research Project Agency (DARPA) as well as other federal funding agencies such as the National Science Foundation (NSF) and the National Institutes of Health have provided significant financial support to investigate this problem without much success. A recent funding program from DARPA was designed to establish the failure modes in order to generate a reliable neural interface technology and again was unsuccessful at producing a robust

Chronic multisite brain recordings from a totally implantable bidirectional neural interface: experience in 5 patients with Parkinson's disease.

Science.gov (United States)

Swann, Nicole C; de Hemptinne, Coralie; Miocinovic, Svjetlana; Qasim, Salman; Ostrem, Jill L; Galifianakis, Nicholas B; Luciano, Marta San; Wang, Sarah S; Ziman, Nathan; Taylor, Robin; Starr, Philip A

2018-02-01

OBJECTIVE Dysfunction of distributed neural networks underlies many brain disorders. The development of neuromodulation therapies depends on a better understanding of these networks. Invasive human brain recordings have a favorable temporal and spatial resolution for the analysis of network phenomena but have generally been limited to acute intraoperative recording or short-term recording through temporarily externalized leads. Here, the authors describe their initial experience with an investigational, first-generation, totally implantable, bidirectional neural interface that allows both continuous therapeutic stimulation and recording of field potentials at multiple sites in a neural network. METHODS Under a physician-sponsored US Food and Drug Administration investigational device exemption, 5 patients with Parkinson's disease were implanted with the Activa PC+S system (Medtronic Inc.). The device was attached to a quadripolar lead placed in the subdural space over motor cortex, for electrocorticography potential recordings, and to a quadripolar lead in the subthalamic nucleus (STN), for both therapeutic stimulation and recording of local field potentials. Recordings from the brain of each patient were performed at multiple time points over a 1-year period. RESULTS There were no serious surgical complications or interruptions in deep brain stimulation therapy. Signals in both the cortex and the STN were relatively stable over time, despite a gradual increase in electrode impedance. Canonical movement-related changes in specific frequency bands in the motor cortex were identified in most but not all recordings. CONCLUSIONS The acquisition of chronic multisite field potentials in humans is feasible. The device performance characteristics described here may inform the design of the next generation of totally implantable neural interfaces. This research tool provides a platform for translating discoveries in brain network dynamics to improved neurostimulation

Brain-computer interface training combined with transcranial direct current stimulation in patients with chronic severe hemiparesis: Proof of concept study.

Science.gov (United States)

Kasashima-Shindo, Yuko; Fujiwara, Toshiyuki; Ushiba, Junichi; Matsushika, Yayoi; Kamatani, Daiki; Oto, Misa; Ono, Takashi; Nishimoto, Atsuko; Shindo, Keiichiro; Kawakami, Michiyuki; Tsuji, Tetsuya; Liu, Meigen

2015-04-01

Brain-computer interface technology has been applied to stroke patients to improve their motor function. Event-related desynchronization during motor imagery, which is used as a brain-computer interface trigger, is sometimes difficult to detect in stroke patients. Anodal transcranial direct current stimulation (tDCS) is known to increase event-related desynchronization. This study investigated the adjunctive effect of anodal tDCS for brain-computer interface training in patients with severe hemiparesis. Eighteen patients with chronic stroke. A non-randomized controlled study. Subjects were divided between a brain-computer interface group and a tDCS- brain-computer interface group and participated in a 10-day brain-computer interface training. Event-related desynchronization was detected in the affected hemisphere during motor imagery of the affected fingers. The tDCS-brain-computer interface group received anodal tDCS before brain-computer interface training. Event-related desynchronization was evaluated before and after the intervention. The Fugl-Meyer Assessment upper extremity motor score (FM-U) was assessed before, immediately after, and 3 months after, the intervention. Event-related desynchronization was significantly increased in the tDCS- brain-computer interface group. The FM-U was significantly increased in both groups. The FM-U improvement was maintained at 3 months in the tDCS-brain-computer interface group. Anodal tDCS can be a conditioning tool for brain-computer interface training in patients with severe hemiparetic stroke.

Stretchable human-machine interface based on skin-conformal sEMG electrodes with self-similar geometry

Science.gov (United States)

Dong, Wentao; Zhu, Chen; Hu, Wei; Xiao, Lin; Huang, Yong'an

2018-01-01

Current stretchable surface electrodes have attracted increasing attention owing to their potential applications in biological signal monitoring, wearable human-machine interfaces (HMIs) and the Internet of Things. The paper proposed a stretchable HMI based on a surface electromyography (sEMG) electrode with a self-similar serpentine configuration. The sEMG electrode was transfer-printed onto the skin surface conformally to monitor biological signals, followed by signal classification and controlling of a mobile robot. Such electrodes can bear rather large deformation (such as >30%) under an appropriate areal coverage. The sEMG electrodes have been used to record electrophysiological signals from different parts of the body with sharp curvature, such as the index finger, back of the neck and face, and they exhibit great potential for HMI in the fields of robotics and healthcare. The electrodes placed onto the two wrists would generate two different signals with the fist clenched and loosened. It is classified to four kinds of signals with a combination of the gestures from the two wrists, that is, four control modes. Experiments demonstrated that the electrodes were successfully used as an HMI to control the motion of a mobile robot remotely. Project supported by the National Natural Science Foundation of China (Nos. 51635007, 91323303).

Handcrafted Electrocorticography Electrodes for a Rodent Behavioral Model

Directory of Open Access Journals (Sweden)

Nishat Tasnim

2016-08-01

Full Text Available Electrocorticography (ECoG is a minimally invasive neural recording method that has been extensively used for neuroscience applications. It has proven to have the potential to ease the establishment of proper links for neural interfaces that can offer disabled patients an alternative solution for their lost sensory and motor functions through the use of brain-computer interface (BCI technology. Although many neural recording methods exist, ECoG provides a combination of stability, high spatial and temporal resolution with chronic and mobile capabilities that could make BCI systems accessible for daily applications. However, many ECoG electrodes require MEMS fabricating techniques which are accompanied by various expenses that are obstacles for research projects. For this reason, this paper presents an animal study using a low cost and simple handcrafted ECoG electrode that is made of commercially accessible materials. The study is performed on a Lewis rat implanted with a handcrafted 32-channel non-penetrative ECoG electrode covering an area of 3 × 3 mm2 on the cortical surface. The ECoG electrodes were placed on the motor and somatosensory cortex to record the signal patterns while the animal was active on a treadmill. Using a Tucker-Davis Technologies acquisition system and the software Synapse to monitor and analyze the electrophysiological signals, the electrodes obtained signals within the amplitude range of 200 µV for local field potentials with reliable spatiotemporal profiles. It was also confirmed that the handcrafted ECoG electrode has the stability and chronic features found in other commercial electrodes.

Real-time brain computer interface using imaginary movements

DEFF Research Database (Denmark)

El-Madani, Ahmad; Sørensen, Helge Bjarup Dissing; Kjær, Troels W.

2015-01-01

Background: Brain Computer Interface (BCI) is the method of transforming mental thoughts and imagination into actions. A real-time BCI system can improve the quality of life of patients with severe neuromuscular disorders by enabling them to communicate with the outside world. In this paper...

Tangible User Interface and Mu Rhythm Suppression: The Effect of User Interface on the Brain Activity in Its Operator and Observer

Directory of Open Access Journals (Sweden)

Kazuo Isoda

2017-03-01

Full Text Available The intuitiveness of tangible user interface (TUI is not only for its operator. It is quite possible that this type of user interface (UI can also have an effect on the experience and learning of observers who are just watching the operator using it. To understand the possible effect of TUI, the present study focused on the mu rhythm suppression in the sensorimotor area reflecting execution and observation of action, and investigated the brain activity both in its operator and observer. In the observer experiment, the effect of TUI on its observers was demonstrated through the brain activity. Although the effect of the grasping action itself was uncertain, the unpredictability of the result of the action seemed to have some effect on the mirror neuron system (MNS-related brain activity. In the operator experiment, in spite of the same grasping action, the brain activity was activated in the sensorimotor area when UI functions were included (TUI. Such activation of the brain activity was not found with a graphical user interface (GUI that has UI functions without grasping action. These results suggest that the MNS-related brain activity is involved in the effect of TUI, indicating the possibility of UI evaluation based on brain activity.

Efficacy of brain-computer interface-driven neuromuscular electrical stimulation for chronic paresis after stroke.

Science.gov (United States)

Mukaino, Masahiko; Ono, Takashi; Shindo, Keiichiro; Fujiwara, Toshiyuki; Ota, Tetsuo; Kimura, Akio; Liu, Meigen; Ushiba, Junichi

2014-04-01

Brain computer interface technology is of great interest to researchers as a potential therapeutic measure for people with severe neurological disorders. The aim of this study was to examine the efficacy of brain computer interface, by comparing conventional neuromuscular electrical stimulation and brain computer interface-driven neuromuscular electrical stimulation, using an A-B-A-B withdrawal single-subject design. A 38-year-old male with severe hemiplegia due to a putaminal haemorrhage participated in this study. The design involved 2 epochs. In epoch A, the patient attempted to open his fingers during the application of neuromuscular electrical stimulation, irrespective of his actual brain activity. In epoch B, neuromuscular electrical stimulation was applied only when a significant motor-related cortical potential was observed in the electroencephalogram. The subject initially showed diffuse functional magnetic resonance imaging activation and small electro-encephalogram responses while attempting finger movement. Epoch A was associated with few neurological or clinical signs of improvement. Epoch B, with a brain computer interface, was associated with marked lateralization of electroencephalogram (EEG) and blood oxygenation level dependent responses. Voluntary electromyogram (EMG) activity, with significant EEG-EMG coherence, was also prompted. Clinical improvement in upper-extremity function and muscle tone was observed. These results indicate that self-directed training with a brain computer interface may induce activity- dependent cortical plasticity and promote functional recovery. This preliminary clinical investigation encourages further research using a controlled design.

Light Stimulation Properties to Influence Brain Activity: A Brain-CoMputer Interface application

NARCIS (Netherlands)

Bieger, J.; Garcia Molina, G.

2010-01-01

Brain-Computer Interfaces (BCIs) enable people to control appliances without involving the normal output pathways of peripheral nervesand muscles. A particularly promising type of BCI is based on the Steady-State Visual Evoked Potential (SSVEP). Users can selectcommands by focusing their attention

Neuroengineering tools/applications for bidirectional interfaces, brain computer interfaces, and neuroprosthetic implants - a review of recent progress

Directory of Open Access Journals (Sweden)

Ryan M Rothschild

2010-10-01

Full Text Available The main focus of this review is to provide a holistic amalgamated overview of the most recent human in vivo techniques for implementing brain-computer interfaces (BCIs, bidirectional interfaces and neuroprosthetics. Neuroengineering is providing new methods for tackling current difficulties; however neuroprosthetics have been studied for decades. Recent progresses are permitting the design of better systems with higher accuracies, repeatability and system robustness. Bidirectional interfaces integrate recording and the relaying of information from and to the brain for the development of BCIs. The concepts of non-invasive and invasive recording of brain activity are introduced. This includes classical and innovative techniques like electroencephalography (EEG and near-infrared spectroscopy (NIRS. Then the problem of gliosis and solutions for (semi- permanent implant biocompatibility such as innovative implant coatings, materials and shapes are discussed. Implant power and the transmission of their data through implanted pulse generators (IPGs and wireless telemetry are taken into account. How sensation can be relayed back to the brain to increase integration of the neuroengineered systems with the body by methods such as micro-stimulation and transcranial magnetic stimulation (TMS are then addressed. The neuroprosthetic section discusses some of the various types and how they operate. Visual prosthetics are discussed and the three types, dependant on implant location, are examined. Auditory prosthetics, being cochlear or cortical, are then addressed. Replacement hand and limb prosthetics are then considered. These are followed by sections concentrating on the control of wheelchairs, computers and robotics directly from brain activity as recorded by non-invasive and invasive techniques.

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.

Depth-resolved detection and process dependence of traps at ultrathin plasma-oxidized and deposited SiO2/Si interfaces

International Nuclear Information System (INIS)

Brillson, L. J.; Young, A. P.; White, B. D.; Schaefer, J.; Niimi, H.; Lee, Y. M.; Lucovsky, G.

2000-01-01

Low-energy electron-excited nanoluminescence spectroscopy reveals depth-resolved optical emission associated with traps near the interface between ultrathin SiO 2 deposited by plasma-enhanced chemical vapor deposition on plasma-oxidized crystalline Si. These near-interface states exhibit a strong dependence on local chemical bonding changes introduced by thermal/gas processing, layer-specific nitridation, or depth-dependent radiation exposure. The depth-dependent results provide a means to test chemical and structural bond models used to develop advanced dielectric-semiconductor junctions. (c) 2000 American Vacuum Society

The Future of Brain-Computer Interfacing (keynote paper)

NARCIS (Netherlands)

Nijholt, Antinus

In this paper we survey some early applications and research on brain-computer interfacing. We emphasize and revalue the role the views on artistic and playful applications have played. In previous years various road maps for BCI research appeared. The interest in medical applications has guided BCI

Brain-computer interfacing under distraction: an evaluation study

DEFF Research Database (Denmark)

Brandl, Stephanie; Frølich, Laura; Höhne, Johannes

2016-01-01

Objective. While motor-imagery based brain-computer interfaces (BCIs) have been studied over many years by now, most of these studies have taken place in controlled lab settings. Bringing BCI technology into everyday life is still one of the main challenges in this field of research. Approach...

Local impedance measurement of an electrode/single-pentacene-grain interface by frequency-modulation scanning impedance microscopy

Energy Technology Data Exchange (ETDEWEB)

Kimura, Tomoharu; Yamada, Hirofumi, E-mail: h-yamada@kuee.kyoto-u.ac.jp [Department of Electronic Science and Engineering, Kyoto University, Kyoto 615-8510 (Japan); Kobayashi, Kei [Department of Electronic Science and Engineering, Kyoto University, Kyoto 615-8510 (Japan); The Hakubi Center for Advanced Research, Kyoto University, Kyoto 615-8520 (Japan)

2015-08-07

The device performances of organic thin film transistors are often limited by the metal–organic interface because of the disordered molecular layers at the interface and the energy barriers against the carrier injection. It is important to study the local impedance at the interface without being affected by the interface morphology. We combined frequency modulation atomic force microscopy with scanning impedance microscopy (SIM) to sensitively measure the ac responses of the interface to an ac voltage applied across the interface and the dc potential drop at the interface. By using the frequency-modulation SIM (FM-SIM) technique, we characterized the interface impedance of a Pt electrode and a single pentacene grain as a parallel circuit of a contact resistance and a capacitance. We found that the reduction of the contact resistance was caused by the reduction of the energy level mismatch at the interface by the FM-SIM measurements, demonstrating the usefulness of the FM-SIM technique for investigation of the local interface impedance without being affected by its morphology.

Brain-computer interface for alertness estimation and improving

Science.gov (United States)

Hramov, Alexander; Maksimenko, Vladimir; Hramova, Marina

2018-02-01

Using wavelet analysis of the signals of electrical brain activity (EEG), we study the processes of neural activity, associated with perception of visual stimuli. We demonstrate that the brain can process visual stimuli in two scenarios: (i) perception is characterized by destruction of the alpha-waves and increase in the high-frequency (beta) activity, (ii) the beta-rhythm is not well pronounced, while the alpha-wave energy remains unchanged. The special experiments show that the motivation factor initiates the first scenario, explained by the increasing alertness. Based on the obtained results we build the brain-computer interface and demonstrate how the degree of the alertness can be estimated and controlled in real experiment.

Wireless brain-machine interface using EEG and EOG: brain wave classification and robot control

Science.gov (United States)

Oh, Sechang; Kumar, Prashanth S.; Kwon, Hyeokjun; Varadan, Vijay K.

2012-04-01

A brain-machine interface (BMI) links a user's brain activity directly to an external device. It enables a person to control devices using only thought. Hence, it has gained significant interest in the design of assistive devices and systems for people with disabilities. In addition, BMI has also been proposed to replace humans with robots in the performance of dangerous tasks like explosives handling/diffusing, hazardous materials handling, fire fighting etc. There are mainly two types of BMI based on the measurement method of brain activity; invasive and non-invasive. Invasive BMI can provide pristine signals but it is expensive and surgery may lead to undesirable side effects. Recent advances in non-invasive BMI have opened the possibility of generating robust control signals from noisy brain activity signals like EEG and EOG. A practical implementation of a non-invasive BMI such as robot control requires: acquisition of brain signals with a robust wearable unit, noise filtering and signal processing, identification and extraction of relevant brain wave features and finally, an algorithm to determine control signals based on the wave features. In this work, we developed a wireless brain-machine interface with a small platform and established a BMI that can be used to control the movement of a robot by using the extracted features of the EEG and EOG signals. The system records and classifies EEG as alpha, beta, delta, and theta waves. The classified brain waves are then used to define the level of attention. The acceleration and deceleration or stopping of the robot is controlled based on the attention level of the wearer. In addition, the left and right movements of eye ball control the direction of the robot.

Robotic devices and brain-machine interfaces for hand rehabilitation post-stroke.

Science.gov (United States)

McConnell, Alistair C; Moioli, Renan C; Brasil, Fabricio L; Vallejo, Marta; Corne, David W; Vargas, Patricia A; Stokes, Adam A

2017-06-28

To review the state of the art of robotic-aided hand physiotherapy for post-stroke rehabilitation, including the use of brain-machine interfaces. Each patient has a unique clinical history and, in response to personalized treatment needs, research into individualized and at-home treatment options has expanded rapidly in recent years. This has resulted in the development of many devices and design strategies for use in stroke rehabilitation. The development progression of robotic-aided hand physiotherapy devices and brain-machine interface systems is outlined, focussing on those with mechanisms and control strategies designed to improve recovery outcomes of the hand post-stroke. A total of 110 commercial and non-commercial hand and wrist devices, spanning the 2 major core designs: end-effector and exoskeleton are reviewed. The growing body of evidence on the efficacy and relevance of incorporating brain-machine interfaces in stroke rehabilitation is summarized. The challenges involved in integrating robotic rehabilitation into the healthcare system are discussed. This review provides novel insights into the use of robotics in physiotherapy practice, and may help system designers to develop new devices.

From assistance towards restoration with epidural brain-computer interfacing.

Science.gov (United States)

Gharabaghi, Alireza; Naros, Georgios; Walter, Armin; Grimm, Florian; Schuermeyer, Marc; Roth, Alexander; Bogdan, Martin; Rosenstiel, Wolfgang; Birbaumer, Niels

2014-01-01

Today's implanted brain-computer interfaces make direct contact with the brain or even penetrate the tissue, bearing additional risks with regard to safety and stability. What is more, these approaches aim to control prosthetic devices as assistive tools and do not yet strive to become rehabilitative tools for restoring lost motor function. We introduced a less invasive, implantable interface by applying epidural electrocorticography in a chronic stroke survivor with a persistent motor deficit. He was trained to modulate his natural motor-related oscillatory brain activity by receiving online feedback. Epidural recordings of field potentials in the beta-frequency band projecting onto the anatomical hand knob proved most successful in discriminating between the attempt to move the paralyzed hand and to rest. These spectral features allowed for fast and reliable control of the feedback device in an online closed-loop paradigm. Only seven training sessions were required to significantly improve maximum wrist extension. For patients suffering from severe motor deficits, epidural implants may decode and train the brain activity generated during attempts to move with high spatial resolution, thus facilitating specific and high-intensity practice even in the absence of motor control. This would thus transform them from pure assistive devices to restorative tools in the context of reinforcement learning and neurorehabilitation.

Localization, correlation, and visualization of electroencephalographic surface electrodes and brain anatomy in epilepsy studies

Science.gov (United States)

Brinkmann, Benjamin H.; O'Brien, Terence J.; Robb, Richard A.; Sharbrough, Frank W.

1997-05-01

Advances in neuroimaging have enhanced the clinician's ability to localize the epileptogenic zone in focal epilepsy, but 20-50 percent of these cases still remain unlocalized. Many sophisticated modalities have been used to study epilepsy, but scalp electrode recorded electroencephalography is particularly useful due to its noninvasive nature and excellent temporal resolution. This study is aimed at specific locations of scalp electrode EEG information for correlation with anatomical structures in the brain. 3D position localizing devices commonly used in virtual reality systems are used to digitize the coordinates of scalp electrodes in a standard clinical configuration. The electrode coordinates are registered with a high- resolution MRI dataset using a robust surface matching algorithm. Volume rendering can then be used to visualize the electrodes and electrode potentials interpolated over the scalp. The accuracy of the coordinate registration is assessed quantitatively with a realistic head phantom.

Neurobionics and the brain-computer interface: current applications and future horizons.

Science.gov (United States)

Rosenfeld, Jeffrey V; Wong, Yan Tat

2017-05-01

The brain-computer interface (BCI) is an exciting advance in neuroscience and engineering. In a motor BCI, electrical recordings from the motor cortex of paralysed humans are decoded by a computer and used to drive robotic arms or to restore movement in a paralysed hand by stimulating the muscles in the forearm. Simultaneously integrating a BCI with the sensory cortex will further enhance dexterity and fine control. BCIs are also being developed to: provide ambulation for paraplegic patients through controlling robotic exoskeletons; restore vision in people with acquired blindness; detect and control epileptic seizures; and improve control of movement disorders and memory enhancement. High-fidelity connectivity with small groups of neurons requires microelectrode placement in the cerebral cortex. Electrodes placed on the cortical surface are less invasive but produce inferior fidelity. Scalp surface recording using electroencephalography is much less precise. BCI technology is still in an early phase of development and awaits further technical improvements and larger multicentre clinical trials before wider clinical application and impact on the care of people with disabilities. There are also many ethical challenges to explore as this technology evolves.

Motivation modulates the P300 amplitude during brain-computer interface use.

Science.gov (United States)

Kleih, S C; Nijboer, F; Halder, S; Kübler, A

2010-07-01

This study examined the effect of motivation as a possible psychological influencing variable on P300 amplitude and performance in a brain-computer interface (BCI) controlled by event-related potentials (ERP). Participants were instructed to copy spell a sentence by attending to cells of a randomly flashing 7*7 matrix. Motivation was manipulated by monetary reward. In two experimental groups participants received 25 (N=11) or 50 (N=11) Euro cent for each correctly selected character; the control group (N=11) was not rewarded. BCI performance was defined as the overall percentage of correctly selected characters (correct response rate=CRR). Participants performed at an average of 99%. At electrode location Cz the P300 amplitude was positively correlated to self-rated motivation. The P300 amplitude of the most motivated participants was significantly higher than that of the least motivated participants. Highly motivated participants were able to communicate correctly faster with the ERP-BCI than less motivated participants. Motivation modulates the P300 amplitude in an ERP-BCI. Motivation may contribute to variance in BCI performance and should be monitored in BCI settings. Copyright 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Guest editorial: Brain/neuronal computer games interfaces and interaction

OpenAIRE

Coyle, D.; Principe, J.; Lotte, F.; Nijholt, Antinus

2013-01-01

Nowadays brainwave or electroencephalogram (EEG) controlled games controllers are adding new options to satisfy the continual demand for new ways to interact with games, following trends such as the Nintendo® Wii, Microsoft® Kinect and Playstation® Move which are based on accelerometers and motion capture. EEG-based brain-computer games interaction are controlled through brain-computer interface (BCI) technology which requires sophisticated signal processing to produce a low communication ban...

As We May Think and Be: Brain-computer interfaces to expand the substrate of mind

Directory of Open Access Journals (Sweden)

Mijail Demian Serruya

2015-04-01

Full Text Available Over a half-century ago, the scientist Vannevar Bush explored the conundrum of how to tap the exponentially rising sea of human knowledge for the betterment of humanity. In his description of a hypothetical electronic library he dubbed the memex, he anticipated internet search and online encyclopedias (Bush, 1945. By blurring the boundary between brain and computer, brain-computer interfaces (BCI could lead to more efficient use of electronic resources (Schalk, 2008. We could expand the substrate of the mind itself rather than merely interfacing it to external computers. Components of brain-computer interfaces could be re-arranged to create brain-brain interfaces, or tightly interconnected links between a person’s brain and ectopic neural modules. Such modules – whether sitting in a bubbling Petri dish, rendered in reciprocally linked integrated circuits, or implanted in our belly – would mark the first step on to a path of breaking out of the limitations imposed by our phylogenetic past Novel BCI architectures could generate novel abilities to navigate and access information that might speed translational science efforts and push the boundaries of human knowledge in an unprecedented manner.

Brain-Computer Interface Spellers: A Review.

Science.gov (United States)

Rezeika, Aya; Benda, Mihaly; Stawicki, Piotr; Gembler, Felix; Saboor, Abdul; Volosyak, Ivan

2018-03-30

A Brain-Computer Interface (BCI) provides a novel non-muscular communication method via brain signals. A BCI-speller can be considered as one of the first published BCI applications and has opened the gate for many advances in the field. Although many BCI-spellers have been developed during the last few decades, to our knowledge, no reviews have described the different spellers proposed and studied in this vital field. The presented speller systems are categorized according to major BCI paradigms: P300, steady-state visual evoked potential (SSVEP), and motor imagery (MI). Different BCI paradigms require specific electroencephalogram (EEG) signal features and lead to the development of appropriate Graphical User Interfaces (GUIs). The purpose of this review is to consolidate the most successful BCI-spellers published since 2010, while mentioning some other older systems which were built explicitly for spelling purposes. We aim to assist researchers and concerned individuals in the field by illustrating the highlights of different spellers and presenting them in one review. It is almost impossible to carry out an objective comparison between different spellers, as each has its variables, parameters, and conditions. However, the gathered information and the provided taxonomy about different BCI-spellers can be helpful, as it could identify suitable systems for first-hand users, as well as opportunities of development and learning from previous studies for BCI researchers.

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.

Evaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Driving.

Science.gov (United States)

Zander, Thorsten O; Andreessen, Lena M; Berg, Angela; Bleuel, Maurice; Pawlitzki, Juliane; Zawallich, Lars; Krol, Laurens R; Gramann, Klaus

2017-01-01

We tested the applicability and signal quality of a 16 channel dry electroencephalography (EEG) system in a laboratory environment and in a car under controlled, realistic conditions. The aim of our investigation was an estimation how well a passive Brain-Computer Interface (pBCI) can work in an autonomous driving scenario. The evaluation considered speed and accuracy of self-applicability by an untrained person, quality of recorded EEG data, shifts of electrode positions on the head after driving-related movements, usability, and complexity of the system as such and wearing comfort over time. An experiment was conducted inside and outside of a stationary vehicle with running engine, air-conditioning, and muted radio. Signal quality was sufficient for standard EEG analysis in the time and frequency domain as well as for the use in pBCIs. While the influence of vehicle-induced interferences to data quality was insignificant, driving-related movements led to strong shifts in electrode positions. In general, the EEG system used allowed for a fast self-applicability of cap and electrodes. The assessed usability of the system was still acceptable while the wearing comfort decreased strongly over time due to friction and pressure to the head. From these results we conclude that the evaluated system should provide the essential requirements for an application in an autonomous driving context. Nevertheless, further refinement is suggested to reduce shifts of the system due to body movements and increase the headset's usability and wearing comfort.

Personality Trait and Facial Expression Filter-Based Brain-Computer Interface

Directory of Open Access Journals (Sweden)

Seongah Chin

2013-02-01

Full Text Available In this paper, we present technical approaches that bridge the gap in the research related to the use of brain-computer interfaces for entertainment and facial expressions. Such facial expressions that reflect an individual's personal traits can be used to better realize artificial facial expressions in a gaming environment based on a brain-computer interface. First, an emotion extraction filter is introduced in order to classify emotions on the basis of the users' brain signals in real time. Next, a personality trait filter is defined to classify extrovert and introvert types, which manifest as five traits: very extrovert, extrovert, medium, introvert and very introvert. In addition, facial expressions derived from expression rates are obtained by an extrovert-introvert fuzzy model through its defuzzification process. Finally, we confirm this validation via an analysis of the variance of the personality trait filter, a k-fold cross validation of the emotion extraction filter, an accuracy analysis, a user study of facial synthesis and a test case game.

Clinical thermometry, using the 27 MHz multi-electrode current-source interstitial hyperthermia system in brain tumours

International Nuclear Information System (INIS)

Kaatee, Robert S.J.P.; Nowak, Peter C.J.M.; Zee, Jacoba van der; Bree, Jacob de; Kanis, Bart P.; Crezee, Hans; Levendag, Peter C.; Visser, Andries G.

2001-01-01

Background and purpose: In interstitial hyperthermia, temperature measurements are mainly performed inside heating applicators, and therefore, give the maximum temperatures of a rather heterogeneous temperature distribution. The problem of how to estimate lesion temperatures using the multi-electrode current-source interstitial hyperthermia (MECS-IHT) system in the brain was studied. Materials and methods: Temperatures were measured within the electrodes and in an extra catheter at the edge of a 4x4x4.5 cm 3 glioblastoma multiforme resection cavity. From the temperature decays during a power-off period, information was obtained about local maximum and minimum tissue temperatures. The significance of these data was examined through model calculations. Results: Maximum tissue temperatures could be estimated roughly by switching off all electrodes for about 5 s. Model calculations showed that the minimum tissue temperatures near a certain afterloading catheter correspond well with the temperature of the applicator inside, about 1 min after this applicator was switched off. Conclusions: Although the electrode temperatures read during heating are not suitable to assess the temperature distribution, it is feasible to heat the brain adequately using the MECS-IHT system with extra sensors outside the electrodes and/or application of decay methods

Vibrotactile Feedback for Brain-Computer Interface Operation

OpenAIRE

Cincotti, Febo; Kauhanen, Laura; Aloise, Fabio; Palomäki, Tapio; Caporusso, Nicholas; Jylänki, Pasi; Mattia, Donatella; Babiloni, Fabio; Vanacker, Gerolf; Nuttin, Marnix; Marciani, Maria Grazia; Millán, José del R.

2007-01-01

To be correctly mastered, brain-computer interfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim was to explore the benefits of vibrotactile feedback during users' training and control of EEG-based BCI applications. A protocol for delivering vibrotactile feedback, including specific hardware and software arrangements, was specified. In three studies with 33 subjects (i...

An array of highly flexible electrodes with a tailored configuration locked by gelatin during implantation – initial evaluation in cortex cerebri of awake rats

Directory of Open Access Journals (Sweden)

Johan eAgorelius

2015-09-01

Full Text Available A major challenge in the field of neural interfaces is to overcome the problem of poor stability of neuronal recordings, which impedes long-term studies of individual neurons in the brain. Conceivably, unstable recordings reflect relative movements between electrode and tissue. To address this challenge, we have developed a new ultra-flexible electrode array and evaluated its performance in awake non-restrained animals.MethodsAn array of eight separated gold leads (4 x10 μm, individually flexible in 3D, were cut from a gold sheet using laser milling and insulated with Parylene C. To provide structural support during implantation into rat cortex, the electrode array was embedded in a hard gelatin based material, which dissolves after implantation. Recordings were made during 3 weeks. At termination, the animals were perfused with fixative and frozen to prevent dislocation of the implanted electrodes. A thick slice of brain tissue, with the electrode array still in situ, was made transparent using methyl salicylate to evaluate the conformation of the implanted electrode array.ResultsMedian noise levels and signal/noise remained relatively stable during the 3 week observation period; 4.3 μV to 5.9 μV and 2.8 to 4.2, respectively. The spike amplitudes were often quite stable within recording sessions and for 15% of recordings where single-units were identified, the highest-SNR unit had an amplitude higher than 150 V. In addition, high correlations (>0.96 between unit waveforms recorded at different time points were obtained for 58% of the electrode sites. The structure of the electrode array was well preserved 3 weeks after implantation.Conclusions A new implantable multichannel neural interface, comprising electrodes individually flexible in 3D that retain its architecture and functionality after implantation has been developed. Since the new neural interface design is adaptable, it offers a versatile tool to explore the function of various

Brain computer interface for operating a robot

Science.gov (United States)

Nisar, Humaira; Balasubramaniam, Hari Chand; Malik, Aamir Saeed

2013-10-01

A Brain-Computer Interface (BCI) is a hardware/software based system that translates the Electroencephalogram (EEG) signals produced by the brain activity to control computers and other external devices. In this paper, we will present a non-invasive BCI system that reads the EEG signals from a trained brain activity using a neuro-signal acquisition headset and translates it into computer readable form; to control the motion of a robot. The robot performs the actions that are instructed to it in real time. We have used the cognitive states like Push, Pull to control the motion of the robot. The sensitivity and specificity of the system is above 90 percent. Subjective results show a mixed trend of the difficulty level of the training activities. The quantitative EEG data analysis complements the subjective results. This technology may become very useful for the rehabilitation of disabled and elderly people.

Shaping of neuronal activity through a Brain Computer Interface

OpenAIRE

Valero-Aguayo, Luis; Silva-Sauer, Leandro; Velasco-Alvarez, Ricardo; Ron-Angevin, Ricardo

2014-01-01

Neuronal responses are human actions which can be measured by an EEG, and which imply changes in waves when neurons are synchronized. This activity could be changed by principles of behaviour analysis. This research tests the efficacy of the behaviour shaping procedure to progressively change neuronal activity, so that those brain responses are adapted according to the differential reinforcement of visual feedback. The Brain Computer Interface (BCI) enables us to record the EEG in real ti...

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.

Brain-computer interface analysis of a dynamic visuo-motor task.

Science.gov (United States)

Logar, Vito; Belič, Aleš

2011-01-01

The area of brain-computer interfaces (BCIs) represents one of the more interesting fields in neurophysiological research, since it investigates the development of the machines that perform different transformations of the brain's "thoughts" to certain pre-defined actions. Experimental studies have reported some successful implementations of BCIs; however, much of the field still remains unexplored. According to some recent reports the phase coding of informational content is an important mechanism in the brain's function and cognition, and has the potential to explain various mechanisms of the brain's data transfer, but it has yet to be scrutinized in the context of brain-computer interface. Therefore, if the mechanism of phase coding is plausible, one should be able to extract the phase-coded content, carried by brain signals, using appropriate signal-processing methods. In our previous studies we have shown that by using a phase-demodulation-based signal-processing approach it is possible to decode some relevant information on the current motor action in the brain from electroencephalographic (EEG) data. In this paper the authors would like to present a continuation of their previous work on the brain-information-decoding analysis of visuo-motor (VM) tasks. The present study shows that EEG data measured during more complex, dynamic visuo-motor (dVM) tasks carries enough information about the currently performed motor action to be successfully extracted by using the appropriate signal-processing and identification methods. The aim of this paper is therefore to present a mathematical model, which by means of the EEG measurements as its inputs predicts the course of the wrist movements as applied by each subject during the task in simulated or real time (BCI analysis). However, several modifications to the existing methodology are needed to achieve optimal decoding results and a real-time, data-processing ability. The information extracted from the EEG could

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.

A user-friendly SSVEP-based brain-computer interface using a time-domain classifier.

Science.gov (United States)

Luo, An; Sullivan, Thomas J

2010-04-01

We introduce a user-friendly steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) system. Single-channel EEG is recorded using a low-noise dry electrode. Compared to traditional gel-based multi-sensor EEG systems, a dry sensor proves to be more convenient, comfortable and cost effective. A hardware system was built that displays four LED light panels flashing at different frequencies and synchronizes with EEG acquisition. The visual stimuli have been carefully designed such that potential risk to photosensitive people is minimized. We describe a novel stimulus-locked inter-trace correlation (SLIC) method for SSVEP classification using EEG time-locked to stimulus onsets. We studied how the performance of the algorithm is affected by different selection of parameters. Using the SLIC method, the average light detection rate is 75.8% with very low error rates (an 8.4% false positive rate and a 1.3% misclassification rate). Compared to a traditional frequency-domain-based method, the SLIC method is more robust (resulting in less annoyance to the users) and is also suitable for irregular stimulus patterns.

Brain Machine Interfaces : technology status, applications and the way to the future

NARCIS (Netherlands)

Erp, J.B.F. van; Duistermaat, M.; Philippens, I.H.C.H.M.; Veen, H.A.H.C. van; Werkhoven, P.J.

2006-01-01

Brain Machine Interfaces (BMIs) enable direct communication between the brain or nervous system and a machine without involving the sensory-motor system. BMIs are an embryonic technology and remarkable accomplishments have recently been reported. BMIs have a high potential and possibly an enormous

Reward-based hypertension control by a synthetic brain-dopamine interface.

Science.gov (United States)

Rössger, Katrin; Charpin-El Hamri, Ghislaine; Fussenegger, Martin

2013-11-05

Synthetic biology has significantly advanced the design of synthetic trigger-controlled devices that can reprogram mammalian cells to interface with complex metabolic activities. In the brain, the neurotransmitter dopamine coordinates communication with target neurons via a set of dopamine receptors that control behavior associated with reward-driven learning. This dopamine transmission has recently been suggested to increase central sympathetic outflow, resulting in plasma dopamine levels that correlate with corresponding brain activities. By functionally rewiring the human dopamine receptor D1 (DRD1) via the second messenger cyclic adenosine monophosphate (cAMP) to synthetic promoters containing cAMP response element-binding protein 1(CREB1)-specific cAMP-responsive operator modules, we have designed a synthetic dopamine-sensitive transcription controller that reversibly fine-tunes specific target gene expression at physiologically relevant brain-derived plasma dopamine levels. Following implantation of circuit-transgenic human cell lines insulated by semipermeable immunoprotective microcontainers into mice, the designer device interfaced with dopamine-specific brain activities and produced a systemic expression response when the animal's reward system was stimulated by food, sexual arousal, or addictive drugs. Reward-triggered brain activities were able to remotely program peripheral therapeutic implants to produce sufficient amounts of the atrial natriuretic peptide, which reduced the blood pressure of hypertensive mice to the normal physiologic range. Seamless control of therapeutic transgenes by subconscious behavior may provide opportunities for treatment strategies of the future.

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

Science.gov (United States)

Eugster, Manuel J. A.; Ruotsalo, Tuukka; Spapé, Michiel M.; Barral, Oswald; Ravaja, Niklas; Jacucci, Giulio; Kaski, Samuel

2016-01-01

Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user’s interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recommending information by relevance inferred directly from brain signals. In experiments, participants were asked to read Wikipedia documents about a selection of topics while their EEG was recorded. Based on the prediction of word relevance, the individual’s search intent was modeled and successfully used for retrieving new relevant documents from the whole English Wikipedia corpus. The results show that the users’ interests toward digital content can be modeled from the brain signals evoked by reading. The introduced brain-relevance paradigm enables the recommendation of information without any explicit user interaction and may be applied across diverse information-intensive applications. PMID:27929077

Soft, curved electrode systems capable of integration on the auricle as a persistent brain–computer interface

Science.gov (United States)

Norton, James J. S.; Lee, Dong Sup; Lee, Jung Woo; Lee, Woosik; Kwon, Ohjin; Won, Phillip; Jung, Sung-Young; Cheng, Huanyu; Jeong, Jae-Woong; Akce, Abdullah; Umunna, Stephen; Na, Ilyoun; Kwon, Yong Ho; Wang, Xiao-Qi; Liu, ZhuangJian; Paik, Ungyu; Huang, Yonggang; Bretl, Timothy; Yeo, Woon-Hong; Rogers, John A.

2015-01-01

Recent advances in electrodes for noninvasive recording of electroencephalograms expand opportunities collecting such data for diagnosis of neurological disorders and brain–computer interfaces. Existing technologies, however, cannot be used effectively in continuous, uninterrupted modes for more than a few days due to irritation and irreversible degradation in the electrical and mechanical properties of the skin interface. Here we introduce a soft, foldable collection of electrodes in open, fractal mesh geometries that can mount directly and chronically on the complex surface topology of the auricle and the mastoid, to provide high-fidelity and long-term capture of electroencephalograms in ways that avoid any significant thermal, electrical, or mechanical loading of the skin. Experimental and computational studies establish the fundamental aspects of the bending and stretching mechanics that enable this type of intimate integration on the highly irregular and textured surfaces of the auricle. Cell level tests and thermal imaging studies establish the biocompatibility and wearability of such systems, with examples of high-quality measurements over periods of 2 wk with devices that remain mounted throughout daily activities including vigorous exercise, swimming, sleeping, and bathing. Demonstrations include a text speller with a steady-state visually evoked potential-based brain–computer interface and elicitation of an event-related potential (P300 wave). PMID:25775550

Analysis of deep brain stimulation electrode characteristics for neural recording

Science.gov (United States)

Kent, Alexander R.; Grill, Warren M.

2014-08-01

Objective. Closed-loop deep brain stimulation (DBS) systems have the potential to optimize treatment of movement disorders by enabling automatic adjustment of stimulation parameters based on a feedback signal. Evoked compound action potentials (ECAPs) and local field potentials (LFPs) recorded from the DBS electrode may serve as suitable closed-loop control signals. The objective of this study was to understand better the factors that influence ECAP and LFP recording, including the physical presence of the electrode, the geometrical dimensions of the electrode, and changes in the composition of the peri-electrode space across recording conditions. Approach. Coupled volume conductor-neuron models were used to calculate single-unit activity as well as ECAP responses and LFP activity from a population of model thalamic neurons. Main results. Comparing ECAPs and LFPs measured with and without the presence of the highly conductive recording contacts, we found that the presence of these contacts had a negligible effect on the magnitude of single-unit recordings, ECAPs (7% RMS difference between waveforms), and LFPs (5% change in signal magnitude). Spatial averaging across the contact surface decreased the ECAP magnitude in a phase-dependent manner (74% RMS difference), resulting from a differential effect of the contact on the contribution from nearby or distant elements, and decreased the LFP magnitude (25% change). Reductions in the electrode diameter or recording contact length increased signal energy and increased spatial sensitivity of single neuron recordings. Moreover, smaller diameter electrodes (500 µm) were more selective for recording from local cells over passing axons, with the opposite true for larger diameters (1500 µm). Changes in electrode dimensions had phase-dependent effects on ECAP characteristics, and generally had small effects on the LFP magnitude. ECAP signal energy and LFP magnitude decreased with tighter contact spacing (100 µm), compared to

Social Interaction in a Cooperative Brain-computer Interface Game

NARCIS (Netherlands)

Obbink, Michel; Gürkök, Hayrettin; Plass - Oude Bos, D.; Hakvoort, Gido; Poel, Mannes; Nijholt, Antinus; Camurri, Antonio; Costa, Cristina

Does using a brain-computer interface (BCI) influence the social interaction between people when playing a cooperative game? By measuring the amount of speech, utterances, instrumental gestures and empathic gestures during a cooperative game where two participants had to reach a certain goal, and

Mental workload during brain-computer interface training.

Science.gov (United States)

Felton, Elizabeth A; Williams, Justin C; Vanderheiden, Gregg C; Radwin, Robert G

2012-01-01

It is not well understood how people perceive the difficulty of performing brain-computer interface (BCI) tasks, which specific aspects of mental workload contribute the most, and whether there is a difference in perceived workload between participants who are able-bodied and disabled. This study evaluated mental workload using the NASA Task Load Index (TLX), a multi-dimensional rating procedure with six subscales: Mental Demands, Physical Demands, Temporal Demands, Performance, Effort, and Frustration. Able-bodied and motor disabled participants completed the survey after performing EEG-based BCI Fitts' law target acquisition and phrase spelling tasks. The NASA-TLX scores were similar for able-bodied and disabled participants. For example, overall workload scores (range 0-100) for 1D horizontal tasks were 48.5 (SD = 17.7) and 46.6 (SD 10.3), respectively. The TLX can be used to inform the design of BCIs that will have greater usability by evaluating subjective workload between BCI tasks, participant groups, and control modalities. Mental workload of brain-computer interfaces (BCI) can be evaluated with the NASA Task Load Index (TLX). The TLX is an effective tool for comparing subjective workload between BCI tasks, participant groups (able-bodied and disabled), and control modalities. The data can inform the design of BCIs that will have greater usability.

Encoder-decoder optimization for brain-computer interfaces.

Science.gov (United States)

Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam

2015-06-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Encoder-decoder optimization for brain-computer interfaces.

Directory of Open Access Journals (Sweden)

Josh Merel

2015-06-01

Full Text Available Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model" and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Local Structure and Ionic Conduction at Interfaces of Electrode and Solid Electrolytes

OpenAIRE

Yamada, Hirotsohi; Oga, Yusuke; Saruwatari, Isamu; Moriguchi, Isamu

2012-01-01

All solid state batteries are attracting interests as next generation energy storage devices. However, little is known on interfaces between active materials and solid electrolytes, which may affect performance of the devices. In this study, interfacial phenomena between electrodes and solid electrolytes of all solid state batteries were investigated by using nano-composites of Li 2SiO 3-TiO 2, Li 2SiO 3-LiTiO 2, and Li 2SiO 3-FePO 4. Studies on ionic conductivity of these composites revealed...

EEG datasets for motor imagery brain-computer interface.

Science.gov (United States)

Cho, Hohyun; Ahn, Minkyu; Ahn, Sangtae; Kwon, Moonyoung; Jun, Sung Chan

2017-07-01

Most investigators of brain-computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)-based BCI is one of the standard concepts of BCI, in that the user can generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation. Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task-related states. We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information. Our EEG datasets included the information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task-related states. © The Authors 2017. Published by Oxford University Press.

Neuro-robotics from brain machine interfaces to rehabilitation robotics

CERN Document Server

Artemiadis

2014-01-01

Neuro-robotics is one of the most multidisciplinary fields of the last decades, fusing information and knowledge from neuroscience, engineering and computer science. This book focuses on the results from the strategic alliance between Neuroscience and Robotics that help the scientific community to better understand the brain as well as design robotic devices and algorithms for interfacing humans and robots. The first part of the book introduces the idea of neuro-robotics, by presenting state-of-the-art bio-inspired devices. The second part of the book focuses on human-machine interfaces for pe

Towards passive brain-computer interfaces: applying brain-computer interface technology to human-machine systems in general.

Science.gov (United States)

Zander, Thorsten O; Kothe, Christian

2011-04-01

Cognitive monitoring is an approach utilizing realtime brain signal decoding (RBSD) for gaining information on the ongoing cognitive user state. In recent decades this approach has brought valuable insight into the cognition of an interacting human. Automated RBSD can be used to set up a brain-computer interface (BCI) providing a novel input modality for technical systems solely based on brain activity. In BCIs the user usually sends voluntary and directed commands to control the connected computer system or to communicate through it. In this paper we propose an extension of this approach by fusing BCI technology with cognitive monitoring, providing valuable information about the users' intentions, situational interpretations and emotional states to the technical system. We call this approach passive BCI. In the following we give an overview of studies which utilize passive BCI, as well as other novel types of applications resulting from BCI technology. We especially focus on applications for healthy users, and the specific requirements and demands of this user group. Since the presented approach of combining cognitive monitoring with BCI technology is very similar to the concept of BCIs itself we propose a unifying categorization of BCI-based applications, including the novel approach of passive BCI.

Brain-computer interface using P300 and virtual reality: a gaming approach for treating ADHD.

Science.gov (United States)

Rohani, Darius Adam; Sorensen, Helge B D; Puthusserypady, Sadasivan

2014-01-01

This paper presents a novel brain-computer interface (BCI) system aiming at the rehabilitation of attention-deficit/hyperactive disorder in children. It uses the P300 potential in a series of feedback games to improve the subjects' attention. We applied a support vector machine (SVM) using temporal and template-based features to detect these P300 responses. In an experimental setup using five subjects, an average error below 30% was achieved. To make it more challenging the BCI system has been embedded inside an immersive 3D virtual reality (VR) classroom with simulated distractions, which was created by combining a low-cost infrared camera and an "off-axis perspective projection" algorithm. This system is intended for kids by operating with four electrodes, as well as a non-intrusive VR setting. With the promising results, and considering the simplicity of the scheme, we hope to encourage future studies to adapt the techniques presented in this study.

Brain-Computer Interface application: auditory serial interface to control a two-class motor-imagery-based wheelchair.

Science.gov (United States)

Ron-Angevin, Ricardo; Velasco-Álvarez, Francisco; Fernández-Rodríguez, Álvaro; Díaz-Estrella, Antonio; Blanca-Mena, María José; Vizcaíno-Martín, Francisco Javier

2017-05-30

Certain diseases affect brain areas that control the movements of the patients' body, thereby limiting their autonomy and communication capacity. Research in the field of Brain-Computer Interfaces aims to provide patients with an alternative communication channel not based on muscular activity, but on the processing of brain signals. Through these systems, subjects can control external devices such as spellers to communicate, robotic prostheses to restore limb movements, or domotic systems. The present work focus on the non-muscular control of a robotic wheelchair. A proposal to control a wheelchair through a Brain-Computer Interface based on the discrimination of only two mental tasks is presented in this study. The wheelchair displacement is performed with discrete movements. The control signals used are sensorimotor rhythms modulated through a right-hand motor imagery task or mental idle state. The peculiarity of the control system is that it is based on a serial auditory interface that provides the user with four navigation commands. The use of two mental tasks to select commands may facilitate control and reduce error rates compared to other endogenous control systems for wheelchairs. Seventeen subjects initially participated in the study; nine of them completed the three sessions of the proposed protocol. After the first calibration session, seven subjects were discarded due to a low control of their electroencephalographic signals; nine out of ten subjects controlled a virtual wheelchair during the second session; these same nine subjects achieved a medium accuracy level above 0.83 on the real wheelchair control session. The results suggest that more extensive training with the proposed control system can be an effective and safe option that will allow the displacement of a wheelchair in a controlled environment for potential users suffering from some types of motor neuron diseases.

An associative Brain-Computer-Interface for acute stroke patients

DEFF Research Database (Denmark)

Mrachacz-Kersting, Natalie; Stevenson, Andrew James Thomas; Aliakbaryhosseinabadi, Susan

2016-01-01

An efficient innovative Brain-Computer-Interface system that empowers chronic stroke patients to control an artificial activation of their lower limb muscle through task specific motor intent has been tested in the past. In the current study it was applied to acute stroke patients. The system...

Ownership and Agency of an Independent Supernumerary Hand Induced by an Imitation Brain-Computer Interface.

Science.gov (United States)

Bashford, Luke; Mehring, Carsten

2016-01-01

To study body ownership and control, illusions that elicit these feelings in non-body objects are widely used. Classically introduced with the Rubber Hand Illusion, these illusions have been replicated more recently in virtual reality and by using brain-computer interfaces. Traditionally these illusions investigate the replacement of a body part by an artificial counterpart, however as brain-computer interface research develops it offers us the possibility to explore the case where non-body objects are controlled in addition to movements of our own limbs. Therefore we propose a new illusion designed to test the feeling of ownership and control of an independent supernumerary hand. Subjects are under the impression they control a virtual reality hand via a brain-computer interface, but in reality there is no causal connection between brain activity and virtual hand movement but correct movements are observed with 80% probability. These imitation brain-computer interface trials are interspersed with movements in both the subjects' real hands, which are in view throughout the experiment. We show that subjects develop strong feelings of ownership and control over the third hand, despite only receiving visual feedback with no causal link to the actual brain signals. Our illusion is crucially different from previously reported studies as we demonstrate independent ownership and control of the third hand without loss of ownership in the real hands.

Resistive switching near electrode interfaces: Estimations by a current model

Science.gov (United States)

Schroeder, Herbert; Zurhelle, Alexander; Stemmer, Stefanie; Marchewka, Astrid; Waser, Rainer

2013-02-01

The growing resistive switching database is accompanied by many detailed mechanisms which often are pure hypotheses. Some of these suggested models can be verified by checking their predictions with the benchmarks of future memory cells. The valence change memory model assumes that the different resistances in ON and OFF states are made by changing the defect density profiles in a sheet near one working electrode during switching. The resulting different READ current densities in ON and OFF states were calculated by using an appropriate simulation model with variation of several important defect and material parameters of the metal/insulator (oxide)/metal thin film stack such as defect density and its profile change in density and thickness, height of the interface barrier, dielectric permittivity, applied voltage. The results were compared to the benchmarks and some memory windows of the varied parameters can be defined: The required ON state READ current density of 105 A/cm2 can only be achieved for barriers smaller than 0.7 eV and defect densities larger than 3 × 1020 cm-3. The required current ratio between ON and OFF states of at least 10 requests defect density reduction of approximately an order of magnitude in a sheet of several nanometers near the working electrode.

Design of a 32-channel EEG system for brain control interface applications.

Science.gov (United States)

Wang, Ching-Sung

2012-01-01

This study integrates the hardware circuit design and the development support of the software interface to achieve a 32-channel EEG system for BCI applications. Since the EEG signals of human bodies are generally very weak, in addition to preventing noise interference, it also requires avoiding the waveform distortion as well as waveform offset and so on; therefore, the design of a preamplifier with high common-mode rejection ratio and high signal-to-noise ratio is very important. Moreover, the friction between the electrode pads and the skin as well as the design of dual power supply will generate DC bias which affects the measurement signals. For this reason, this study specially designs an improved single-power AC-coupled circuit, which effectively reduces the DC bias and improves the error caused by the effects of part errors. At the same time, the digital way is applied to design the adjustable amplification and filter function, which can design for different EEG frequency bands. For the analog circuit, a frequency band will be taken out through the filtering circuit and then the digital filtering design will be used to adjust the extracted frequency band for the target frequency band, combining with MATLAB to design man-machine interface for displaying brain wave. Finally the measured signals are compared to the traditional 32-channel EEG signals. In addition to meeting the IFCN standards, the system design also conducted measurement verification in the standard EEG isolation room in order to demonstrate the accuracy and reliability of this system design.

Characterization of lead zirconate titanate (PZT)--indium tin oxide (ITO) thin film interface

International Nuclear Information System (INIS)

Sreenivas, K.; Sayer, M.; Laursen, T.; Whitton, J.L.; Pascual, R.; Johnson, D.J.; Amm, D.T.

1990-01-01

In this paper the interface between ultrathin sputtered lead zirconate titanate (PZT) films and a conductive electrode (indium tin oxide-ITO) is investigated. Structural and compositional changes at the PZT-ITO interface have been examined by surface analysis and depth profiling techniques of glancing angle x-ray diffraction, Rutherford backscattering (RBS), SIMS, Auger electron spectroscopy (AES), and elastic recoil detection analysis (ERDA). Studies indicate significant interdiffusion of lead into the underlying ITP layer and glass substrate with a large amount of residual stress at the interface. Influence of such compositional deviations at the interface is correlated to an observed thickness dependence in the dielectric properties of PZT films

Anatomy of the western Java plate interface from depth-migrated seismic images

OpenAIRE

Kopp, Heidrun; Hindle, David; Klaeschen, Dirk; Oncken, O.; Scholl, D.

2009-01-01

Newly pre-stack depth-migrated seismic images resolve the structural details of the western Java forearc and plate interface. The structural segmentation of the forearc into discrete mechanical domains correlates with distinct deformation styles. Approximately 2/3 of the trench sediment fill is detached and incorporated into frontal prism imbricates, while the floor sequence is underthrust beneath the décollement. Western Java, however, differs markedly from margins such as Nankai or Barbados...

Postmortem diffusion MRI of the human brainstem and thalamus for deep brain stimulator electrode localization

Science.gov (United States)

Calabrese, Evan; Hickey, Patrick; Hulette, Christine; Zhang, Jingxian; Parente, Beth; Lad, Shivanand P.; Johnson, G. Allan

2015-01-01

Deep brain stimulation (DBS) is an established surgical therapy for medically refractory tremor disorders including essential tremor (ET) and is currently under investigation for use in a variety of other neurologic and psychiatric disorders. There is growing evidence that the anti-tremor effects of DBS for ET are directly related to modulation of the dentatorubrothalamic tract (DRT), a white matter pathway that connects the cerebellum, red nucleus, and ventral intermediate nucleus of the thalamus. Emerging white matter targets for DBS, like the DRT, will require improved 3D reference maps of deep brain anatomy and structural connectivity for accurate electrode targeting. High-resolution diffusion MRI of postmortem brain specimens can provide detailed volumetric images of important deep brain nuclei and 3D reconstructions of white matter pathways with probabilistic tractography techniques. We present a high spatial and angular resolution diffusion MRI template of the postmortem human brainstem and thalamus with 3D reconstructions of the nuclei and white matter tracts involved in ET circuitry. We demonstrate accurate registration of these data to in vivo, clinical images from patients receiving DBS therapy, and correlate electrode proximity to tractography of the DRT with improvement of ET symptoms. PMID:26043869

Investigation of Implantable Multi-Channel Electrode Array in Rat Cerebral Cortex Used for Recording

Science.gov (United States)

Taniguchi, Noriyuki; Fukayama, Osamu; Suzuki, Takafumi; Mabuchi, Kunihiko

There have recently been many studies concerning the control of robot movements using neural signals recorded from the brain (usually called the Brain-Machine interface (BMI)). We fabricated implantable multi-electrode arrays to obtain neural signals from the rat cerebral cortex. As any multi-electrode array should have electrode alignment that minimizes invasion, it is necessary to customize the recording site. We designed three types of 22-channel multi-electrode arrays, i.e., 1) wide, 2) three-layered, and 3) separate. The first extensively covers the cerebral cortex. The second has a length of 2 mm, which can cover the area of the primary motor cortex. The third array has a separate structure, which corresponds to the position of the forelimb and hindlimb areas of the primary motor cortex. These arrays were implanted into the cerebral cortex of a rat. We estimated the walking speed from neural signals using our fabricated three-layered array to investigate its feasibility for BMI research. The neural signal of the rat and its walking speed were simultaneously recorded. The results revealed that evaluation using either the anterior electrode group or posterior group provided accurate estimates. However, two electrode groups around the center yielded poor estimates although it was possible to record neural signals.

Soft brain-machine interfaces for assistive robotics: A novel control approach.

Science.gov (United States)

Schiatti, Lucia; Tessadori, Jacopo; Barresi, Giacinto; Mattos, Leonardo S; Ajoudani, Arash

2017-07-01

Robotic systems offer the possibility of improving the life quality of people with severe motor disabilities, enhancing the individual's degree of independence and interaction with the external environment. In this direction, the operator's residual functions must be exploited for the control of the robot movements and the underlying dynamic interaction through intuitive and effective human-robot interfaces. Towards this end, this work aims at exploring the potential of a novel Soft Brain-Machine Interface (BMI), suitable for dynamic execution of remote manipulation tasks for a wide range of patients. The interface is composed of an eye-tracking system, for an intuitive and reliable control of a robotic arm system's trajectories, and a Brain-Computer Interface (BCI) unit, for the control of the robot Cartesian stiffness, which determines the interaction forces between the robot and environment. The latter control is achieved by estimating in real-time a unidimensional index from user's electroencephalographic (EEG) signals, which provides the probability of a neutral or active state. This estimated state is then translated into a stiffness value for the robotic arm, allowing a reliable modulation of the robot's impedance. A preliminary evaluation of this hybrid interface concept provided evidence on the effective execution of tasks with dynamic uncertainties, demonstrating the great potential of this control method in BMI applications for self-service and clinical care.

Detecting Mental States by Machine Learning Techniques: The Berlin Brain-Computer Interface

Science.gov (United States)

Blankertz, Benjamin; Tangermann, Michael; Vidaurre, Carmen; Dickhaus, Thorsten; Sannelli, Claudia; Popescu, Florin; Fazli, Siamac; Danóczy, Márton; Curio, Gabriel; Müller, Klaus-Robert

The Berlin Brain-Computer Interface Brain-Computer Interface (BBCI) uses a machine learning approach to extract user-specific patterns from high-dimensional EEG-features optimized for revealing the user's mental state. Classical BCI applications are brain actuated tools for patients such as prostheses (see Section 4.1) or mental text entry systems ([1] and see [2-5] for an overview on BCI). In these applications, the BBCI uses natural motor skills of the users and specifically tailored pattern recognition algorithms for detecting the user's intent. But beyond rehabilitation, there is a wide range of possible applications in which BCI technology is used to monitor other mental states, often even covert ones (see also [6] in the fMRI realm). While this field is still largely unexplored, two examples from our studies are exemplified in Sections 4.3 and 4.4.

BRAIN-COMPUTER-INTERFACE – SUPPORTED MOTOR IMAGERY TRAININTG FOR PATIENTS WITH HEMIPARESIS

Directory of Open Access Journals (Sweden)

O. A. Mokienko

2013-01-01

Full Text Available The aim of study was to assess the feasibility of motor imagery supported brain-computer interface in patients with hemiparesis. 13 patients with central paresis of the hand and 15 healthy volunteers were learning to control EEG-based interface with feedback. No differences on interface control quality were found between patients and healthy subjects. The trainings were accompanied by the desynchronization of sensorimotor rhythm. In patients with cortical damage the source of EEG-activity was dislocated.

Towards SSVEP-based, portable, responsive Brain-Computer Interface.

Science.gov (United States)

Kaczmarek, Piotr; Salomon, Pawel

2015-08-01

A Brain-Computer Interface in motion control application requires high system responsiveness and accuracy. SSVEP interface consisted of 2-8 stimuli and 2 channel EEG amplifier was presented in this paper. The observed stimulus is recognized based on a canonical correlation calculated in 1 second window, ensuring high interface responsiveness. A threshold classifier with hysteresis (T-H) was proposed for recognition purposes. Obtained results suggest that T-H classifier enables to significantly increase classifier performance (resulting in accuracy of 76%, while maintaining average false positive detection rate of stimulus different then observed one between 2-13%, depending on stimulus frequency). It was shown that the parameters of T-H classifier, maximizing true positive rate, can be estimated by gradient-based search since the single maximum was observed. Moreover the preliminary results, performed on a test group (N=4), suggest that for T-H classifier exists a certain set of parameters for which the system accuracy is similar to accuracy obtained for user-trained classifier.

Depth sensitivity and source-detector separations for near infrared spectroscopy based on the Colin27 brain template.

Directory of Open Access Journals (Sweden)

Gary E Strangman

Full Text Available Understanding the spatial and depth sensitivity of non-invasive near-infrared spectroscopy (NIRS measurements to brain tissue-i.e., near-infrared neuromonitoring (NIN - is essential for designing experiments as well as interpreting research findings. However, a thorough characterization of such sensitivity in realistic head models has remained unavailable. In this study, we conducted 3,555 Monte Carlo (MC simulations to densely cover the scalp of a well-characterized, adult male template brain (Colin27. We sought to evaluate: (i the spatial sensitivity profile of NIRS to brain tissue as a function of source-detector separation, (ii the NIRS sensitivity to brain tissue as a function of depth in this realistic and complex head model, and (iii the effect of NIRS instrument sensitivity on detecting brain activation. We found that increasing the source-detector (SD separation from 20 to 65 mm provides monotonic increases in sensitivity to brain tissue. For every 10 mm increase in SD separation (up to ~45 mm, sensitivity to gray matter increased an additional 4%. Our analyses also demonstrate that sensitivity in depth (S decreases exponentially, with a "rule-of-thumb" formula S=0.75*0.85(depth. Thus, while the depth sensitivity of NIRS is not strictly limited, NIN signals in adult humans are strongly biased towards the outermost 10-15 mm of intracranial space. These general results, along with the detailed quantitation of sensitivity estimates around the head, can provide detailed guidance for interpreting the likely sources of NIRS signals, as well as help NIRS investigators design and plan better NIRS experiments, head probes and instruments.

Brain-Computer Interface Controlled Cyborg: Establishing a Functional Information Transfer Pathway from Human Brain to Cockroach Brain.

Science.gov (United States)

Li, Guangye; Zhang, Dingguo

2016-01-01

An all-chain-wireless brain-to-brain system (BTBS), which enabled motion control of a cyborg cockroach via human brain, was developed in this work. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) was used in this system for recognizing human motion intention and an optimization algorithm was proposed in SSVEP to improve online performance of the BCI. The cyborg cockroach was developed by surgically integrating a portable microstimulator that could generate invasive electrical nerve stimulation. Through Bluetooth communication, specific electrical pulse trains could be triggered from the microstimulator by BCI commands and were sent through the antenna nerve to stimulate the brain of cockroach. Serial experiments were designed and conducted to test overall performance of the BTBS with six human subjects and three cockroaches. The experimental results showed that the online classification accuracy of three-mode BCI increased from 72.86% to 78.56% by 5.70% using the optimization algorithm and the mean response accuracy of the cyborgs using this system reached 89.5%. Moreover, the results also showed that the cyborg could be navigated by the human brain to complete walking along an S-shape track with the success rate of about 20%, suggesting the proposed BTBS established a feasible functional information transfer pathway from the human brain to the cockroach brain.

Electrochemical noise and impedance of Au electrode/electrolyte interfaces enabling extracellular detection of glioma cell populations.

Science.gov (United States)

Rocha, Paulo R F; Schlett, Paul; Kintzel, Ulrike; Mailänder, Volker; Vandamme, Lode K J; Zeck, Gunther; Gomes, Henrique L; Biscarini, Fabio; de Leeuw, Dago M

2016-10-06

Microelectrode arrays (MEA) record extracellular local field potentials of cells adhered to the electrodes. A disadvantage is the limited signal-to-noise ratio. The state-of-the-art background noise level is about 10 μVpp. Furthermore, in MEAs low frequency events are filtered out. Here, we quantitatively analyze Au electrode/electrolyte interfaces with impedance spectroscopy and noise measurements. The equivalent circuit is the charge transfer resistance in parallel with a constant phase element that describes the double layer capacitance, in series with a spreading resistance. This equivalent circuit leads to a Maxwell-Wagner relaxation frequency, the value of which is determined as a function of electrode area and molarity of an aqueous KCl electrolyte solution. The electrochemical voltage and current noise is measured as a function of electrode area and frequency and follow unambiguously from the measured impedance. By using large area electrodes the noise floor can be as low as 0.3 μVpp. The resulting high sensitivity is demonstrated by the extracellular detection of C6 glioma cell populations. Their minute electrical activity can be clearly detected at a frequency below about 10 Hz, which shows that the methodology can be used to monitor slow cooperative biological signals in cell populations.

Brain Machine Interfaces for Robotic Control in Space Applications, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This SBIR will study the application of a brain machine interface (BMI) to enable crew to remotely operate and monitor robots from inside a flight vehicle, habitat...

[In search of the musical brain].

Science.gov (United States)

Samson, S

2011-01-01

The emotional power of music opens novel prospects in the field of affective neurosciences. To clarify the neurobiological substrate of emotions brought by music, we adopted an integrative approach, which combines neuropsychology, brain imaging and electrophysiology (intracranial depth electrode recordings). The results of a series of studies carried out in patients with focal brain lesions allow to describe the involvement of different temporal lobe regions and, in particular, of the amygdala in these emotional judgments before discussing the therapeutic benefits of music to handle Alzheimer's disease.

[The current state of the brain-computer interface problem].

Science.gov (United States)

Shurkhay, V A; Aleksandrova, E V; Potapov, A A; Goryainov, S A

2015-01-01

It was only 40 years ago that the first PC appeared. Over this period, rather short in historical terms, we have witnessed the revolutionary changes in lives of individuals and the entire society. Computer technologies are tightly connected with any field, either directly or indirectly. We can currently claim that computers are manifold superior to a human mind in terms of a number of parameters; however, machines lack the key feature: they are incapable of independent thinking (like a human). However, the key to successful development of humankind is collaboration between the brain and the computer rather than competition. Such collaboration when a computer broadens, supplements, or replaces some brain functions is known as the brain-computer interface. Our review focuses on real-life implementation of this collaboration.

What turns assistive into restorative brain-machine interfaces?

Directory of Open Access Journals (Sweden)

Alireza Gharabaghi

2016-10-01

Full Text Available Brain-machine interfaces (BMI may support motor impaired patients during activities of daily living by controlling external devices such as prostheses (assistive BMI. Moreover, BMIs are applied in conjunction with robotic orthoses for rehabilitation of lost motor function via neurofeedback training (restorative BMI. Using assistive BMI in a rehabilitation context does not automatically turn them into restorative devices. This perspective article suggests key features of restorative BMI and provides the supporting evidence:In summary, BMI may be referred to as restorative tools when demonstrating subsequently (i operant learning and progressive evolution of specific brain states/dynamics, (ii correlated modulations of functional networks related to the therapeutic goal, (iii subsequent improvement in a specific task, and (iv an explicit correlation between the modulated brain dynamics and the achieved behavioral gains. Such findings would provide the rationale for translating BMI-based interventions into clinical settings for reinforcement learning and motor rehabilitation following stroke.

Remapping cortical modulation for electrocorticographic brain-computer interfaces: a somatotopy-based approach in individuals with upper-limb paralysis

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Degenhart, Alan D.; Hiremath, Shivayogi V.; Yang, Ying; Foldes, Stephen; Collinger, Jennifer L.; Boninger, Michael; Tyler-Kabara, Elizabeth C.; Wang, Wei

2018-04-01

Objective. Brain-computer interface (BCI) technology aims to provide individuals with paralysis a means to restore function. Electrocorticography (ECoG) uses disc electrodes placed on either the surface of the dura or the cortex to record field potential activity. ECoG has been proposed as a viable neural recording modality for BCI systems, potentially providing stable, long-term recordings of cortical activity with high spatial and temporal resolution. Previously we have demonstrated that a subject with spinal cord injury (SCI) could control an ECoG-based BCI system with up to three degrees of freedom (Wang et al 2013 PLoS One). Here, we expand upon these findings by including brain-control results from two additional subjects with upper-limb paralysis due to amyotrophic lateral sclerosis and brachial plexus injury, and investigate the potential of motor and somatosensory cortical areas to enable BCI control. Approach. Individuals were implanted with high-density ECoG electrode grids over sensorimotor cortical areas for less than 30 d. Subjects were trained to control a BCI by employing a somatotopic control strategy where high-gamma activity from attempted arm and hand movements drove the velocity of a cursor. Main results. Participants were capable of generating robust cortical modulation that was differentiable across attempted arm and hand movements of their paralyzed limb. Furthermore, all subjects were capable of voluntarily modulating this activity to control movement of a computer cursor with up to three degrees of freedom using the somatotopic control strategy. Additionally, for those subjects with electrode coverage of somatosensory cortex, we found that somatosensory cortex was capable of supporting ECoG-based BCI control. Significance. These results demonstrate the feasibility of ECoG-based BCI systems for individuals with paralysis as well as highlight some of the key challenges that must be overcome before such systems are translated to the clinical

A brain computer interface-based explorer.

Science.gov (United States)

Bai, Lijuan; Yu, Tianyou; Li, Yuanqing

2015-04-15

In recent years, various applications of brain computer interfaces (BCIs) have been studied. In this paper, we present a hybrid BCI combining P300 and motor imagery to operate an explorer. Our system is mainly composed of a BCI mouse, a BCI speller and an explorer. Through this system, the user can access his computer and manipulate (open, close, copy, paste, and delete) files such as documents, pictures, music, movies and so on. The system has been tested with five subjects, and the experimental results show that the explorer can be successfully operated according to subjects' intentions. Copyright © 2014 Elsevier B.V. All rights reserved.

A bidirectional brain-machine interface featuring a neuromorphic hardware decoder

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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.

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.

Region based Brain Computer Interface for a home control application.

Science.gov (United States)

Akman Aydin, Eda; Bay, Omer Faruk; Guler, Inan

2015-08-01

Environment control is one of the important challenges for disabled people who suffer from neuromuscular diseases. Brain Computer Interface (BCI) provides a communication channel between the human brain and the environment without requiring any muscular activation. The most important expectation for a home control application is high accuracy and reliable control. Region-based paradigm is a stimulus paradigm based on oddball principle and requires selection of a target at two levels. This paper presents an application of region based paradigm for a smart home control application for people with neuromuscular diseases. In this study, a region based stimulus interface containing 49 commands was designed. Five non-disabled subjects were attended to the experiments. Offline analysis results of the experiments yielded 95% accuracy for five flashes. This result showed that region based paradigm can be used to select commands of a smart home control application with high accuracy in the low number of repetitions successfully. Furthermore, a statistically significant difference was not observed between the level accuracies.

Improved Targeting Through Collaborative Decision-Making and Brain Computer Interfaces

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Stoica, Adrian; Barrero, David F.; McDonald-Maier, Klaus

2013-01-01

This paper reports a first step toward a brain-computer interface (BCI) for collaborative targeting. Specifically, we explore, from a broad perspective, how the collaboration of a group of people can increase the performance on a simple target identification task. To this end, we requested a group of people to identify the location and color of a sequence of targets appearing on the screen and measured the time and accuracy of the response. The individual results are compared to a collective identification result determined by simple majority voting, with random choice in case of drawn. The results are promising, as the identification becomes significantly more reliable even with this simple voting and a small number of people (either odd or even number) involved in the decision. In addition, the paper briefly analyzes the role of brain-computer interfaces in collaborative targeting, extending the targeting task by using a BCI instead of a mechanical response.

A brain-computer interface controlled mail client.

Science.gov (United States)

Yu, Tianyou; Li, Yuanqing; Long, Jinyi; Wang, Cong

2013-01-01

In this paper, we propose a brain-computer interface (BCI) based mail client. This system is controlled by hybrid features extracted from scalp-recorded electroencephalographic (EEG). We emulate the computer mouse by the motor imagery-based mu rhythm and the P300 potential. Furthermore, an adaptive P300 speller is included to provide text input function. With this BCI mail client, users can receive, read, write mails, as well as attach files in mail writing. The system has been tested on 3 subjects. Experimental results show that mail communication with this system is feasible.

Visual Prosthesis: Interfacing Stimulating Electrodes with Retinal Neurons to Restore Vision

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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.

Online LDA BASED brain-computer interface system to aid disabled people

OpenAIRE

Apdullah Yayık; Yakup Kutlu

2017-01-01

This paper aims to develop brain-computer interface system based on electroencephalography that can aid disabled people in daily life. The system relies on one of the most effective event-related potential wave, P300, which can be elicited by oddball paradigm. Developed application has a basic interaction tool that enables disabled people to convey their needs to other people selecting related objects. These objects pseudo-randomly flash in a visual interface on computer screen. The user must...

Evolution of the Brain Computing Interface (BCI and Proposed Electroencephalography (EEG Signals Based Authentication Model

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Ramzan Qaseem

2018-01-01

Full Text Available With current advancements in the field of Brain Computer interface it is required to study how it will affect the other technologies currently in use. In this paper, the authors motivate the need of Brain Computing Interface in the era of IoT (Internet of Things, and analyze how BCI in the presence of IoT could have serious privacy breach if not protected by new kind of more secure protocols. Security breach and hacking has been around for a long time but now we are sensitive towards data as our lives depend on it. When everything is interconnected through IoT and considering that we control all interconnected things by means of our brain using BCI (Brain Computer Interface, the meaning of security breach becomes much more sensitive than in the past. This paper describes the old security methods being used for authentication and how they can be compromised. Considering the sensitivity of data in the era of IoT, a new form of authentication is required, which should incorporate BCI rather than usual authentication techniques.

Polymer Coatings of Cochlear Implant Electrode Surface - An Option for Improving Electrode-Nerve-Interface by Blocking Fibroblast Overgrowth.

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C Hadler

Full Text Available Overgrowth of connective tissue and scar formation induced by the electrode array insertion increase the impedance and, thus, diminish the interactions between neural probes as like cochlear implants (CI and the target tissue. Therefore, it is of great clinical interest to modify the carrier material of the electrodes to improve the electrode nerve interface for selective cell adhesion. On one side connective tissue growth needs to be reduced to avoid electrode array encapsulation, on the other side the carrier material should not compromise the interaction with neuronal cells. The present in vitro-study qualitatively and quantitatively characterises the interaction of fibroblasts, glial cells and spiral ganglion neurons (SGN with ultrathin poly(N,N-dimethylacrylamide (PDMAA, poly(2-ethyloxazoline (PEtOx and poly([2-methacryloyloxyethyl]trimethylammoniumchlorid (PMTA films immobilised onto glass surfaces using a photoreactive anchor layer. The layer thickness and hydrophilicity of the polymer films were characterised by ellipsometric and water contact angle measurement. Moreover the topography of the surfaces was investigated using atomic force microscopy (AFM. The neuronal and non-neuronal cells were dissociated from spiral ganglions of postnatal rats and cultivated for 48 h on top of the polymer coatings. Immunocytochemical staining of neuronal and intermediary filaments revealed that glial cells predominantly attached on PMTA films, but not on PDMAA and PEtOx monolayers. Hereby, strong survival rates and neurite outgrowth were only found on PMTA, whereas PDMAA and PEtOx coatings significantly reduced the SG neuron survival and neuritogenesis. As also shown by scanning electron microscopy (SEM SGN strongly survived and retained their differentiated phenotype only on PMTA. In conclusion, survival and neuritogenesis of SGN may be associated with the extent of the glial cell growth. Since PMTA was the only of the polar polymers used in this study

Ethical Issues in Brain-Computer Interface Research, Development, and Dissemination

NARCIS (Netherlands)

Vlek, Rutger; Steines, David; Szibbo, Dyana; Kübler, Andrea; Schneider, Mary-Jane; Haselager, Pim; Nijboer, Femke

The steadily growing field of brain-computer interfacing (BCI) may develop useful technologies, with a potential impact not only on individuals, but also on society as a whole. At the same time, the development of BCI presents significant ethical and legal challenges. In a workshop during the 4th

New generation of human machine interfaces for controlling UAV through depth-based gesture recognition

Science.gov (United States)

Mantecón, Tomás.; del Blanco, Carlos Roberto; Jaureguizar, Fernando; García, Narciso

2014-06-01

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces.

Science.gov (United States)

Heo, Jeong; Yoon, Heenam; Park, Kwang Suk

2017-06-23

Amyotrophic lateral sclerosis (ALS) patients whose voluntary muscles are paralyzed commonly communicate with the outside world using eye movement. There have been many efforts to support this method of communication by tracking or detecting eye movement. An electrooculogram (EOG), an electro-physiological signal, is generated by eye movements and can be measured with electrodes placed around the eye. In this study, we proposed a new practical electrode position on the forehead to measure EOG signals, and we developed a wearable forehead EOG measurement system for use in Human Computer/Machine interfaces (HCIs/HMIs). Four electrodes, including the ground electrode, were placed on the forehead. The two channels were arranged vertically and horizontally, sharing a positive electrode. Additionally, a real-time eye movement classification algorithm was developed based on the characteristics of the forehead EOG. Three applications were employed to evaluate the proposed system: a virtual keyboard using a modified Bremen BCI speller and an automatic sequential row-column scanner, and a drivable power wheelchair. The mean typing speeds of the modified Bremen brain-computer interface (BCI) speller and automatic row-column scanner were 10.81 and 7.74 letters per minute, and the mean classification accuracies were 91.25% and 95.12%, respectively. In the power wheelchair demonstration, the user drove the wheelchair through an 8-shape course without collision with obstacles.

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.

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

Structural and magnetic depth profiles of magneto-ionic heterostructures beyond the interface limit

Energy Technology Data Exchange (ETDEWEB)

Gilbert, DA; Grutter, AJ; Arenholz, E; Liu, K; Kirby, BJ; Borchers, JA; Maranville, BB

2016-07-22

Electric field control of magnetism provides a promising route towards ultralow power information storage and sensor technologies. The effects of magneto-ionic motion have been prominently featured in the modification of interface characteristics. Here, we demonstrate magnetoelectric coupling moderated by voltage-driven oxygen migration beyond the interface in relatively thick AlO_x/GdO_x/Co(15 nm) films. Oxygen migration and Co magnetization are quantitatively mapped with polarized neutron reflectometry under electro-thermal conditioning. The depth-resolved profiles uniquely identify interfacial and bulk behaviours and a semi-reversible control of the magnetization. Magnetometry measurements suggest changes in the microstructure which disrupt long-range ferromagnetic ordering, resulting in an additional magnetically soft phase. X-ray spectroscopy confirms changes in the Co oxidation state, but not in the Gd, suggesting that the GdO_x transmits oxygen but does not source or sink it. These results together provide crucial insight into controlling magnetism via magneto-ionic motion, both at interfaces and throughout the bulk of the films.

A subject-independent pattern-based Brain-Computer Interface

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Andreas Markus Ray

2015-10-01

Full Text Available While earlier Brain-Computer Interface (BCI studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e. happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to match their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders.

뇌-컴퓨터 쿸터페쿴스 (Brain-Computer Interfaces) 기술엿 대한 국내·외 연구개발 뿙향 조사 (Research and Development in Brain-Computer Interfacing Technology: A Comprehensive Technical Review). Final Report.

NARCIS (Netherlands)

Nam, Chang Soo; Kim, Sung-Phil; Krusienkki, Dean; Nijholt, Antinus

2015-01-01

This report commisioned by the Korean American Scientists and Engineers Association (KSEA) and written with the support of the Korea Federation of Science and Technology Societies (KOFST) surveys research and development trends in the area of brain-computer interface (Brain-Computer Interfaces, BCI)

Amplifier spurious input current components in electrode-electrolyte interface impedance measurements

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Madrid Rossana E

2005-03-01

Full Text Available Abstract Background In Impedance Microbiology, the time during which the measuring equipment is connected to the bipolar cells is rather long, usually between 6 to 24 hrs for microorganisms with duplication times in the order of less than one hour and concentrations ranging from 101 to 107 [CFU/ml]. Under these conditions, the electrode-electrolyte interface impedance may show a slow drift of about 2%/hr. By and large, growth curves superimposed on such drift do not stabilize, are less reproducible, and keep on distorting all over the measurement of the temporal reactive or resistive records due to interface changes, in turn originated in bacterial activity. This problem has been found when growth curves were obtained by means of impedance analyzers or with impedance bridges using different types of operational amplifiers. Methods Suspecting that the input circuitry was the culprit of the deleterious effect, we used for that matter (a ultra-low bias current amplifiers, (b isolating relays for the selection of cells, and (c a shorter connection time, so that the relays were maintained opened after the readings, to bring down such spurious drift to a negligible value. Bacterial growth curves were obtained in order to test their quality. Results It was demonstrated that the drift decreases ten fold when the circuit remained connected to the cell for a short time between measurements, so that the distortion became truly negligible. Improvement due to better-input amplifiers was not as good as by reducing the connection time. Moreover, temperature effects were insignificant with a regulation of ± 0.2 [°C]. Frequency did not influence either. Conclusion The drift originated either at the dc input bias offset current (Ios of the integrated circuits, or in discrete transistors connected directly to the electrodes immersed in the cells, depending on the particular circuit arrangement. Reduction of the connection time was the best countermeasure.

Using brain-computer interfaces and brain-state dependent stimulation as tools in cognitive neuroscience

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Ole eJensen

2011-05-01

Full Text Available Large efforts are currently being made to develop and improve online analysis of brain activity which can be used e.g. for brain-computer interfacing (BCI. A BCI allows a subject to control a device by willfully changing his/her own brain activity. BCI therefore holds the promise as a tool for aiding the disabled and for augmenting human performance. While technical developments obviously are important, we will here argue that new insight gained from cognitive neuroscience can be used to identify signatures of neural activation which reliably can be modulated by the subject at will. This review will focus mainly on oscillatory activity in the alpha band which is strongly modulated by changes in covert attention. Besides developing BCIs for their traditional purpose, they might also be used as a research tool for cognitive neuroscience. There is currently a strong interest in how brain state fluctuations impact cognition. These state fluctuations are partly reflected by ongoing oscillatory activity. The functional role of the brain state can be investigated by introducing stimuli in real time to subjects depending on the actual state of the brain. This principle of brain-state dependent stimulation may also be used as a practical tool for augmenting human behavior. In conclusion, new approaches based on online analysis of ongoing brain activity are currently in rapid development. These approaches are amongst others informed by new insight gained from EEG/MEG studies in cognitive neuroscience and hold the promise of providing new ways for investigating the brain at work.

A Review of Hybrid Brain-Computer Interface Systems

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Setare Amiri

2013-01-01

Full Text Available Increasing number of research activities and different types of studies in brain-computer interface (BCI systems show potential in this young research area. Research teams have studied features of different data acquisition techniques, brain activity patterns, feature extraction techniques, methods of classifications, and many other aspects of a BCI system. However, conventional BCIs have not become totally applicable, due to the lack of high accuracy, reliability, low information transfer rate, and user acceptability. A new approach to create a more reliable BCI that takes advantage of each system is to combine two or more BCI systems with different brain activity patterns or different input signal sources. This type of BCI, called hybrid BCI, may reduce disadvantages of each conventional BCI system. In addition, hybrid BCIs may create more applications and possibly increase the accuracy and the information transfer rate. However, the type of BCIs and their combinations should be considered carefully. In this paper, after introducing several types of BCIs and their combinations, we review and discuss hybrid BCIs, different possibilities to combine them, and their advantages and disadvantages.

Implantação estereotáxica de eletrodos profundos por ressonância magnética para cirurgia de epilepsia MRI-guided stereotactic implantation of depth electrodes in epilepsy surgery

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MURILO S. MENESES

1999-09-01

Full Text Available Apresentamos o caso de uma paciente com epilepsia refratária ao tratamento medicamentoso e submetida à monitorização em vídeo-eletrencefalografia por eletrodos de profundidade intracerebrais. A história, o exame clínico, a ressonância magnética (RM, a vídeo-eletrencefalografia e o estudo neuropsicológico não foram suficientes para a determinação da área cerebral de origem das crises convulsivas. Eletrodos de profundidade intracerebrais colocados por estereotaxia guiada por RM possibilitaram o registro de forma muito clara da atividade epileptiforme, determinando com precisão a área cerebral epileptogênica a ser removida por cirurgia. Após lobectomia temporal anterior direita com amígdalo-hipocampectomia realizada há três meses, a paciente permanece sem crises convulsivas. Segundo informações obtidas durante o último Congresso da Liga Brasileira de Epilepsia, esta é a primeira cirurgia estereotáxica para colocação de eletrodos de profundidade intracerebrais em epilepsia no Brasil.We present the case of a 40-year-old woman with refractory epilepsy since aged 18, who was submitted to video-EEG monitoring with intracerebral depth electrodes. The clinical history and examination, magnetic resonance image (MRI, video-EEG and neuropsychological study did not allow the determination of the cerebral onset of epileptic seizures. Depth electrodes inserted by MRI-guided stereotaxis allowed the recording of the epileptic activity and thus showed quite accurately the area of the brain to be surgically resected. She underwent a right anterior temporal lobectomy with amygdalohippocampectomy. The immediate postoperative period was uneventful and she is without epileptic seizures after three months of follow-up. The average pre-operative free-seizure period was two weeks. To our knowledge, this is the first stereotactic surgery for insertion of depth intracerebral electrodes in epilepsy in Brazil.

Identifying cochlear implant channels with poor electrode-neuron interface: partial tripolar, single-channel thresholds and psychophysical tuning curves.

Science.gov (United States)

Bierer, Julie Arenberg; Faulkner, Kathleen F

2010-04-01

The goal of this study was to evaluate the ability of a threshold measure, made with a restricted electrode configuration, to identify channels exhibiting relatively poor spatial selectivity. With a restricted electrode configuration, channel-to-channel variability in threshold may reflect variations in the interface between the electrodes and auditory neurons (i.e., nerve survival, electrode placement, and tissue impedance). These variations in the electrode-neuron interface should also be reflected in psychophysical tuning curve (PTC) measurements. Specifically, it is hypothesized that high single-channel thresholds obtained with the spatially focused partial tripolar (pTP) electrode configuration are predictive of wide or tip-shifted PTCs. Data were collected from five cochlear implant listeners implanted with the HiRes90k cochlear implant (Advanced Bionics Corp., Sylmar, CA). Single-channel thresholds and most comfortable listening levels were obtained for stimuli that varied in presumed electrical field size by using the pTP configuration for which a fraction of current (sigma) from a center-active electrode returns through two neighboring electrodes and the remainder through a distant indifferent electrode. Forward-masked PTCs were obtained for channels with the highest, lowest, and median tripolar (sigma = 1 or 0.9) thresholds. The probe channel and level were fixed and presented with either the monopolar (sigma = 0) or a more focused pTP (sigma > or = 0.55) configuration. The masker channel and level were varied, whereas the configuration was fixed to sigma = 0.5. A standard, three-interval, two-alternative forced choice procedure was used for thresholds and masked levels. Single-channel threshold and variability in threshold across channels systematically increased as the compensating current, sigma, increased and the presumed electrical field became more focused. Across subjects, channels with the highest single-channel thresholds, when measured with a

New electrodes for hydrogen/oxygen solid polymer electrolyte fuel cell

Energy Technology Data Exchange (ETDEWEB)

Mosdale, R [CEA Centre d` Etudes de Grenoble, 38 (France). Dept. de Recherche Fondamentale sur la Matiere Condensee; Stevens, P [CEA Centre d` Etudes de Grenoble, 38 (France). Dept. de Thermohydraulique et de Physique

1993-12-31

A new method of preparation of Electrode/Membrane/Electrode (EME) assemblies for Proton Exchange Membrane Fuel Cells (PEMFC) has been developed. The electrodes are deposited directly onto a Nafion electrolyte membrane from a mixture of platinized carbon, Nafion solution, and PTFE by using a spray technique. By this technique, porous electrodes are obtained with an optimized gas/electrolyte/catalyst interface, and electrode/membrane interface.

Toward affective brain-computer interfaces : exploring the neurophysiology of affect during human media interaction

NARCIS (Netherlands)

Mühl, C.

2012-01-01

Affective Brain-Computer Interfaces (aBCI), the sensing of emotions from brain activity, seems a fantasy from the realm of science fiction. But unlike faster-than-light travel or teleportation, aBCI seems almost within reach due to novel sensor technologies, the advancement of neuroscience, and the

EEG-based emergency braking intention prediction for brain-controlled driving considering one electrode falling-off.

Science.gov (United States)

Huikang Wang; Luzheng Bi; Teng Teng

2017-07-01

This paper proposes a novel method of electroencephalography (EEG)-based driver emergency braking intention detection system for brain-controlled driving considering one electrode falling-off. First, whether one electrode falls off is discriminated based on EEG potentials. Then, the missing signals are estimated by using the signals collected from other channels based on multivariate linear regression. Finally, a linear decoder is applied to classify driver intentions. Experimental results show that the falling-off discrimination accuracy is 99.63% on average and the correlation coefficient and root mean squared error (RMSE) between the estimated and experimental data are 0.90 and 11.43 μV, respectively, on average. Given one electrode falls off, the system accuracy of the proposed intention prediction method is significantly higher than that of the original method (95.12% VS 79.11%) and is close to that (95.95%) of the original system under normal situations (i. e., no electrode falling-off).

Neuroanatomical correlates of brain-computer interface performance.

Science.gov (United States)

Kasahara, Kazumi; DaSalla, Charles Sayo; Honda, Manabu; Hanakawa, Takashi

2015-04-15

Brain-computer interfaces (BCIs) offer a potential means to replace or restore lost motor function. However, BCI performance varies considerably between users, the reasons for which are poorly understood. Here we investigated the relationship between sensorimotor rhythm (SMR)-based BCI performance and brain structure. Participants were instructed to control a computer cursor using right- and left-hand motor imagery, which primarily modulated their left- and right-hemispheric SMR powers, respectively. Although most participants were able to control the BCI with success rates significantly above chance level even at the first encounter, they also showed substantial inter-individual variability in BCI success rate. Participants also underwent T1-weighted three-dimensional structural magnetic resonance imaging (MRI). The MRI data were subjected to voxel-based morphometry using BCI success rate as an independent variable. We found that BCI performance correlated with gray matter volume of the supplementary motor area, supplementary somatosensory area, and dorsal premotor cortex. We suggest that SMR-based BCI performance is associated with development of non-primary somatosensory and motor areas. Advancing our understanding of BCI performance in relation to its neuroanatomical correlates may lead to better customization of BCIs based on individual brain structure. Copyright © 2015 Elsevier Inc. All rights reserved.

Brain-Computer Interfaces Applying Our Minds to Human-computer Interaction

CERN Document Server

Tan, Desney S

2010-01-01

For generations, humans have fantasized about the ability to create devices that can see into a person's mind and thoughts, or to communicate and interact with machines through thought alone. Such ideas have long captured the imagination of humankind in the form of ancient myths and modern science fiction stories. Recent advances in cognitive neuroscience and brain imaging technologies have started to turn these myths into a reality, and are providing us with the ability to interface directly with the human brain. This ability is made possible through the use of sensors that monitor physical p

First Principle simulations of electrochemical interfaces - a DFT study

DEFF Research Database (Denmark)

Ahmed, Rizwan

for the whole system to qualify as a proper electrochemical interface. I have also contributed to the model, which accounts for pH in the first principle electrode-electrolyte interface simulations. This is an important step forward, since electrochemical reaction rate and barrier for charge transfer can......In this thesis, I have looked beyond the computational hydrogen electrode (CHE) model, and focused on the first principle simulations which treats the electrode-electrolyte interfaces explicitly. Since obtaining a realistic electrode-electrolyte interface was difficult, I aimed to address various...... challenges regarding first principle electrochemical interface modeling in order to bridge the gap between the model interface used in simulations and real catalyst at operating conditions. Atomic scale insight for the processes and reactions that occur at the electrochemical interface presents a challenge...

Atomic-Scale Simulation of Electrochemical Processes at Electrode/Water Interfaces under Referenced Bias Potential.

Science.gov (United States)

Bouzid, Assil; Pasquarello, Alfredo

2018-04-19

Based on constant Fermi-level molecular dynamics and a proper alignment scheme, we perform simulations of the Pt(111)/water interface under variable bias potential referenced to the standard hydrogen electrode (SHE). Our scheme yields a potential of zero charge μ pzc of ∼0.22 eV relative to the SHE and a double layer capacitance C dl of ≃19 μF cm -2 , in excellent agreement with experimental measurements. In addition, we study the structural reorganization of the electrical double layer for bias potentials ranging from -0.92 eV to +0.44 eV and find that O down configurations, which are dominant at potentials above the pzc, reorient to favor H down configurations as the measured potential becomes negative. Our modeling scheme allows one to not only access atomic-scale processes at metal/water interfaces, but also to quantitatively estimate macroscopic electrochemical quantities.

The Changes in the Hemodynamic Activity of the Brain during Motor Imagery Training with the Use of Brain-Computer Interface

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Silchenko, A.V.; Tintěra, J.; Rydlo, J.

2016-01-01

Roč. 42, č. 1 (2016), s. 1-12 ISSN 0362-1197 R&D Projects: GA MŠk ED1.1.00/02.0070 Grant - others:GA MŠk(CZ) EE.2.3.20.0073 Institutional support: RVO:67985807 Keywords : brain-computer interface * motor imagery * hemodynamic activity * brain plasticity * functional MRI Subject RIV: IN - Informatics, Computer Science

An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode.

Science.gov (United States)

Shon, Ahnsei; Chu, Jun-Uk; Jung, Jiuk; Kim, Hyungmin; Youn, Inchan

2017-12-21

Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS) components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC)-compliant power transmission circuit, a medical implant communication service (MICS)-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time.

An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode

Directory of Open Access Journals (Sweden)

Ahnsei Shon

2017-12-01

Full Text Available Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC-compliant power transmission circuit, a medical implant communication service (MICS-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time.

Semi-automated Anatomical Labeling and Inter-subject Warping of High-Density Intracranial Recording Electrodes in Electrocorticography

Directory of Open Access Journals (Sweden)

Liberty S. Hamilton

2017-10-01

Full Text Available In this article, we introduce img_pipe, our open source python package for preprocessing of imaging data for use in intracranial electrocorticography (ECoG and intracranial stereo-EEG analyses. The process of electrode localization, labeling, and warping for use in ECoG currently varies widely across laboratories, and it is usually performed with custom, lab-specific code. This python package aims to provide a standardized interface for these procedures, as well as code to plot and display results on 3D cortical surface meshes. It gives the user an easy interface to create anatomically labeled electrodes that can also be warped to an atlas brain, starting with only a preoperative T1 MRI scan and a postoperative CT scan. We describe the full capabilities of our imaging pipeline and present a step-by-step protocol for users.

Evaluation of a modified Fitts law brain-computer interface target acquisition task in able and motor disabled individuals

Science.gov (United States)

Felton, E. A.; Radwin, R. G.; Wilson, J. A.; Williams, J. C.

2009-10-01

A brain-computer interface (BCI) is a communication system that takes recorded brain signals and translates them into real-time actions, in this case movement of a cursor on a computer screen. This work applied Fitts' law to the evaluation of performance on a target acquisition task during sensorimotor rhythm-based BCI training. Fitts' law, which has been used as a predictor of movement time in studies of human movement, was used here to determine the information transfer rate, which was based on target acquisition time and target difficulty. The information transfer rate was used to make comparisons between control modalities and subject groups on the same task. Data were analyzed from eight able-bodied and five motor disabled participants who wore an electrode cap that recorded and translated their electroencephalogram (EEG) signals into computer cursor movements. Direct comparisons were made between able-bodied and disabled subjects, and between EEG and joystick cursor control in able-bodied subjects. Fitts' law aptly described the relationship between movement time and index of difficulty for each task movement direction when evaluated separately and averaged together. This study showed that Fitts' law can be successfully applied to computer cursor movement controlled by neural signals.

Evolution of brain-computer interfaces: going beyond classic motor physiology

Science.gov (United States)

Leuthardt, Eric C.; Schalk, Gerwin; Roland, Jarod; Rouse, Adam; Moran, Daniel W.

2010-01-01

The notion that a computer can decode brain signals to infer the intentions of a human and then enact those intentions directly through a machine is becoming a realistic technical possibility. These types of devices are known as brain-computer interfaces (BCIs). The evolution of these neuroprosthetic technologies could have significant implications for patients with motor disabilities by enhancing their ability to interact and communicate with their environment. The cortical physiology most investigated and used for device control has been brain signals from the primary motor cortex. To date, this classic motor physiology has been an effective substrate for demonstrating the potential efficacy of BCI-based control. However, emerging research now stands to further enhance our understanding of the cortical physiology underpinning human intent and provide further signals for more complex brain-derived control. In this review, the authors report the current status of BCIs and detail the emerging research trends that stand to augment clinical applications in the future. PMID:19569892

Implantable fiber-optic interface for parallel multisite long-term optical dynamic brain interrogation in freely moving mice

Science.gov (United States)

Doronina-Amitonova, L. V.; Fedotov, I. V.; Ivashkina, O. I.; Zots, M. A.; Fedotov, A. B.; Anokhin, K. V.; Zheltikov, A. M.

2013-01-01

Seeing the big picture of functional responses within large neural networks in a freely functioning brain is crucial for understanding the cellular mechanisms behind the higher nervous activity, including the most complex brain functions, such as cognition and memory. As a breakthrough toward meeting this challenge, implantable fiber-optic interfaces integrating advanced optogenetic technologies and cutting-edge fiber-optic solutions have been demonstrated, enabling a long-term optogenetic manipulation of neural circuits in freely moving mice. Here, we show that a specifically designed implantable fiber-optic interface provides a powerful tool for parallel long-term optical interrogation of distinctly separate, functionally different sites in the brain of freely moving mice. This interface allows the same groups of neurons lying deeply in the brain of a freely behaving mouse to be reproducibly accessed and optically interrogated over many weeks, providing a long-term dynamic detection of genome activity in response to a broad variety of pharmacological and physiological stimuli. PMID:24253232

Fluctuations at electrode-YSZ interfaces

DEFF Research Database (Denmark)

Jacobsen, T.; Hansen, K.V.; Skou, E.

in D/A converters, duty cycles of thermo regulators, etc. But even so, the dramatic spikes seen at the Ni anode emphasizes the care that must be taken in order to obtain reproducible results from point electrode studies. However, it is noted that Pt cathodes and Ni anodes show reverse patterns...

Electrode interface controlled electrical properties in epitaxial Pb(Zr{sub 0.52}Ti{sub 0.48})O{sub 3} films grown on Si substrates with SrTiO{sub 3} buffer layer

Energy Technology Data Exchange (ETDEWEB)

Boni, Andra Georgia, E-mail: andra.boni@infim.ro [National Institute of Materials Physics, Atomistilor 105bis, Magurele, Ilfov 77125 (Romania); University of Bucharest, Faculty of Physics, Magurele 077125 (Romania); Chirila, Cristina; Pasuk, Iuliana; Negrea, Raluca; Trupina, Lucian [National Institute of Materials Physics, Atomistilor 105bis, Magurele, Ilfov 77125 (Romania); Le Rhun, Gwenael [CEA, LETI, MINATEC Campus, 17 rue des Martyrs, 38054 Grenoble cedex 9 (France); Vilquin, Bertrand [Université de Lyon, Ecole Centrale de Lyon, INL, CNRS UMR5270, 36 avenue Guy de Collongue, F-69134 Ecully cedex (France); Pintilie, Ioana; Pintilie, Lucian [National Institute of Materials Physics, Atomistilor 105bis, Magurele, Ilfov 77125 (Romania)

2015-10-30

Electrical properties of ferroelectric capacitors based on PbZr{sub 0.52}Ti{sub 0.48}O{sub 3} thin films grown by pulsed laser deposition on silicon substrate with SrTiO{sub 3} buffer layer grown by molecular beam epitaxy were studied. A SrRuO{sub 3} layer was deposited as bottom electrode also by pulse laser deposition and Pt, Ir, Ru, SrRuO{sub 3} were used as top contacts. Electrical characterization comprised hysteresis and capacitance–voltage measurements in the temperature range from 150 K to 400 K. It was found that the macroscopic electrical properties are affected by the electrode interface, by the choice of the top electrode. However, even for metals with very different work functions (e.g. Pt and SrRuO{sub 3}) the properties of the top and bottom electrode interfaces remain fairly symmetric suggesting a strong influence from the bound polarization charges located near the interface. - Highlights: • Ferroelectric capacitors based on PbZr{sub 0.52}Ti{sub 0.48}O{sub 3} were deposited on Si substrate. • The structural characterization proved the epitaxial growth of the layers. • Macroscopic electrical properties are affected by the choice of the top electrode. • The difference on imprint field, dielectric constant are analyzed depending on the electrode-ferroelectric interface.

Detection of EEG electrodes in brain volumes.

Science.gov (United States)

Graffigna, Juan P; Gómez, M Eugenia; Bustos, José J

2010-01-01

This paper presents a method to detect 128 EEG electrodes in image study and to merge with the Nuclear Magnetic Resonance volume for better diagnosis. First we propose three hypotheses to define a specific acquisition protocol in order to recognize the electrodes and to avoid distortions in the image. In the second instance we describe a method for segmenting the electrodes. Finally, registration is performed between volume of the electrodes and NMR.

Evolvix BEST Names for semantic reproducibility across code2brain interfaces.

Science.gov (United States)

Loewe, Laurence; Scheuer, Katherine S; Keel, Seth A; Vyas, Vaibhav; Liblit, Ben; Hanlon, Bret; Ferris, Michael C; Yin, John; Dutra, Inês; Pietsch, Anthony; Javid, Christine G; Moog, Cecilia L; Meyer, Jocelyn; Dresel, Jerdon; McLoone, Brian; Loberger, Sonya; Movaghar, Arezoo; Gilchrist-Scott, Morgaine; Sabri, Yazeed; Sescleifer, Dave; Pereda-Zorrilla, Ivan; Zietlow, Andrew; Smith, Rodrigo; Pietenpol, Samantha; Goldfinger, Jacob; Atzen, Sarah L; Freiberg, Erika; Waters, Noah P; Nusbaum, Claire; Nolan, Erik; Hotz, Alyssa; Kliman, Richard M; Mentewab, Ayalew; Fregien, Nathan; Loewe, Martha

2017-01-01

Names in programming are vital for understanding the meaning of code and big data. We define code2brain (C2B) interfaces as maps in compilers and brains between meaning and naming syntax, which help to understand executable code. While working toward an Evolvix syntax for general-purpose programming that makes accurate modeling easy for biologists, we observed how names affect C2B quality. To protect learning and coding investments, C2B interfaces require long-term backward compatibility and semantic reproducibility (accurate reproduction of computational meaning from coder-brains to reader-brains by code alone). Semantic reproducibility is often assumed until confusing synonyms degrade modeling in biology to deciphering exercises. We highlight empirical naming priorities from diverse individuals and roles of names in different modes of computing to show how naming easily becomes impossibly difficult. We present the Evolvix BEST (Brief, Explicit, Summarizing, Technical) Names concept for reducing naming priority conflicts, test it on a real challenge by naming subfolders for the Project Organization Stabilizing Tool system, and provide naming questionnaires designed to facilitate C2B debugging by improving names used as keywords in a stabilizing programming language. Our experiences inspired us to develop Evolvix using a flipped programming language design approach with some unexpected features and BEST Names at its core. © 2016 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

CONTROL OF A ROBOTIC ARM THROUGH A BRAIN MACHINE INTERFACE WITH MUTUAL LEARNING

OpenAIRE

ALEXANDRE ORMIGA GALVAO BARBOSA

2010-01-01

Esse trabalho apresenta o desenvolvimento de uma interface cérebro-máquina (Brain Machine Interface - BMI) como um meio alternativo de comunicação para uso na robótica. O trabalho engloba o projeto e construção de um eletroencefalógrafo (EEG), assim como o desenvolvimento de todos os algoritmos computacionais e demais técnicas necessárias para o reconhecimento de atividades mentais. A interface cérebro-máquina desenvolvida é utilizada para comandar os movimentos de um manipulador robótico MA2...

Training to use a commercial brain-computer interface as access technology: a case study.

Science.gov (United States)

Taherian, Sarvnaz; Selitskiy, Dmitry; Pau, James; Davies, T Claire; Owens, R Glynn

2016-01-01

This case study describes how an individual with spastic quadriplegic cerebral palsy was trained over a period of four weeks to use a commercial electroencephalography (EEG)-based brain-computer interface (BCI). The participant spent three sessions exploring the system, and seven sessions playing a game focused on EEG feedback training of left and right arm motor imagery and a customised, training game paradigm was employed. The participant showed improvement in the production of two distinct EEG patterns. The participant's performance was influenced by motivation, fatigue and concentration. Six weeks post-training the participant could still control the BCI and used this to type a sentence using an augmentative and alternative communication application on a wirelessly linked device. The results from this case study highlight the importance of creating a dynamic, relevant and engaging training environment for BCIs. Implications for Rehabilitation Customising a training paradigm to suit the users' interests can influence adherence to assistive technology training. Mood, fatigue, physical illness and motivation influence the usability of a brain-computer interface. Commercial brain-computer interfaces, which require little set up time, may be used as access technology for individuals with severe disabilities.

Evaluation of LDA Ensembles Classifiers for Brain Computer Interface

International Nuclear Information System (INIS)

Arjona, Cristian; Pentácolo, José; Gareis, Iván; Atum, Yanina; Gentiletti, Gerardo; Acevedo, Rubén; Rufiner, Leonardo

2011-01-01

The Brain Computer Interface (BCI) translates brain activity into computer commands. To increase the performance of the BCI, to decode the user intentions it is necessary to get better the feature extraction and classification techniques. In this article the performance of a three linear discriminant analysis (LDA) classifiers ensemble is studied. The system based on ensemble can theoretically achieved better classification results than the individual counterpart, regarding individual classifier generation algorithm and the procedures for combine their outputs. Classic algorithms based on ensembles such as bagging and boosting are discussed here. For the application on BCI, it was concluded that the generated results using ER and AUC as performance index do not give enough information to establish which configuration is better.

Designing a hands-on brain computer interface laboratory course.

Science.gov (United States)

Khalighinejad, Bahar; Long, Laura Kathleen; Mesgarani, Nima

2016-08-01

Devices and systems that interact with the brain have become a growing field of research and development in recent years. Engineering students are well positioned to contribute to both hardware development and signal analysis techniques in this field. However, this area has been left out of most engineering curricula. We developed an electroencephalography (EEG) based brain computer interface (BCI) laboratory course to educate students through hands-on experiments. The course is offered jointly by the Biomedical Engineering, Electrical Engineering, and Computer Science Departments of Columbia University in the City of New York and is open to senior undergraduate and graduate students. The course provides an effective introduction to the experimental design, neuroscience concepts, data analysis techniques, and technical skills required in the field of BCI.

Feasibility of task-specific brain-machine interface training for upper-extremity paralysis in patients with chronic hemiparetic stroke.

Science.gov (United States)

Nishimoto, Atsuko; Kawakami, Michiyuki; Fujiwara, Toshiyuki; Hiramoto, Miho; Honaga, Kaoru; Abe, Kaoru; Mizuno, Katsuhiro; Ushiba, Junichi; Liu, Meigen

2018-01-10

Brain-machine interface training was developed for upper-extremity rehabilitation for patients with severe hemiparesis. Its clinical application, however, has been limited because of its lack of feasibility in real-world rehabilitation settings. We developed a new compact task-specific brain-machine interface system that enables task-specific training, including reach-and-grasp tasks, and studied its clinical feasibility and effectiveness for upper-extremity motor paralysis in patients with stroke. Prospective beforeâ€"after study. Twenty-six patients with severe chronic hemiparetic stroke. Participants were trained with the brain-machine interface system to pick up and release pegs during 40-min sessions and 40 min of standard occupational therapy per day for 10 days. Fugl-Meyer upper-extremity motor (FMA) and Motor Activity Log-14 amount of use (MAL-AOU) scores were assessed before and after the intervention. To test its feasibility, 4 occupational therapists who operated the system for the first time assessed it with the Quebec User Evaluation of Satisfaction with assistive Technology (QUEST) 2.0. FMA and MAL-AOU scores improved significantly after brain-machine interface training, with the effect sizes being medium and large, respectively (pmachine interface system is feasible for use in real-world clinical settings.

Towards a Switched-Capacitor Based Stimulator for Efficient Deep-Brain Stimulation

Science.gov (United States)

Vidal, Jose; Ghovanloo, Maysam

2013-01-01

We have developed a novel 4-channel prototype stimulation circuit for implantable neurological stimulators (INS). This Switched-Capacitor based Stimulator (SCS) aims to utilize charge storage and charge injection techniques to take advantage of both the efficiency of conventional voltage-controlled stimulators (VCS) and the safety and controllability of current-controlled stimulators (CCS). The discrete SCS prototype offers fine control over stimulation parameters such as voltage, current, pulse width, frequency, and active electrode channel via a LabVIEW graphical user interface (GUI) when connected to a PC through USB. Furthermore, the prototype utilizes a floating current sensor to provide charge-balanced biphasic stimulation and ensure safety. The stimulator was analyzed using an electrode-electrolyte interface (EEI) model as well as with a pair of pacing electrodes in saline. The primary motivation of this research is to test the feasibility and functionality of a safe, effective, and power-efficient switched-capacitor based stimulator for use in Deep Brain Stimulation. PMID:21095987

Improved 2-D resistivity imaging of features in covered karst terrain with arrays of implanted electrodes

Science.gov (United States)

Kiflu, H. G.; Kruse, S. E.; Harro, D.; Loke, M. H.; Wilkinson, P. B.

2013-12-01

Electrical resistivity tomography is commonly used to identify geologic features associated with sinkhole formation. In covered karst terrain, however, it can be difficult to resolve the depth to top of limestone with this method. This is due to the fact that array lengths, and hence depth of resolution, are often limited by residential or commercial lot dimensions in urban environments. Furthermore, the sediments mantling the limestone are often clay-rich and highly conductive. The resistivity method has limited sensitivity to resistive zones beneath conductive zones. This sensitivity can be improved significantly with electrodes implanted at depth in the cover sediments near the top of limestone. An array of deep electrodes is installed with direct push technology in the karst cover. When combined with a surface array in which each surface electrode is underlain by a deep electrode, the array geometry is similar to a borehole array turned on its side. This method, called the Multi-Electrode Resistivity Implant Technique (MERIT), offers the promise of significantly improved resolution of epikarst and cover collapse development zones in the overlying sediment, the limestone or at the sediment-bedrock interface in heterogeneous karst environments. With a non-traditional array design, the question of optimal array geometries arises. Optimizing array geometries is complicated by the fact that many plausible 4-electrode readings will produce negative apparent resistivity values, even in homogeneous terrain. Negative apparent resistivities cannot be used in inversions based on the logarithm of the apparent resistivity. New algorithms for seeking optimal array geometries have been developed by modifying the 'Compare R' method of Wilkinson and Loke. The optimized arrays show significantly improved resolution over basic arrays adapted from traditional 2D surface geometries. Several MERIT case study surveys have been conducted in covered karst in west-central Florida, with

Understanding and Overcoming the Challenges Posed by Electrode/Electrolyte Interfaces in Rechargeable Magnesium Batteries

Energy Technology Data Exchange (ETDEWEB)

Mizuno, Fuminori, E-mail: fuminori.mizuno@tema.toyota.com; Singh, Nikhilendra; Arthur, Timothy S.; Fanson, Paul T. [Toyota Research Institute of North America, Ann Arbor, MI (United States); Ramanathan, Mayandi [Department of Chemical and Biological Engineering, Center for Electrochemical Science and Engineering, Illinois Institute of Technology, Chicago, IL (United States); Department of Chemical Engineering, University of Washington, Seattle, WA (United States); Benmayza, Aadil; Prakash, Jai [Department of Chemical and Biological Engineering, Center for Electrochemical Science and Engineering, Illinois Institute of Technology, Chicago, IL (United States); Liu, Yi-Sheng; Glans, Per-Anders; Guo, Jinghua [Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA (United States)

2014-11-11

Magnesium (Mg) battery technologies have attracted attention as a high energy-density storage system due to the following advantages: (1) potentially high energy-density derived from a divalent nature, (2) low-cost due to the use of an earth-abundant metal, and (3) intrinsic safety aspect attributed to non-dendritic growth of Mg. However, these notable advantages are downplayed by undesirable battery reactions and related phenomena. As a result, there are only a few working rechargeable Mg battery systems. One of the root causes for undesirable behavior is the sluggish diffusion of Mg{sup 2+} inside a host lattice. Another root cause is the interfacial reaction at the electrode/electrolyte boundary. For the cathode/electrolyte interface, Mg{sup 2+} in the electrolyte needs a solvation–desolvation process prior to diffusion inside the cathode. Apart from the solid electrolyte interface (SEI) formed on the cathode, the divalent nature of Mg should cause kinetically slower solvation–desolvation processes than that of Li-ion systems. This would result in a high charge-transfer resistance and a larger overpotential. On the contrary, for the anode/electrolyte interface, the Mg deposition and dissolution process depends on the electrolyte nature and its compatibility with Mg metal. Also, the Mg metal/electrolyte interface tends to change over time, and with operating conditions, suggesting the presence of interfacial phenomena on the Mg metal. Hence, the solvation–desolvation process of Mg has to be considered with a possible SEI. Here, we focus on the anode/electrolyte interface in a Mg battery, and discuss the next steps to improve the battery performance.

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

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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.

Brain-computer interface after nervous system injury.

Science.gov (United States)

Burns, Alexis; Adeli, Hojjat; Buford, John A

2014-12-01

Brain-computer interface (BCI) has proven to be a useful tool for providing alternative communication and mobility to patients suffering from nervous system injury. BCI has been and will continue to be implemented into rehabilitation practices for more interactive and speedy neurological recovery. The most exciting BCI technology is evolving to provide therapeutic benefits by inducing cortical reorganization via neuronal plasticity. This article presents a state-of-the-art review of BCI technology used after nervous system injuries, specifically: amyotrophic lateral sclerosis, Parkinson's disease, spinal cord injury, stroke, and disorders of consciousness. Also presented is transcending, innovative research involving new treatment of neurological disorders. © The Author(s) 2014.

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.

Modulation of Posterior Alpha Activity by Spatial Attention Allows for Controlling A Continuous Brain-Computer Interface.

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Horschig, Jörn M; Oosterheert, Wouter; Oostenveld, Robert; Jensen, Ole

2015-11-01

Here we report that the modulation of alpha activity by covert attention can be used as a control signal in an online brain-computer interface, that it is reliable, and that it is robust. Subjects were instructed to orient covert visual attention to the left or right hemifield. We decoded the direction of attention from the magnetoencephalogram by a template matching classifier and provided the classification outcome to the subject in real-time using a novel graphical user interface. Training data for the templates were obtained from a Posner-cueing task conducted just before the BCI task. Eleven subjects participated in four sessions each. Eight of the subjects achieved classification rates significantly above chance level. Subjects were able to significantly increase their performance from the first to the second session. Individual patterns of posterior alpha power remained stable throughout the four sessions and did not change with increased performance. We conclude that posterior alpha power can successfully be used as a control signal in brain-computer interfaces. We also discuss several ideas for further improving the setup and propose future research based on solid hypotheses about behavioral consequences of modulating neuronal oscillations by brain computer interfacing.

Quantification of Hydrogen Concentrations in Surface and Interface Layers and Bulk Materials through Depth Profiling with Nuclear Reaction Analysis.

Science.gov (United States)

Wilde, Markus; Ohno, Satoshi; Ogura, Shohei; Fukutani, Katsuyuki; Matsuzaki, Hiroyuki

2016-03-29

Nuclear reaction analysis (NRA) via the resonant (1)H((15)N,αγ)(12)C reaction is a highly effective method of depth profiling that quantitatively and non-destructively reveals the hydrogen density distribution at surfaces, at interfaces, and in the volume of solid materials with high depth resolution. The technique applies a (15)N ion beam of 6.385 MeV provided by an electrostatic accelerator and specifically detects the (1)H isotope in depths up to about 2 μm from the target surface. Surface H coverages are measured with a sensitivity in the order of ~10(13) cm(-2) (~1% of a typical atomic monolayer density) and H volume concentrations with a detection limit of ~10(18) cm(-3) (~100 at. ppm). The near-surface depth resolution is 2-5 nm for surface-normal (15)N ion incidence onto the target and can be enhanced to values below 1 nm for very flat targets by adopting a surface-grazing incidence geometry. The method is versatile and readily applied to any high vacuum compatible homogeneous material with a smooth surface (no pores). Electrically conductive targets usually tolerate the ion beam irradiation with negligible degradation. Hydrogen quantitation and correct depth analysis require knowledge of the elementary composition (besides hydrogen) and mass density of the target material. Especially in combination with ultra-high vacuum methods for in-situ target preparation and characterization, (1)H((15)N,αγ)(12)C NRA is ideally suited for hydrogen analysis at atomically controlled surfaces and nanostructured interfaces. We exemplarily demonstrate here the application of (15)N NRA at the MALT Tandem accelerator facility of the University of Tokyo to (1) quantitatively measure the surface coverage and the bulk concentration of hydrogen in the near-surface region of a H2 exposed Pd(110) single crystal, and (2) to determine the depth location and layer density of hydrogen near the interfaces of thin SiO2 films on Si(100).

Evaluation of electrode position in deep brain stimulation by image fusion (MRI and CT)

Energy Technology Data Exchange (ETDEWEB)

Barnaure, I.; Lovblad, K.O.; Vargas, M.I. [Geneva University Hospital, Department of Neuroradiology, Geneva 14 (Switzerland); Pollak, P.; Horvath, J.; Boex, C.; Burkhard, P. [Geneva University Hospital, Department of Neurology, Geneva (Switzerland); Momjian, S. [Geneva University Hospital, Department of Neurosurgery, Geneva (Switzerland); Remuinan, J. [Geneva University Hospital, Department of Radiology, Geneva (Switzerland)

2015-09-15

Imaging has an essential role in the evaluation of correct positioning of electrodes implanted for deep brain stimulation (DBS). Although MRI offers superior anatomic visualization of target sites, there are safety concerns in patients with implanted material; imaging guidelines are inconsistent and vary. The fusion of postoperative CT with preoperative MRI images can be an alternative for the assessment of electrode positioning. The purpose of this study was to assess the accuracy of measurements realized on fused images (acquired without a stereotactic frame) using a manufacturer-provided software. Data from 23 Parkinson's disease patients who underwent bilateral electrode placement for subthalamic nucleus (STN) DBS were acquired. Preoperative high-resolution T2-weighted sequences at 3 T, and postoperative CT series were fused using a commercially available software. Electrode tip position was measured on the obtained images in three directions (in relation to the midline, the AC-PC line and an AC-PC line orthogonal, respectively) and assessed in relation to measures realized on postoperative 3D T1 images acquired at 1.5 T. Mean differences between measures carried out on fused images and on postoperative MRI lay between 0.17 and 0.97 mm. Fusion of CT and MRI images provides a safe and fast technique for postoperative assessment of electrode position in DBS. (orig.)

Comparison of four classification methods for brain-computer interface

Czech Academy of Sciences Publication Activity Database

Frolov, A.; Húsek, Dušan; Bobrov, P.

2011-01-01

Roč. 21, č. 2 (2011), s. 101-115 ISSN 1210-0552 R&D Projects: GA MŠk(CZ) 1M0567; GA ČR GA201/05/0079; GA ČR GAP202/10/0262 Institutional research plan: CEZ:AV0Z10300504 Keywords : brain computer interface * motor imagery * visual imagery * EEG pattern classification * Bayesian classification * Common Spatial Patterns * Common Tensor Discriminant Analysis Subject RIV: IN - Informatics, Computer Science Impact factor: 0.646, year: 2011

Ethical aspects of brain computer interfaces: a scoping review

OpenAIRE

Burwell, Sasha; Sample, Matthew; Racine, Eric

2017-01-01

Background Brain-Computer Interface (BCI) is a set of technologies that are of increasing interest to researchers. BCI has been proposed as assistive technology for individuals who are non-communicative or paralyzed, such as those with amyotrophic lateral sclerosis or spinal cord injury. The technology has also been suggested for enhancement and entertainment uses, and there are companies currently marketing BCI devices for those purposes (e.g., gaming) as well as health-related purposes (e.g...

Spectral Transfer Learning using Information Geometry for a User-Independent Brain-Computer Interface

OpenAIRE

Nicholas Roy Waytowich; Nicholas Roy Waytowich; Vernon Lawhern; Vernon Lawhern; Addison Bohannon; Addison Bohannon; Kenneth Ball; Brent Lance

2016-01-01

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry and recreation. However, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter- individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this p...

Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface

OpenAIRE

Waytowich, Nicholas R.; Lawhern, Vernon J.; Bohannon, Addison W.; Ball, Kenneth R.; Lance, Brent J.

2016-01-01

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this p...

fNIRS-based brain-computer interfaces: a review

Directory of Open Access Journals (Sweden)

Noman eNaseer

2015-01-01

Full Text Available A brain-computer interface (BCI is a communication system that allows the use of brain activity to control computers or other external devices. It can, by bypassing the peripheral nervous system, provide a means of communication for people suffering from severe motor disabilities or in a persistent vegetative state. In this paper, brain-signal generation tasks, noise removal methods, feature extraction/selection schemes, and classification techniques for fNIRS-based BCI are reviewed. The most common brain areas for fNIRS BCI are the primary motor cortex and the prefrontal cortex. In relation to the motor cortex, motor imagery tasks were preferred to motor execution tasks since possible proprioceptive feedback could be avoided. In relation to the prefrontal cortex, fNIRS showed a significant advantage due to no hair in detecting the cognitive tasks like mental arithmetic, music imagery, emotion induction, etc. In removing physiological noise in fNIRS data, band-pass filtering was mostly used. However, more advanced techniques like adaptive filtering, independent component analysis, multi optodes arrangement, etc. are being pursued to overcome the problem that a band-pass filter cannot be used when both brain and physiological signals occur within a close band. In extracting features related to the desired brain signal, the mean, variance, peak value, slope, skewness, and kurtosis of the noised-removed hemodynamic response were used. For classification, the linear discriminant analysis method provided simple but good performance among others: support vector machine, hidden Markov model, artificial neural network, etc. fNIRS will be more widely used to monitor the occurrence of neuro-plasticity after neuro-rehabilitation and neuro-stimulation. Technical breakthroughs in the future are expected via bundled-type probes, hybrid EEG-fNIRS BCI, and through the detection of initial dips.

SIMS of Organic Materials—Interface Location in Argon Gas Cluster Depth Profiles Using Negative Secondary Ions

Science.gov (United States)

Havelund, R.; Seah, M. P.; Tiddia, M.; Gilmore, I. S.

2018-02-01

A procedure has been established to define the interface position in depth profiles accurately when using secondary ion mass spectrometry and the negative secondary ions. The interface position varies strongly with the extent of the matrix effect and so depends on the secondary ion measured. Intensity profiles have been measured at both fluorenylmethyloxycarbonyl-uc(l)-pentafluorophenylalanine (FMOC) to Irganox 1010 and Irganox 1010 to FMOC interfaces for many secondary ions. These profiles show separations of the two interfaces that vary over some 10 nm depending on the secondary ion selected. The shapes of these profiles are strongly governed by matrix effects, slightly weakened by a long wavelength roughening. The matrix effects are separately measured using homogeneous, known mixtures of these two materials. Removal of the matrix and roughening effects give consistent compositional profiles for all ions that are described by an integrated exponentially modified Gaussian (EMG) profile. Use of a simple integrated Gaussian may lead to significant errors. The average interface positions in the compositional profiles are determined to standard uncertainties of 0.19 and 0.14 nm, respectively, using the integrated EMG function. Alternatively, and more simply, it is shown that interface positions and profiles may be deduced from data for several secondary ions with measured matrix factors by simply extrapolating the result to Ξ = 0. Care must be taken in quoting interface resolutions since those measured for predominantly Gaussian interfaces with Ξ above or below zero, without correction, appear significantly better than the true resolution.

Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training

DEFF Research Database (Denmark)

Bender, Thomas; Kjaer, Troels W.; Thomsen, Carsten E.

2013-01-01

This paper presents a novel and computationally simple tri-training based semi-supervised steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). It is implemented with autocorrelation-based features and a Naïve-Bayes classifier (NBC). The system uses nine characters...

Habit learning and brain-machine interfaces (BMI): a tribute to Valentino Braitenberg's "Vehicles".

Science.gov (United States)

Birbaumer, Niels; Hummel, Friedhelm C

2014-10-01

Brain-Machine Interfaces (BMI) allow manipulation of external devices and computers directly with brain activity without involvement of overt motor actions. The neurophysiological principles of such robotic brain devices and BMIs follow Hebbian learning rules as described and realized by Valentino Braitenberg in his book "Vehicles," in the concept of a "thought pump" residing in subcortical basal ganglia structures. We describe here the application of BMIs for brain communication in totally locked-in patients and argue that the thought pump may extinguish-at least partially-in those people because of extinction of instrumentally learned cognitive responses and brain responses. We show that Pavlovian semantic conditioning may allow brain communication even in the completely paralyzed who does not show response-effect contingencies. Principles of skill learning and habit acquisition as formulated by Braitenberg are the building blocks of BMIs and neuroprostheses.

Training leads to increased auditory brain-computer interface performance of end-users with motor impairments.

Science.gov (United States)

Halder, S; Käthner, I; Kübler, A

2016-02-01

Auditory brain-computer interfaces are an assistive technology that can restore communication for motor impaired end-users. Such non-visual brain-computer interface paradigms are of particular importance for end-users that may lose or have lost gaze control. We attempted to show that motor impaired end-users can learn to control an auditory speller on the basis of event-related potentials. Five end-users with motor impairments, two of whom with additional visual impairments, participated in five sessions. We applied a newly developed auditory brain-computer interface paradigm with natural sounds and directional cues. Three of five end-users learned to select symbols using this method. Averaged over all five end-users the information transfer rate increased by more than 1800% from the first session (0.17 bits/min) to the last session (3.08 bits/min). The two best end-users achieved information transfer rates of 5.78 bits/min and accuracies of 92%. Our results show that an auditory BCI with a combination of natural sounds and directional cues, can be controlled by end-users with motor impairment. Training improves the performance of end-users to the level of healthy controls. To our knowledge, this is the first time end-users with motor impairments controlled an auditory brain-computer interface speller with such high accuracy and information transfer rates. Further, our results demonstrate that operating a BCI with event-related potentials benefits from training and specifically end-users may require more than one session to develop their full potential. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Cortical and subcortical mechanisms of brain-machine interfaces.

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Marchesotti, Silvia; Martuzzi, Roberto; Schurger, Aaron; Blefari, Maria Laura; Del Millán, José R; Bleuler, Hannes; Blanke, Olaf

2017-06-01

Technical advances in the field of Brain-Machine Interfaces (BMIs) enable users to control a variety of external devices such as robotic arms, wheelchairs, virtual entities and communication systems through the decoding of brain signals in real time. Most BMI systems sample activity from restricted brain regions, typically the motor and premotor cortex, with limited spatial resolution. Despite the growing number of applications, the cortical and subcortical systems involved in BMI control are currently unknown at the whole-brain level. Here, we provide a comprehensive and detailed report of the areas active during on-line BMI control. We recorded functional magnetic resonance imaging (fMRI) data while participants controlled an EEG-based BMI inside the scanner. We identified the regions activated during BMI control and how they overlap with those involved in motor imagery (without any BMI control). In addition, we investigated which regions reflect the subjective sense of controlling a BMI, the sense of agency for BMI-actions. Our data revealed an extended cortical-subcortical network involved in operating a motor-imagery BMI. This includes not only sensorimotor regions but also the posterior parietal cortex, the insula and the lateral occipital cortex. Interestingly, the basal ganglia and the anterior cingulate cortex were involved in the subjective sense of controlling the BMI. These results inform basic neuroscience by showing that the mechanisms of BMI control extend beyond sensorimotor cortices. This knowledge may be useful for the development of BMIs that offer a more natural and embodied feeling of control for the user. Hum Brain Mapp 38:2971-2989, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

European public deliberation on brain machine interface technology: five convergence seminars.

Science.gov (United States)

Jebari, Karim; Hansson, Sven-Ove

2013-09-01

We present a novel procedure to engage the public in ethical deliberations on the potential impacts of brain machine interface technology. We call this procedure a convergence seminar, a form of scenario-based group discussion that is founded on the idea of hypothetical retrospection. The theoretical background of this procedure and the results of five seminars are presented.

Electrodes for Semiconductor Gas Sensors

Science.gov (United States)

Lee, Sung Pil

2017-01-01

The electrodes of semiconductor gas sensors are important in characterizing sensors based on their sensitivity, selectivity, reversibility, response time, and long-term stability. The types and materials of electrodes used for semiconductor gas sensors are analyzed. In addition, the effect of interfacial zones and surface states of electrode–semiconductor interfaces on their characteristics is studied. This study describes that the gas interaction mechanism of the electrode–semiconductor interfaces should take into account the interfacial zone, surface states, image force, and tunneling effect. PMID:28346349

The effect of Quinpirol and Sulpiride on the brain activity waves in conscious and aneasthetized rat

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Komaki AR

1998-06-01

Full Text Available Brain's waves are produced by spontaneous activity of neurons. These waves are changed by neurotransmitters in the central nervous system (CNS. Concentration of these neurotransmitters can be changed by various drugs and total power of brain waves also increase or decrease by these drugs. In this research effect of Quinpirol and Sulpiride on the brain waves was investigated. Male wistar rats (weight 190-230 were aneasthetized with thiopental and two holes were made into the frontal and occipital area and two Ag/AgCl electrodes were fixed into these holes. One week after recovery, two electrodes were connected to the physiograph and the results were analyzed before and after intraperitoneal and intracerebroventricular (ICV injection of drugs by PC computer. Our results showed that intraperitoneal administration (5 mg/kg of diazepam reduced the depth of anesthesia. Conversely, intracerebroventricular injection of sulpiride increased the depth of anesthesia which was manifested by an increase in relative power of delta waves and reduction of relative power of alpha waves. This drug had a biphasic effect on EEG, at high doses in increased the depth of aneasthesia and total sleep. Wehteas depth of anesthesia was decreased at low dose. Simutanuos administration of sulpiride and quinpirole produced an effect on EEG similar to diazepam. As a result, biphasic effect of D2 agonist and antagonist drugs on brain waves are due to nonspecific action of these drugs on these receptors and this effect may be produced by other mechanisms

Performance of Brain-computer Interfacing based on tactile selective sensation and motor imagery

DEFF Research Database (Denmark)

Yao, Lin; Sheng, Xinjun; Mrachacz-Kersting, Natalie

2018-01-01

We proposed a multi-class tactile brain-computer interface that utilizes stimulus-induced oscillatory dynamics. It was hypothesized that somatosensory attention can modulate tactile induced oscillation changes, which can decode different sensation attention tasks. Subjects performed four tactile...

Independent Mobility Achieved through a Wireless Brain-Machine Interface.

Directory of Open Access Journals (Sweden)

Camilo Libedinsky

Full Text Available Individuals with tetraplegia lack independent mobility, making them highly dependent on others to move from one place to another. Here, we describe how two macaques were able to use a wireless integrated system to control a robotic platform, over which they were sitting, to achieve independent mobility using the neuronal activity in their motor cortices. The activity of populations of single neurons was recorded using multiple electrode arrays implanted in the arm region of primary motor cortex, and decoded to achieve brain control of the platform. We found that free-running brain control of the platform (which was not equipped with any machine intelligence was fast and accurate, resembling the performance achieved using joystick control. The decoding algorithms can be trained in the absence of joystick movements, as would be required for use by tetraplegic individuals, demonstrating that the non-human primate model is a good pre-clinical model for developing such a cortically-controlled movement prosthetic. Interestingly, we found that the response properties of some neurons differed greatly depending on the mode of control (joystick or brain control, suggesting different roles for these neurons in encoding movement intention and movement execution. These results demonstrate that independent mobility can be achieved without first training on prescribed motor movements, opening the door for the implementation of this technology in persons with tetraplegia.

Detection of User Independent Single Trial ERPs in Brain Computer Interfaces: An Adaptive Spatial Filtering Approach

DEFF Research Database (Denmark)

Leza, Cristina; Puthusserypady, Sadasivan

2017-01-01

Brain Computer Interfaces (BCIs) use brain signals to communicate with the external world. The main challenges to address are speed, accuracy and adaptability. Here, a novel algorithm for P300 based BCI spelling system is presented, specifically suited for single-trial detection of Event...

Control of a nursing bed based on a hybrid brain-computer interface.

Science.gov (United States)

Nengneng Peng; Rui Zhang; Haihua Zeng; Fei Wang; Kai Li; Yuanqing Li; Xiaobin Zhuang

2016-08-01

In this paper, we propose an intelligent nursing bed system which is controlled by a hybrid brain-computer interface (BCI) involving steady-state visual evoked potential (SSVEP) and P300. Specifically, the hybrid BCI includes an asynchronous brain switch based on SSVEP and P300, and a P300-based BCI. The brain switch is used to turn on/off the control system of the electric nursing bed through idle/control state detection, whereas the P300-based BCI is for operating the nursing bed. At the beginning, the user may focus on one group of flashing buttons in the graphic user interface (GUI) of the brain switch, which can simultaneously evoke SSVEP and P300, to switch on the control system. Here, the combination of SSVEP and P300 is used for improving the performance of the brain switch. Next, the user can control the nursing bed using the P300-based BCI. The GUI of the P300-based BCI includes 10 flashing buttons, which correspond to 10 functional operations, namely, left-side up, left-side down, back up, back down, bedpan open, bedpan close, legs up, legs down, right-side up, and right-side down. For instance, he/she can focus on the flashing button "back up" in the GUI of the P300-based BCI to activate the corresponding control such that the nursing bed is adjusted up. Eight healthy subjects participated in our experiment, and obtained an average accuracy of 93.75% and an average false positive rate (FPR) of 0.15 event/min. The effectiveness of our system was thus demonstrated.

Invasive brain-machine interfaces: a survey of paralyzed patients’ attitudes, knowledge and methods of information retrieval

Science.gov (United States)

Lahr, Jacob; Schwartz, Christina; Heimbach, Bernhard; Aertsen, Ad; Rickert, Jörn; Ball, Tonio

2015-08-01

Objective. Brain-machine interfaces (BMI) are an emerging therapeutic option that can allow paralyzed patients to gain control over assistive technology devices (ATDs). BMI approaches can be broadly classified into invasive (based on intracranially implanted electrodes) and noninvasive (based on skin electrodes or extracorporeal sensors). Invasive BMIs have a favorable signal-to-noise ratio, and thus allow for the extraction of more information than noninvasive BMIs, but they are also associated with the risks related to neurosurgical device implantation. Current noninvasive BMI approaches are typically concerned, among other issues, with long setup times and/or intensive training. Recent studies have investigated the attitudes of paralyzed patients eligible for BMIs, particularly patients affected by amyotrophic lateral sclerosis (ALS). These studies indicate that paralyzed patients are indeed interested in BMIs. Little is known, however, about the degree of knowledge among paralyzed patients concerning BMI approaches or about how patients retrieve information on ATDs. Furthermore, it is not yet clear if paralyzed patients would accept intracranial implantation of BMI electrodes with the premise of decoding improvements, and what the attitudes of a broader range of patients with diseases such as stroke or spinal cord injury are towards this new kind of treatment. Approach. Using a questionnaire, we surveyed 131 paralyzed patients for their opinions on invasive BMIs and their attitude toward invasive BMI treatment options. Main results. The majority of the patients knew about and had a positive attitude toward invasive BMI approaches. The group of ALS patients was especially open to the concept of BMIs. The acceptance of invasive BMI technology depended on the improvements expected from the technology. Furthermore, the survey revealed that for paralyzed patients, the Internet is an important source of information on ATDs. Significance. Websites tailored to

Toward FRP-Based Brain-Machine Interfaces-Single-Trial Classification of Fixation-Related Potentials.

Directory of Open Access Journals (Sweden)

Andrea Finke

Full Text Available The co-registration of eye tracking and electroencephalography provides a holistic measure of ongoing cognitive processes. Recently, fixation-related potentials have been introduced to quantify the neural activity in such bi-modal recordings. Fixation-related potentials are time-locked to fixation onsets, just like event-related potentials are locked to stimulus onsets. Compared to existing electroencephalography-based brain-machine interfaces that depend on visual stimuli, fixation-related potentials have the advantages that they can be used in free, unconstrained viewing conditions and can also be classified on a single-trial level. Thus, fixation-related potentials have the potential to allow for conceptually different brain-machine interfaces that directly interpret cortical activity related to the visual processing of specific objects. However, existing research has investigated fixation-related potentials only with very restricted and highly unnatural stimuli in simple search tasks while participant's body movements were restricted. We present a study where we relieved many of these restrictions while retaining some control by using a gaze-contingent visual search task. In our study, participants had to find a target object out of 12 complex and everyday objects presented on a screen while the electrical activity of the brain and eye movements were recorded simultaneously. Our results show that our proposed method for the classification of fixation-related potentials can clearly discriminate between fixations on relevant, non-relevant and background areas. Furthermore, we show that our classification approach generalizes not only to different test sets from the same participant, but also across participants. These results promise to open novel avenues for exploiting fixation-related potentials in electroencephalography-based brain-machine interfaces and thus providing a novel means for intuitive human-machine interaction.

Brain-computer interface on the basis of EEG system Encephalan

Science.gov (United States)

Maksimenko, Vladimir; Badarin, Artem; Nedaivozov, Vladimir; Kirsanov, Daniil; Hramov, Alexander

2018-04-01

We have proposed brain-computer interface (BCI) for the estimation of the brain response on the presented visual tasks. Proposed BCI is based on the EEG recorder Encephalan-EEGR-19/26 (Medicom MTD, Russia) supplemented by a special home-made developed acquisition software. BCI is tested during experimental session while subject is perceiving the bistable visual stimuli and classifying them according to the interpretation. We have subjected the participant to the different external conditions and observed the significant decrease in the response, associated with the perceiving the bistable visual stimuli, during the presence of distraction. Based on the obtained results we have proposed possibility to use of BCI for estimation of the human alertness during solving the tasks required substantial visual attention.

Are we there yet? Evaluating commercial grade brain-computer interface for control of computer applications by individuals with cerebral palsy.

Science.gov (United States)

Taherian, Sarvnaz; Selitskiy, Dmitry; Pau, James; Claire Davies, T

2017-02-01

Using a commercial electroencephalography (EEG)-based brain-computer interface (BCI), the training and testing protocol for six individuals with spastic quadriplegic cerebral palsy (GMFCS and MACS IV and V) was evaluated. A customised, gamified training paradigm was employed. Over three weeks, the participants spent two sessions exploring the system, and up to six sessions playing the game which focussed on EEG feedback of left and right arm motor imagery. The participants showed variable inconclusive results in the ability to produce two distinct EEG patterns. Participant performance was influenced by physical illness, motivation, fatigue and concentration. The results from this case study highlight the infancy of BCIs as a form of assistive technology for people with cerebral palsy. Existing commercial BCIs are not designed according to the needs of end-users. Implications for Rehabilitation Mood, fatigue, physical illness and motivation influence the usability of a brain-computer interface. Commercial brain-computer interfaces are not designed for practical assistive technology use for people with cerebral palsy. Practical brain-computer interface assistive technologies may need to be flexible to suit individual needs.

Handbook of reference electrodes

CERN Document Server

Inzelt, György; Scholz, Fritz

2013-01-01

Reference Electrodes are a crucial part of any electrochemical system, yet an up-to-date and comprehensive handbook is long overdue. Here, an experienced team of electrochemists provides an in-depth source of information and data for the proper choice and construction of reference electrodes. This includes all kinds of applications such as aqueous and non-aqueous solutions, ionic liquids, glass melts, solid electrolyte systems, and membrane electrodes. Advanced technologies such as miniaturized, conducting-polymer-based, screen-printed or disposable reference electrodes are also covered. Essen

Bigger data for big data: from Twitter to brain-computer interfaces.

Science.gov (United States)

Roesch, Etienne B; Stahl, Frederic; Gaber, Mohamed Medhat

2014-02-01

We are sympathetic with Bentley et al.'s attempt to encompass the wisdom of crowds in a generative model, but posit that a successful attempt at using big data will include more sensitive measurements, more varied sources of information, and will also build from the indirect information available through technology, from ancillary technical features to data from brain-computer interfaces.

Tactile event-related potentials in amyotrophic lateral sclerosis (ALS): Implications for brain-computer interface.

Science.gov (United States)

Silvoni, S; Konicar, L; Prats-Sedano, M A; Garcia-Cossio, E; Genna, C; Volpato, C; Cavinato, M; Paggiaro, A; Veser, S; De Massari, D; Birbaumer, N

2016-01-01

We investigated neurophysiological brain responses elicited by a tactile event-related potential paradigm in a sample of ALS patients. Underlying cognitive processes and neurophysiological signatures for brain-computer interface (BCI) are addressed. We stimulated the palm of the hand in a group of fourteen ALS patients and a control group of ten healthy participants and recorded electroencephalographic signals in eyes-closed condition. Target and non-target brain responses were analyzed and classified offline. Classification errors served as the basis for neurophysiological brain response sub-grouping. A combined behavioral and quantitative neurophysiological analysis of sub-grouped data showed neither significant between-group differences, nor significant correlations between classification performance and the ALS patients' clinical state. Taking sequential effects of stimuli presentation into account, analyses revealed mean classification errors of 19.4% and 24.3% in healthy participants and ALS patients respectively. Neurophysiological correlates of tactile stimuli presentation are not altered by ALS. Tactile event-related potentials can be used to monitor attention level and task performance in ALS and may constitute a viable basis for future BCIs. Implications for brain-computer interface implementation of the proposed method for patients in critical conditions, such as the late stage of ALS and the (completely) locked-in state, are discussed. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

The electrode kinetics of the evolution and dissolution of oxygen at the urania-zirconia interfaces

International Nuclear Information System (INIS)

Badwal, S.P.S.; Bevan, D.J.M.; Bockris, J.O'M.

1980-01-01

In order to assess the potential of urania-yttria fluorite-type solid solutions as electrodes for high-temperature electrolysis of steam, oxygen evolution and dissolution reactions have been studied at the (Usub(0.7)Ysub(0.3))Osub (2+x)/YSZ interface. A current-interruption technique was used to separate overpotential and resistive potential drop. In oxygen and air the overpotential-current curves obey the Tafel law, suggesting that a charge-transfer process is rate determining. Activation energies of 120 kJ mole -1 and 165 kJ mole -1 were obtained for the cathodic reaction in oxygen and air respectively. The capacitance obtained from galvanostatic transients varied with potential, temperature, and oxygen partial pressure. The average value of n, the number of electrons involved in the overall charge-transfer reaction, was determined to be 4.01 from reversible potential measurements. The overpotential losses are small for porous electrodes at high psub(O 2 ). A mechanism for the oxygen transfer reaction has been proposed and its limitations discussed. (author)

Brain-Computer Interface Epoc Emotiv a potenciál jeho komerčního využití

OpenAIRE

Vencelides, David

2012-01-01

This work is focused on Brain Computer Interface. Specifically, the device EPOC Emotiv. The first part focuses on the introduction to the topic Brain Computer Interface. Definition of terms, a brief history and ways to measure brain activity. The second part deals with specific BCI products that are available on the consumer market open for sale at a price accessible to the ordinary customer. The third part focuses on the specific BCI product EPOC Emotiv In this part the device is introduced ...

[Brain-Computer Interface: the First Clinical Experience in Russia].

Science.gov (United States)

Mokienko, O A; Lyukmanov, R Kh; Chernikova, L A; Suponeva, N A; Piradov, M A; Frolov, A A

2016-01-01

Motor imagery is suggested to stimulate the same plastic mechanisms in the brain as a real movement. The brain-computer interface (BCI) controls motor imagery by converting EEG during this process into the commands for an external device. This article presents the results of two-stage study of the clinical use of non-invasive BCI in the rehabilitation of patients with severe hemiparesis caused by focal brain damage. It was found that the ability to control BCI did not depend on the duration of a disease, brain lesion localization and the degree of neurological deficit. The first step of the study involved 36 patients; it showed that the efficacy of rehabilitation was higher in the group with the use of BCI (the score on the Action Research Arm Test (ARAT) improved from 1 [0; 2] to 5 [0; 16] points, p = 0.012; no significant improvement was observed in control group). The second step of the study involved 19 patients; the complex BCI-exoskeleton (i.e. with the kinesthetic feedback) was used for motor imagery trainings. The improvement of the motor function of hands was proved by ARAT (the score improved from 2 [0; 37] to 4 [1; 45:5] points, p = 0.005) and Fugl-Meyer scale (from 72 [63; 110 ] to 79 [68; 115] points, p = 0.005).

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

A critical review of cell culture strategies for modelling intracortical brain implant material reactions.

Science.gov (United States)

Gilmour, A D; Woolley, A J; Poole-Warren, L A; Thomson, C E; Green, R A

2016-06-01

The capacity to predict in vivo responses to medical devices in humans currently relies greatly on implantation in animal models. Researchers have been striving to develop in vitro techniques that can overcome the limitations associated with in vivo approaches. This review focuses on a critical analysis of the major in vitro strategies being utilized in laboratories around the world to improve understanding of the biological performance of intracortical, brain-implanted microdevices. Of particular interest to the current review are in vitro models for studying cell responses to penetrating intracortical devices and their materials, such as electrode arrays used for brain computer interface (BCI) and deep brain stimulation electrode probes implanted through the cortex. A background on the neural interface challenge is presented, followed by discussion of relevant in vitro culture strategies and their advantages and disadvantages. Future development of 2D culture models that exhibit developmental changes capable of mimicking normal, postnatal development will form the basis for more complex accurate predictive models in the future. Although not within the scope of this review, innovations in 3D scaffold technologies and microfluidic constructs will further improve the utility of in vitro approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

SFG study on potential-dependent structure of water at Pt electrode/electrolyte solution interface

Energy Technology Data Exchange (ETDEWEB)

Noguchi, Hidenori; Okada, Tsubasa; Uosaki, Kohei [Physical Chemistry Laboratory, Division of Chemistry, Graduate School of Science, Hokkaido University, Sapporo 060-0810 (Japan)

2008-10-01

Structure of water at Pt/electrolyte solution interface was investigated by sum frequency generation (SFG) spectroscopy. Two broad peaks were observed in OH stretching region at ca. 3200 cm{sup -1} and ca. 3400 cm{sup -1}, which are known to be due to the symmetric OH stretching (U{sub 1}) of tetrahedrally coordinated, i.e., strongly hydrogen bonded 'ice-like' water, and the asymmetric OH stretching (U{sub 3}) of water molecules in a more random arrangement, i.e., weakly hydrogen bonded 'liquid-like' water, respectively. The SFG intensity strongly depended on electrode potential. Several possibilities are suggested for the potential dependence of the SFG intensity. (author)

A Review of EEG-Based Brain-Computer Interfaces as Access Pathways for Individuals with Severe Disabilities

Science.gov (United States)

Moghimi, Saba; Kushki, Azadeh; Guerguerian, Anne Marie; Chau, Tom

2013-01-01

Electroencephalography (EEG) is a non-invasive method for measuring brain activity and is a strong candidate for brain-computer interface (BCI) development. While BCIs can be used as a means of communication for individuals with severe disabilities, the majority of existing studies have reported BCI evaluations by able-bodied individuals.…

EXPERIMENTAL AND THEORETICAL FOUNDATIONS AND PRACTICAL IMPLEMENTATION OF TECHNOLOGY BRAIN-COMPUTER INTERFACE

Directory of Open Access Journals (Sweden)

A. Ya. Kaplan

2013-01-01

Full Text Available Technology brain-computer interface (BCI allow saperson to learn how to control external devices via thevoluntary regulation of own EEG directly from the brain without the involvement in the process of nerves and muscles. At the beginning the main goal of BCI was to replace or restore motor function to people disabled by neuromuscular disorders. Currently, the task of designing the BCI increased significantly, more capturing different aspects of life a healthy person. This article discusses the theoretical, experimental and technological base of BCI development and systematized critical fields of real implementation of these technologies.

Addition of visual noise boosts evoked potential-based brain-computer interface.

Science.gov (United States)

Xie, Jun; Xu, Guanghua; Wang, Jing; Zhang, Sicong; Zhang, Feng; Li, Yeping; Han, Chengcheng; Li, Lili

2014-05-14

Although noise has a proven beneficial role in brain functions, there have not been any attempts on the dedication of stochastic resonance effect in neural engineering applications, especially in researches of brain-computer interfaces (BCIs). In our study, a steady-state motion visual evoked potential (SSMVEP)-based BCI with periodic visual stimulation plus moderate spatiotemporal noise can achieve better offline and online performance due to enhancement of periodic components in brain responses, which was accompanied by suppression of high harmonics. Offline results behaved with a bell-shaped resonance-like functionality and 7-36% online performance improvements can be achieved when identical visual noise was adopted for different stimulation frequencies. Using neural encoding modeling, these phenomena can be explained as noise-induced input-output synchronization in human sensory systems which commonly possess a low-pass property. Our work demonstrated that noise could boost BCIs in addressing human needs.

Challenges in clinical applications of brain computer interfaces in individuals with spinal cord injury

OpenAIRE

Rupp, Rüdiger

2014-01-01

Brain computer interfaces (BCIs) are devices that measure brain activities and translate them into control signals used for a variety of applications. Among them are systems for communication, environmental control, neuroprostheses, exoskeletons, or restorative therapies. Over the last years the technology of BCIs has reached a level of matureness allowing them to be used not only in research experiments supervised by scientists, but also in clinical routine with patients with neurological im...

Towards Effective Non-Invasive Brain-Computer Interfaces Dedicated to Gait Rehabilitation Systems

Directory of Open Access Journals (Sweden)

Thierry Castermans

2013-12-01

Full Text Available In the last few years, significant progress has been made in the field of walk rehabilitation. Motor cortex signals in bipedal monkeys have been interpreted to predict walk kinematics. Epidural electrical stimulation in rats and in one young paraplegic has been realized to partially restore motor control after spinal cord injury. However, these experimental trials are far from being applicable to all patients suffering from motor impairments. Therefore, it is thought that more simple rehabilitation systems are desirable in the meanwhile. The goal of this review is to describe and summarize the progress made in the development of non-invasive brain-computer interfaces dedicated to motor rehabilitation systems. In the first part, the main principles of human locomotion control are presented. The paper then focuses on the mechanisms of supra-spinal centers active during gait, including results from electroencephalography, functional brain imaging technologies [near-infrared spectroscopy (NIRS, functional magnetic resonance imaging (fMRI, positron-emission tomography (PET, single-photon emission-computed tomography (SPECT] and invasive studies. The first brain-computer interface (BCI applications to gait rehabilitation are then presented, with a discussion about the different strategies developed in the field. The challenges to raise for future systems are identified and discussed. Finally, we present some proposals to address these challenges, in order to contribute to the improvement of BCI for gait rehabilitation.

Wearable ear EEG for brain interfacing

Science.gov (United States)

Schroeder, Eric D.; Walker, Nicholas; Danko, Amanda S.

2017-02-01

Brain-computer interfaces (BCIs) measuring electrical activity via electroencephalogram (EEG) have evolved beyond clinical applications to become wireless consumer products. Typically marketed for meditation and neu- rotherapy, these devices are limited in scope and currently too obtrusive to be a ubiquitous wearable. Stemming from recent advancements made in hearing aid technology, wearables have been shrinking to the point that the necessary sensors, circuitry, and batteries can be fit into a small in-ear wearable device. In this work, an ear-EEG device is created with a novel system for artifact removal and signal interpretation. The small, compact, cost-effective, and discreet device is demonstrated against existing consumer electronics in this space for its signal quality, comfort, and usability. A custom mobile application is developed to process raw EEG from each device and display interpreted data to the user. Artifact removal and signal classification is accomplished via a combination of support matrix machines (SMMs) and soft thresholding of relevant statistical properties.

The Asilomar Survey: Stakeholders' Opinions on Ethical Issues Related to Brain-Computer Interfacing

NARCIS (Netherlands)

Nijboer, Femke; Clausen, Jens; Allison, Brendan Z.; Haselager, Pim

2013-01-01

Brain-Computer Interface (BCI) research and (future) applications raise important ethical issues that need to be addressed to promote societal acceptance and adequate policies. Here we report on a survey we conducted among 145 BCI researchers at the 4th International BCI conference, which took place

The Asilomar Survey: Stakeholders’ Opinions on Ethical Issues Related to Brain-Computer Interfacing

NARCIS (Netherlands)

Nijboer, F.; Clausen, J.; Allison, B.Z.; Haselager, W.F.G.

2013-01-01

Brain-Computer Interface (BCI) research and (future) applications raise important ethical issues that need to be addressed to promote societal acceptance and adequate policies. Here we report on a survey we conducted among 145 BCI researchers at the 4th International BCI conference, which took place

Helium Ion Microscopy of proton exchange membrane fuel cell electrode structures

DEFF Research Database (Denmark)

Chiriaev, Serguei; Dam Madsen, Nis; Rubahn, Horst-Günter

2017-01-01

electrode interface structure dependence on ionomer content, systematically studied by Helium Ion Microscopy (HIM). A special focus was on acquiring high resolution images of the electrode structure and avoiding interface damage from irradiation and tedious sample preparation. HIM demonstrated its....... In the hot-pressed electrodes, we found more closed contact between the electrode components, reduced particle size, polymer coalescence and formation of nano-sized polymer fiber architecture between the particles. Keywords: proton exchange membrane fuel cells (PEMFCs); Helium Ion Microscopy (HIM...

Brain-computer interfaces for EEG neurofeedback: peculiarities and solutions.

Science.gov (United States)

Huster, René J; Mokom, Zacharais N; Enriquez-Geppert, Stefanie; Herrmann, Christoph S

2014-01-01

Neurofeedback training procedures designed to alter a person's brain activity have been in use for nearly four decades now and represent one of the earliest applications of brain-computer interfaces (BCI). The majority of studies using neurofeedback technology relies on recordings of the electroencephalogram (EEG) and applies neurofeedback in clinical contexts, exploring its potential as treatment for psychopathological syndromes. This clinical focus significantly affects the technology behind neurofeedback BCIs. For example, in contrast to other BCI applications, neurofeedback BCIs usually rely on EEG-derived features with only a minimum of additional processing steps being employed. Here, we highlight the peculiarities of EEG-based neurofeedback BCIs and consider their relevance for software implementations. Having reviewed already existing packages for the implementation of BCIs, we introduce our own solution which specifically considers the relevance of multi-subject handling for experimental and clinical trials, for example by implementing ready-to-use solutions for pseudo-/sham-neurofeedback. © 2013.

Reduction of methanol crossover by thin cracked metal barriers at the interface between membrane and electrode in direct methanol fuel cells

Science.gov (United States)

Kim, Sungjun; Jang, Segeun; Kim, Sang Moon; Ahn, Chi-Yeong; Hwang, Wonchan; Cho, Yong-Hun; Sung, Yung-Eun; Choi, Mansoo

2017-09-01

This work reports the successful reduction in methanol crossover by creating a thin cracked metal barrier at the interface between a Nafion® membrane and an electrode in direct methanol fuel cells (DMFCs). The cracks are generated by simple mechanical stretching of a metal deposited Nafion® membrane as a result of the elastic mismatch between the two attached surfaces. The cracked metal barriers with varying strains (∼0.5 and ∼1.0) are investigated and successfully incorporated into the DMFC. Remarkably, the membrane electrode assembly with the thin metal crack exhibits comparable ohmic resistance as well as reduction of methanol crossover, which enhanced the device performance.

Investigations of the polymer/magnetic interface of organic spin-valves

Energy Technology Data Exchange (ETDEWEB)

Morley, N.A., E-mail: n.a.morley@sheffield.ac.uk [Department of Materials Science and Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD (United Kingdom); Dost, R.; Lingam, A.S.V. [Department of Materials Science and Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD (United Kingdom); Barlow, A.J. [National EPSRC XPS Users’ Service, School of Mechanical and Systems Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)

2015-12-30

Graphical abstract: - Highlights: • Metal carbide and sulphide species are detected at a polymer–magnetic interface. • Top magnetic electrodes on P3HT have uniaxial anisotropy. • Top magnetic electrodes on PBTTT are isotropic. - Abstract: This work investigates the top interface of an organic spin-valve, to determine the interactions between the polymer and top magnetic electrode. The polymers studied are regio-regular poly(3-hexylthiophene) (RR-P3HT) and poly(2,5-bis(3-hexadecylthiophen-2-yl)thieno[3,2-b]thiophene (PBTTT) and the magnetic top electrodes are NiFe and Fe. X-ray photoelectron spectroscopy (XPS) is used to determine the bonding at the interface, along with the extent of how oxidised the magnetic layers are, while atomic force microscopy (AFM) is used to determine the surface roughness. A magneto-optic Kerr effect (MOKE) magnetometer is used to study the magnetic properties of the top electrode. It is shown that at the organic–magnetic interface the magnetic atoms interact with the polymer, as metallic–sulphide and metallic-carbide species are present at the interface. It is also shown that the structure of the polymer influences the anisotropy of the magnetic electrode, such that the magnetic electrodes grown on RR-P3HT have uniaxial anisotropy, while those grown on PBTTT are isotropic.

Hermetic electronic packaging of an implantable brain-machine-interface with transcutaneous optical data communication.

Science.gov (United States)

Schuettler, Martin; Kohler, Fabian; Ordonez, Juan S; Stieglitz, Thomas

2012-01-01

Future brain-computer-interfaces (BCIs) for severely impaired patients are implanted to electrically contact the brain tissue. Avoiding percutaneous cables requires amplifier and telemetry electronics to be implanted too. We developed a hermetic package that protects the electronic circuitry of a BCI from body moisture while permitting infrared communication through the package wall made from alumina ceramic. The ceramic package is casted in medical grade silicone adhesive, for which we identified MED2-4013 as a promising candidate.

Electrical characteristic of the titanium mesh electrode for transcutaneous intrabody communication to monitor implantable artificial organs.

Science.gov (United States)

Okamoto, Eiji; Kikuchi, Sakiko; Mitamura, Yoshinori

2016-09-01

We have developed a tissue-inducing electrode using titanium mesh to obtain mechanically and electrically stable contact with the tissue for a new transcutaneous communication system using the human body as a conductive medium. In this study, we investigated the electrical properties of the titanium mesh electrode by measuring electrode-tissue interface resistance in vivo. The titanium mesh electrode (Hi-Lex Co., Zellez, Hyogo, Japan) consisted of titanium fibers (diameter of 50 μm), and it has an average pore size of 200 μm and 87 % porosity. The titanium mesh electrode has a diameter of 5 mm and thickness of 1.5 mm. Three titanium mesh electrodes were implanted separately into the dorsal region of the rat. We measured the electrode-electrode impedance using an LCR meter for 12 weeks, and we calculated the tissue resistivity and electrode-tissue interface resistance. The electrode-tissue interface resistance of the titanium mesh electrode decreased slightly until the third POD and then continuously increased to 75 Ω. The electrode-tissue interface resistance of the titanium mesh electrode is stable and it has lower electrode-tissue interface resistance than that of a titanium disk electrode. The extracted titanium mesh electrode after 12 weeks implantation was fixed in 10 % buffered formalin solution and stained with hematoxylin-eosin. Light microscopic observation showed that the titanium mesh electrode was filled with connective tissue, inflammatory cells and fibroblasts with some capillaries in the pores of the titanium mesh. The results indicate that the titanium mesh electrode is a promising electrode for the new transcutaneous communication system.

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

International Nuclear Information System (INIS)

Gutierrez, David

2008-01-01

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEG data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation

Mining multi-channel EEG for its information content: An ANN-based method for a brain-computer interface

DEFF Research Database (Denmark)

Peters, B.O.; Pfurtscheller, G.; Flyvbjerg, H.

1998-01-01

. This high recognition rate makes the classifier suitable for a so-called 'Brain-Computer Interface', a system that allows one to control a computer, or another device, with ones brain waves. Our classifier Laplace filters the EEG spatially, but makes use of its entire frequency range, and automatically...

The Berlin Brain-Computer Interface: Progress Beyond Communication and Control.

Science.gov (United States)

Blankertz, Benjamin; Acqualagna, Laura; Dähne, Sven; Haufe, Stefan; Schultze-Kraft, Matthias; Sturm, Irene; Ušćumlic, Marija; Wenzel, Markus A; Curio, Gabriel; Müller, Klaus-Robert

2016-01-01

The combined effect of fundamental results about neurocognitive processes and advancements in decoding mental states from ongoing brain signals has brought forth a whole range of potential neurotechnological applications. In this article, we review our developments in this area and put them into perspective. These examples cover a wide range of maturity levels with respect to their applicability. While we assume we are still a long way away from integrating Brain-Computer Interface (BCI) technology in general interaction with computers, or from implementing neurotechnological measures in safety-critical workplaces, results have already now been obtained involving a BCI as research tool. In this article, we discuss the reasons why, in some of the prospective application domains, considerable effort is still required to make the systems ready to deal with the full complexity of the real world.

The Berlin Brain-Computer Interface: Progress Beyond Communication and Control

Directory of Open Access Journals (Sweden)

Benjamin Blankertz

2016-11-01

Full Text Available The combined effect of fundamental results about neurocognitive processes and advancements in decoding mental states from ongoing brain signals has brought forth a whole range of potential neurotechnological applications. In this article, we review our developments in this area and put them into perspective. These examples cover a wide range of maturity levels with respect to their applicability. While we assume we are still a long way away from integrating Brain-Computer Interface (BCI technology in general interaction with computers, or from implementing neurotechnological measures in safety-critical workplaces, results have already now been obtained involving a BCI as research tool. In this article, we discuss the reasons why, in some of the prospective application domains, considerable effort is still required to make the systems ready to deal with the full complexity of the real world.

A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.

Science.gov (United States)

Shin, Jaeyoung; Kwon, Jinuk; Im, Chang-Hwan

2018-01-01

The performance of a brain-computer interface (BCI) can be enhanced by simultaneously using two or more modalities to record brain activity, which is generally referred to as a hybrid BCI. To date, many BCI researchers have tried to implement a hybrid BCI system by combining electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) to improve the overall accuracy of binary classification. However, since hybrid EEG-NIRS BCI, which will be denoted by hBCI in this paper, has not been applied to ternary classification problems, paradigms and classification strategies appropriate for ternary classification using hBCI are not well investigated. Here we propose the use of an hBCI for the classification of three brain activation patterns elicited by mental arithmetic, motor imagery, and idle state, with the aim to elevate the information transfer rate (ITR) of hBCI by increasing the number of classes while minimizing the loss of accuracy. EEG electrodes were placed over the prefrontal cortex and the central cortex, and NIRS optodes were placed only on the forehead. The ternary classification problem was decomposed into three binary classification problems using the "one-versus-one" (OVO) classification strategy to apply the filter-bank common spatial patterns filter to EEG data. A 10 × 10-fold cross validation was performed using shrinkage linear discriminant analysis (sLDA) to evaluate the average classification accuracies for EEG-BCI, NIRS-BCI, and hBCI when the meta-classification method was adopted to enhance classification accuracy. The ternary classification accuracies for EEG-BCI, NIRS-BCI, and hBCI were 76.1 ± 12.8, 64.1 ± 9.7, and 82.2 ± 10.2%, respectively. The classification accuracy of the proposed hBCI was thus significantly higher than those of the other BCIs ( p < 0.005). The average ITR for the proposed hBCI was calculated to be 4.70 ± 1.92 bits/minute, which was 34.3% higher than that reported for a previous binary hBCI study.

User-customized brain computer interfaces using Bayesian optimization.

Science.gov (United States)

Bashashati, Hossein; Ward, Rabab K; Bashashati, Ali

2016-04-01

The brain characteristics of different people are not the same. Brain computer interfaces (BCIs) should thus be customized for each individual person. In motor-imagery based synchronous BCIs, a number of parameters (referred to as hyper-parameters) including the EEG frequency bands, the channels and the time intervals from which the features are extracted should be pre-determined based on each subject's brain characteristics. To determine the hyper-parameter values, previous work has relied on manual or semi-automatic methods that are not applicable to high-dimensional search spaces. In this paper, we propose a fully automatic, scalable and computationally inexpensive algorithm that uses Bayesian optimization to tune these hyper-parameters. We then build different classifiers trained on the sets of hyper-parameter values proposed by the Bayesian optimization. A final classifier aggregates the results of the different classifiers. We have applied our method to 21 subjects from three BCI competition datasets. We have conducted rigorous statistical tests, and have shown the positive impact of hyper-parameter optimization in improving the accuracy of BCIs. Furthermore, We have compared our results to those reported in the literature. Unlike the best reported results in the literature, which are based on more sophisticated feature extraction and classification methods, and rely on prestudies to determine the hyper-parameter values, our method has the advantage of being fully automated, uses less sophisticated feature extraction and classification methods, and yields similar or superior results compared to the best performing designs in the literature.

Robotics, stem cells, and brain-computer interfaces in rehabilitation and recovery from stroke: updates and advances.

Science.gov (United States)

Boninger, Michael L; Wechsler, Lawrence R; Stein, Joel

2014-11-01

The aim of this study was to describe the current state and latest advances in robotics, stem cells, and brain-computer interfaces in rehabilitation and recovery for stroke. The authors of this summary recently reviewed this work as part of a national presentation. The article represents the information included in each area. Each area has seen great advances and challenges as products move to market and experiments are ongoing. Robotics, stem cells, and brain-computer interfaces all have tremendous potential to reduce disability and lead to better outcomes for patients with stroke. Continued research and investment will be needed as the field moves forward. With this investment, the potential for recovery of function is likely substantial.

Capacitance enhancement via electrode patterning

International Nuclear Information System (INIS)

Ho, Tuan A.; Striolo, Alberto

2013-01-01

The necessity of increasing the energy density in electric double layer capacitors to meet current demand is fueling fundamental and applied research alike. We report here molecular dynamics simulation results for aqueous electrolytes near model electrodes. Particular focus is on the effect of electrode patterning on the structure of interfacial electrolytes, and on the potential drop between the solid electrodes and the bulk electrolytes. The latter is estimated by numerically integrating the Poisson equation using the charge densities due to water and ions accumulated near the interface as input. We considered uniform and patterned electrodes, both positively and negatively charged. The uniformly charged electrodes are modeled as graphite. The patterned ones are obtained by removing carbon atoms from the top-most graphene layer, yielding nanoscopic squares and stripes patterns. For simplicity, the patterned electrodes are effectively simulated as insulators (the charge remains localized on the top-most layer of carbon atoms). Our simulations show that the patterns alter the structure of water and the accumulation of ions at the liquid-solid interfaces. Using aqueous NaCl solutions, we found that while the capacitance calculated for three positively charged electrodes did not change much, that calculated for the negatively charged electrodes significantly increased upon patterning. We find that both water structure and orientation, as well as ion accumulation affect the capacitance. As electrode patterning affects differently water structure and ion accumulation, it might be possible to observe ion-specific effects. These results could be useful for advancing our understanding of electric double layer capacitors, capacitive desalination processes, as well as of fundamental interfacial electrolytes properties

Use of brain electrical activity for the identification of hematomas in mild traumatic brain injury.

Science.gov (United States)

Hanley, Daniel F; Chabot, Robert; Mould, W Andrew; Morgan, Timothy; Naunheim, Rosanne; Sheth, Kevin N; Chiang, William; Prichep, Leslie S

2013-12-15

This study investigates the potential clinical utility in the emergency department (ED) of an index of brain electrical activity to identify intracranial hematomas. The relationship between this index and depth, size, and type of hematoma was explored. Ten minutes of brain electrical activity was recorded from a limited montage in 38 adult patients with traumatic hematomas (CT scan positive) and 38 mild head injured controls (CT scan negative) in the ED. The volume of blood and distance from recording electrodes were measured by blinded independent experts. Brain electrical activity data were submitted to a classification algorithm independently developed traumatic brain injury (TBI) index to identify the probability of a CT+traumatic event. There was no significant relationship between the TBI-Index and type of hematoma, or distance of the bleed from recording sites. A significant correlation was found between TBI-Index and blood volume. The sensitivity to hematomas was 100%, positive predictive value was 74.5%, and positive likelihood ratio was 2.92. The TBI-Index, derived from brain electrical activity, demonstrates high accuracy for identification of traumatic hematomas. Further, this was not influenced by distance of the bleed from the recording electrodes, blood volume, or type of hematoma. Distance and volume limitations noted with other methods, (such as that based on near-infrared spectroscopy) were not found, thus suggesting the TBI-Index to be a potentially important adjunct to acute assessment of head injury. Because of the life-threatening risk of undetected hematomas (false negatives), specificity was permitted to be lower, 66%, in exchange for extremely high sensitivity.

Current trends in hardware and software for brain-computer interfaces (BCIs).

Science.gov (United States)

Brunner, P; Bianchi, L; Guger, C; Cincotti, F; Schalk, G

2011-04-01

A brain-computer interface (BCI) provides a non-muscular communication channel to people with and without disabilities. BCI devices consist of hardware and software. BCI hardware records signals from the brain, either invasively or non-invasively, using a series of device components. BCI software then translates these signals into device output commands and provides feedback. One may categorize different types of BCI applications into the following four categories: basic research, clinical/translational research, consumer products, and emerging applications. These four categories use BCI hardware and software, but have different sets of requirements. For example, while basic research needs to explore a wide range of system configurations, and thus requires a wide range of hardware and software capabilities, applications in the other three categories may be designed for relatively narrow purposes and thus may only need a very limited subset of capabilities. This paper summarizes technical aspects for each of these four categories of BCI applications. The results indicate that BCI technology is in transition from isolated demonstrations to systematic research and commercial development. This process requires several multidisciplinary efforts, including the development of better integrated and more robust BCI hardware and software, the definition of standardized interfaces, and the development of certification, dissemination and reimbursement procedures.

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.

Current trends in hardware and software for brain-computer interfaces (BCIs)

Science.gov (United States)

Brunner, P.; Bianchi, L.; Guger, C.; Cincotti, F.; Schalk, G.

2011-04-01

A brain-computer interface (BCI) provides a non-muscular communication channel to people with and without disabilities. BCI devices consist of hardware and software. BCI hardware records signals from the brain, either invasively or non-invasively, using a series of device components. BCI software then translates these signals into device output commands and provides feedback. One may categorize different types of BCI applications into the following four categories: basic research, clinical/translational research, consumer products, and emerging applications. These four categories use BCI hardware and software, but have different sets of requirements. For example, while basic research needs to explore a wide range of system configurations, and thus requires a wide range of hardware and software capabilities, applications in the other three categories may be designed for relatively narrow purposes and thus may only need a very limited subset of capabilities. This paper summarizes technical aspects for each of these four categories of BCI applications. The results indicate that BCI technology is in transition from isolated demonstrations to systematic research and commercial development. This process requires several multidisciplinary efforts, including the development of better integrated and more robust BCI hardware and software, the definition of standardized interfaces, and the development of certification, dissemination and reimbursement procedures.

Complications and results of subdural grid electrode implantation in epilepsy surgery.

Science.gov (United States)

Lee, W S; Lee, J K; Lee, S A; Kang, J K; Ko, T S

2000-11-01

We assessed the risk of delayed subdural hematoma and other complications associated with subdural grid implantation. Forty-nine patients underwent subdural grid implantation with/without subdural strips or depth electrodes from January 1994 to August 1998. To identify the risk associated with subdural grid implantation, a retrospective review of all patients' medical records and radiological studies was performed. The major complications of 50 subdural grid electrode implantations were as follows: four cases (7.8%) of delayed subdural hematoma at the site of the subdural grid, requiring emergency operation; two cases (3.9%) of infection; one case (2.0%) of epidural hematoma; and one case (2.0%) of brain swelling. After subdural hematoma removal, the electrodes were left in place. CCTV monitoring and cortical stimulation studies were continued thereafter. No delayed subdural hematoma has occurred since routine placement of subdural drains was begun. In our experience the worst complication of subdural grid implantation has been delayed subdural hematoma. Placement of subdural drains and close observation may be helpful to prevent this serious complication.

Identifying cochlear implant channels with poor electrode-neuron interface: electrically-evoked auditory brainstem responses measured with the partial tripolar configuration

Science.gov (United States)

Bierer, Julie Arenberg; Faulkner, Kathleen F.; Tremblay, Kelly L.

2011-01-01

Objectives The goal of this study was to compare cochlear implant behavioral measures and electrically-evoked auditory brainstem responses (EABRs) obtained with a spatially focused electrode configuration. It has been shown previously that channels with high thresholds, when measured with the tripolar configuration, exhibit relatively broad psychophysical tuning curves (Bierer and Faulkner, 2010). The elevated threshold and degraded spatial/spectral selectivity of such channels are consistent with a poor electrode-neuron interface, such as suboptimal electrode placement or reduced nerve survival. However, the psychophysical methods required to obtain these data are time intensive and may not be practical during a clinical mapping procedure, especially for young children. Here we have extended the previous investigation to determine if a physiological approach could provide a similar assessment of channel functionality. We hypothesized that, in accordance with the perceptual measures, higher EABR thresholds would correlate with steeper EABR amplitude growth functions, reflecting a degraded electrode-neuron interface. Design Data were collected from six cochlear implant listeners implanted with the HiRes 90k cochlear implant (Advanced Bionics). Single-channel thresholds and most comfortable listening levels were obtained for stimuli that varied in presumed electrical field size by using the partial tripolar configuration, for which a fraction of current (σ) from a center active electrode returns through two neighboring electrodes and the remainder through a distant indifferent electrode. EABRs were obtained in each subject for the two channels having the highest and lowest tripolar (σ=1 or 0.9) behavioral threshold. Evoked potentials were measured with both the monopolar (σ=0) and a more focused partial tripolar (σ ≥ 0.50) configuration. Results Consistent with previous studies, EABR thresholds were highly and positively correlated with behavioral thresholds

Flexible electrode belt for EIT using nanofiber web dry electrodes.

Science.gov (United States)

Oh, Tong In; Kim, Tae Eui; Yoon, Sun; Kim, Kap Jin; Woo, Eung Je; Sadleir, Rosalind J

2012-10-01

Efficient connection of multiple electrodes to the body for impedance measurement and voltage monitoring applications is of critical importance to measurement quality and practicality. Electrical impedance tomography (EIT) experiments have generally required a cumbersome procedure to attach the multiple electrodes needed in EIT. Once placed, these electrodes must then maintain good contact with the skin during measurements that may last several hours. There is usually also the need to manage the wires that run between the electrodes and the EIT system. These problems become more severe as the number of electrodes increases, and may limit the practicality and portability of this imaging method. There have been several trials describing human-electrode interfaces using configurations such as electrode belts, helmets or rings. In this paper, we describe an electrode belt we developed for long-term EIT monitoring of human lung ventilation. The belt included 16 embossed electrodes that were designed to make good contact with the skin. The electrodes were fabricated using an Ag-plated PVDF nanofiber web and metallic threads. A large contact area and padding were used behind each electrode to improve subject comfort and reduce contact impedances. The electrodes were incorporated, equally spaced, into an elasticated fabric belt. We tested the electrode belt in conjunction with the KHU Mark1 multi-frequency EIT system, and demonstrate time-difference images of phantoms and human subjects during normal breathing and running. We found that the Ag-plated PVDF nanofiber web electrodes were suitable for long-term measurement because of their flexibility and durability. Moreover, the contact impedance and stability of the Ag-plated PVDF nanofiber web electrodes were found to be comparable to similarly tested Ag/AgCl electrodes.

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.

Role of Stress Factors on the Adhesion of Interfaces in R2R Fabricated Organic Photovoltaics

DEFF Research Database (Denmark)

Corazza, Michael; Rolston, Nicholas; Dauskardt, Reinhold H.

2016-01-01

adhesion properties. Depth profiling analysis on the fractured samples reveals interdiffusion of layers in the structure, which results in the increase of adhesion and change of the debond path. It is shown that through diffusion and intermixing of internal interfaces coupled stresses can increase......The role of the common stress factors such as high temperature, humidity,and UV irradiation on interface adhesion of roll-to-roll fabricated organic photovoltaic (OPV) devices is investigated. The samples range from bare front electrodes to complete devices. It is shown that applying single stress...... or combinations of stresses onto the samples variably affect the adhesion properties of the different interfaces in the OPV device. It is revealed that while the exposure of the complete devices to the stresses results in the loss of photovoltaic performance, some interfaces in the devices present improved...

A development architecture for serious games using BCI (brain computer interface) sensors.

Science.gov (United States)

Sung, Yunsick; Cho, Kyungeun; Um, Kyhyun

2012-11-12

Games that use brainwaves via brain-computer interface (BCI) devices, to improve brain functions are known as BCI serious games. Due to the difficulty of developing BCI serious games, various BCI engines and authoring tools are required, and these reduce the development time and cost. However, it is desirable to reduce the amount of technical knowledge of brain functions and BCI devices needed by game developers. Moreover, a systematic BCI serious game development process is required. In this paper, we present a methodology for the development of BCI serious games. We describe an architecture, authoring tools, and development process of the proposed methodology, and apply it to a game development approach for patients with mild cognitive impairment as an example. This application demonstrates that BCI serious games can be developed on the basis of expert-verified theories.

Structure formation and surface chemistry of ionic liquids on model electrode surfaces—Model studies for the electrode | electrolyte interface in Li-ion batteries

Science.gov (United States)

Buchner, Florian; Uhl, Benedikt; Forster-Tonigold, Katrin; Bansmann, Joachim; Groß, Axel; Behm, R. Jürgen

2018-05-01

Ionic liquids (ILs) are considered as attractive electrolyte solvents in modern battery concepts such as Li-ion batteries. Here we present a comprehensive review of the results of previous model studies on the interaction of the battery relevant IL 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide ([BMP]+[TFSI]-) with a series of structurally and chemically well-defined model electrode surfaces, which are increasingly complex and relevant for battery applications [Ag(111), Au(111), Cu(111), pristine and lithiated highly oriented pyrolytic graphite (HOPG), and rutile TiO2(110)]. Combining surface science techniques such as high resolution scanning tunneling microscopy and X-ray photoelectron spectroscopy for characterizing surface structure and chemical composition in deposited (sub-)monolayer adlayers with dispersion corrected density functional theory based calculations, this work aims at a molecular scale understanding of the fundamental processes at the electrode | electrolyte interface, which are crucial for the development of the so-called solid electrolyte interphase (SEI) layer in batteries. Performed under idealized conditions, in an ultrahigh vacuum environment, these model studies provide detailed insights on the structure formation in the adlayer, the substrate-adsorbate and adsorbate-adsorbate interactions responsible for this, and the tendency for chemically induced decomposition of the IL. To mimic the situation in an electrolyte, we also investigated the interaction of adsorbed IL (sub-)monolayers with coadsorbed lithium. Even at 80 K, postdeposited Li is found to react with the IL, leading to decomposition products such as LiF, Li3N, Li2S, LixSOy, and Li2O. In the absence of a [BMP]+[TFSI]- adlayer, it tends to adsorb, dissolve, or intercalate into the substrate (metals, HOPG) or to react with the substrate (TiO2) above a critical temperature, forming LiOx and Ti3+ species in the latter case. Finally, the formation of stable

Robotic devices and brain-machine interfaces for hand rehabilitation post-stroke

OpenAIRE

McConnell, Alistair C; Moioli, Renan C; Brasil, Fabricio L; Vallejo, Marta; Corne, David W; Vargas, Patricia A; Stokes, Adam A

2017-01-01

OBJECTIVE: To review the state of the art of robotic-aided hand physiotherapy for post-stroke rehabilitation, including the use of brain-machine interfaces. Each patient has a unique clinical history and, in response to personalized treatment needs, research into individualized and at-home treatment options has expanded rapidly in recent years. This has resulted in the development of many devices and design strategies for use in stroke rehabilitation.METHODS: The development progression of ro...

Getting signals into the brain: visual prosthetics through thalamic microstimulation.

Science.gov (United States)

Pezaris, John S; Eskandar, Emad N

2009-07-01

Common causes of blindness are diseases that affect the ocular structures, such as glaucoma, retinitis pigmentosa, and macular degeneration, rendering the eyes no longer sensitive to light. The visual pathway, however, as a predominantly central structure, is largely spared in these cases. It is thus widely thought that a device-based prosthetic approach to restoration of visual function will be effective and will enjoy similar success as cochlear implants have for restoration of auditory function. In this article the authors review the potential locations for stimulation electrode placement for visual prostheses, assessing the anatomical and functional advantages and disadvantages of each. Of particular interest to the neurosurgical community is placement of deep brain stimulating electrodes in thalamic structures that has shown substantial promise in an animal model. The theory of operation of visual prostheses is discussed, along with a review of the current state of knowledge. Finally, the visual prosthesis is proposed as a model for a general high-fidelity machine-brain interface.

On the importance of electrode parameters for shaping electric field patterns generated by tDCS

DEFF Research Database (Denmark)

B. Saturnino, Guilherme; Antunes, André; Thielscher, Axel

2015-01-01

Transcranial direct current stimulation (tDCS) uses electrode pads placed on the head to deliver weak direct current to the brain and modulate neuronal excitability. The effects depend on the intensity and spatial distribution of the electric field. This in turn depends on the geometry and electric...... electrode modeling influences the calculated electric field in the brain. We take into account electrode shape, size, connector position and conductivities of different electrode materials (including saline solutions and electrode gels). These factors are systematically characterized to demonstrate...... their impact on the field distribution in the brain. The goals are to assess the effect of simplified electrode models; and to develop practical rules-of-thumb to achieve a stronger stimulation of the targeted brain regions underneath the electrode pads. We show that for standard rectangular electrode pads...

Relating the 3D electrode morphology to Li-ion battery performance; a case for LiFePO4

Science.gov (United States)

Liu, Zhao; Verhallen, Tomas W.; Singh, Deepak P.; Wang, Hongqian; Wagemaker, Marnix; Barnett, Scott

2016-08-01

One of the main goals in lithium ion battery electrode design is to increase the power density. This requires insight in the relation between the complex heterogeneous microstructure existing of active material, conductive additive and electrolyte providing the required electronic and Li-ion transport. FIB-SEM is used to determine the three phase 3D morphology, and Li-ion concentration profiles obtained with Neutron Depth Profiling (NDP) are compared for two cases, conventional LiFePO4 electrodes and better performing carbonate templated LiFePO4 electrodes. This provides detailed understanding of the impact of key parameters such as the tortuosity for electron and Li-ion transport though the electrodes. The created hierarchical pore network of the templated electrodes, containing micron sized pores, appears to be effective only at high rate charge where electrolyte depletion is hindering fast discharge. Surprisingly the carbonate templating method results in a better electronic conductive CB network, enhancing the activity of LiFePO4 near the electrolyte-electrode interface as directly observed with NDP, which in a large part is responsible for the improved rate performance both during charge and discharge. The results demonstrate that standard electrodes have a far from optimal charge transport network and that significantly improved electrode performance should be possible by engineering the microstructure.

Rough Electrode Creates Excess Capacitance in Thin-Film Capacitors.

Science.gov (United States)

Torabi, Solmaz; Cherry, Megan; Duijnstee, Elisabeth A; Le Corre, Vincent M; Qiu, Li; Hummelen, Jan C; Palasantzas, George; Koster, L Jan Anton

2017-08-16

The parallel-plate capacitor equation is widely used in contemporary material research for nanoscale applications and nanoelectronics. To apply this equation, flat and smooth electrodes are assumed for a capacitor. This essential assumption is often violated for thin-film capacitors because the formation of nanoscale roughness at the electrode interface is very probable for thin films grown via common deposition methods. In this work, we experimentally and theoretically show that the electrical capacitance of thin-film capacitors with realistic interface roughness is significantly larger than the value predicted by the parallel-plate capacitor equation. The degree of the deviation depends on the strength of the roughness, which is described by three roughness parameters for a self-affine fractal surface. By applying an extended parallel-plate capacitor equation that includes the roughness parameters of the electrode, we are able to calculate the excess capacitance of the electrode with weak roughness. Moreover, we introduce the roughness parameter limits for which the simple parallel-plate capacitor equation is sufficiently accurate for capacitors with one rough electrode. Our results imply that the interface roughness beyond the proposed limits cannot be dismissed unless the independence of the capacitance from the interface roughness is experimentally demonstrated. The practical protocols suggested in our work for the reliable use of the parallel-plate capacitor equation can be applied as general guidelines in various fields of interest.

Evaluation of the hybrid-L24 electrode using microcomputed tomography.

Science.gov (United States)

Driscoll, Colin L W; Carlson, Matthew L; Fama, Anthony F; Lane, John I

2011-07-01

To compare electrode array position, and depth of insertion of the Cochlear Hybrid-L24 electrode array following traditional cochleostomy and round window (RW) insertion. Prospective cadaveric temporal bone study. Ten cadaveric temporal bones were implanted with the Hybrid-L24 electrode array; half were introduced through a RW approach, whereas the other half were inserted through a traditional scala tympani cochleostomy. A micro-CT scanner was then used to evaluate electrode position, intracochlear trauma, and depth of insertion. All electrodes were inserted into the scala tympani without significant resistance. No electrodes demonstrated tip fold-over or through-fracturing of the osseous spiral lamina, basilar membrane, or spiral ligament. The average angular depth of insertion for all 10 electrodes was 252.4°. Compared to cochleostomy insertions, electrodes inserted through the RW more commonly acquired a proximal perimodiolar orientation, followed a more predictable course, and less commonly contacted critical soft tissue structures. The results of this study demonstrate that the Hybrid-L24 electrode can be successfully inserted using a RW or traditional cochleostomy technique with minimal intracochlear trauma. Our data also suggests that with this model, RW insertions may provide particular advantages with respect to hearing preservation over the traditional cochleostomy approach. Copyright © 2011 The American Laryngological, Rhinological, and Otological Society, Inc.

A qualitative study adopting a user-centered approach to design and validate a brain computer interface for cognitive rehabilitation for people with brain injury.

Science.gov (United States)

Martin, Suzanne; Armstrong, Elaine; Thomson, Eileen; Vargiu, Eloisa; Solà, Marc; Dauwalder, Stefan; Miralles, Felip; Daly Lynn, Jean

2017-07-14

Cognitive rehabilitation is established as a core intervention within rehabilitation programs following a traumatic brain injury (TBI). Digitally enabled assistive technologies offer opportunities for clinicians to increase remote access to rehabilitation supporting transition into home. Brain Computer Interface (BCI) systems can harness the residual abilities of individuals with limited function to gain control over computers through their brain waves. This paper presents an online cognitive rehabilitation application developed with therapists, to work remotely with people who have TBI, who will use BCI at home to engage in the therapy. A qualitative research study was completed with people who are community dwellers post brain injury (end users), and a cohort of therapists involved in cognitive rehabilitation. A user-centered approach over three phases in the development, design and feasibility testing of this cognitive rehabilitation application included two tasks (Find-a-Category and a Memory Card task). The therapist could remotely prescribe activity with different levels of difficulty. The service user had a home interface which would present the therapy activities. This novel work was achieved by an international consortium of academics, business partners and service users.

Changes in functional brain organization and behavioral correlations after rehabilitative therapy using a brain-computer interface

Directory of Open Access Journals (Sweden)

Brittany Mei Young

2014-07-01

Full Text Available This study aims to examine the changes in task-related brain activity induced by rehabilitative therapy using brain-computer interface (BCI technologies and whether these changes are relevant to functional gains achieved through the use of these therapies. Stroke patients with persistent upper-extremity motor deficits received interventional rehabilitation therapy using a closed-loop neurofeedback BCI device (n=8 or no therapy (n=6. Behavioral assessments using the Stroke Impact Scale, the Action Research Arm Test, and the Nine-Hole Peg Test as well as task-based fMRI scans were conducted before, during, after, and one month after therapy administration or at analogous intervals in the absence of therapy. Laterality Index (LI during finger tapping of each hand were calculated for each time point and assessed for correlation with behavioral outcomes. Brain activity during finger tapping of each hand shifted over the course of BCI therapy but not in the absence of therapy to greater involvement of the non-lesioned hemisphere (and lesser involvement of the stroke-lesioned hemisphere as measured by LI. Moreover, changes from baseline LI values during finger tapping of the impaired hand were correlated with gains in both objective and subjective behavioral measures. These findings suggest that the administration of interventional BCI therapy can induce differential changes in brain activity patterns between the lesioned and nonlesioned hemisphere and that these brain changes are associated with changes in specific motor functions.

Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface

DEFF Research Database (Denmark)

Mrachacz-Kersting, Natalie; Jiang, Ning; Stevenson, Andrew James Thomas

2016-01-01

Brain-computer interfaces (BCIs) have the potential to improve functionality in chronic stoke patients when applied over a large number of sessions. Here, we evaluate the effect and the underlying mechanisms of three BCI training sessions in a double-blind-sham-controlled design. The applied BCI......-associative group. Fugl-Meyer motor scores (0.8±0.46 point difference p=0.01), foot (but not finger) tapping frequency, and 10-m walking speed improved significantly for the BCIassociative group, indicating clinically relevant improvements. For the BCI as applied here, the precise coupling between the brain command...

Brain-computer interface research a state-of-the-art summary

CERN Document Server

Allison, Brendan; Edlinger, Günter; Leuthardt, E C

Brain-computer interfaces (BCIs) are rapidly developing into a mainstream, worldwide research endeavor. With so many new groups and projects, it can be difficult to identify the best ones. This book summarizes ten leading projects from around the world. About 60 submissions were received in 2011 for the highly competitive BCI Research Award, and an international jury selected the top ten. This Brief gives a concise but carefully illustrated and fully up-to-date description of each of these projects, together with an introduction and concluding chapter by the editors.

Design, fabrication and skin-electrode contact analysis of polymer microneedle-based ECG electrodes

Science.gov (United States)

O'Mahony, Conor; Grygoryev, Konstantin; Ciarlone, Antonio; Giannoni, Giuseppe; Kenthao, Anan; Galvin, Paul

2016-08-01

Microneedle-based ‘dry’ electrodes have immense potential for use in diagnostic procedures such as electrocardiography (ECG) analysis, as they eliminate several of the drawbacks associated with the conventional ‘wet’ electrodes currently used for physiological signal recording. To be commercially successful in such a competitive market, it is essential that dry electrodes are manufacturable in high volumes and at low cost. In addition, the topographical nature of these emerging devices means that electrode performance is likely to be highly dependent on the quality of the skin-electrode contact. This paper presents a low-cost, wafer-level micromoulding technology for the fabrication of polymeric ECG electrodes that use microneedle structures to make a direct electrical contact to the body. The double-sided moulding process can be used to eliminate post-process via creation and wafer dicing steps. In addition, measurement techniques have been developed to characterize the skin-electrode contact force. We perform the first analysis of signal-to-noise ratio dependency on contact force, and show that although microneedle-based electrodes can outperform conventional gel electrodes, the quality of ECG recordings is significantly dependent on temporal and mechanical aspects of the skin-electrode interface.

Design, fabrication and skin-electrode contact analysis of polymer microneedle-based ECG electrodes

International Nuclear Information System (INIS)

O’Mahony, Conor; Grygoryev, Konstantin; Ciarlone, Antonio; Giannoni, Giuseppe; Kenthao, Anan; Galvin, Paul

2016-01-01

Microneedle-based ‘dry’ electrodes have immense potential for use in diagnostic procedures such as electrocardiography (ECG) analysis, as they eliminate several of the drawbacks associated with the conventional ‘wet’ electrodes currently used for physiological signal recording. To be commercially successful in such a competitive market, it is essential that dry electrodes are manufacturable in high volumes and at low cost. In addition, the topographical nature of these emerging devices means that electrode performance is likely to be highly dependent on the quality of the skin-electrode contact.This paper presents a low-cost, wafer-level micromoulding technology for the fabrication of polymeric ECG electrodes that use microneedle structures to make a direct electrical contact to the body. The double-sided moulding process can be used to eliminate post-process via creation and wafer dicing steps. In addition, measurement techniques have been developed to characterize the skin-electrode contact force. We perform the first analysis of signal-to-noise ratio dependency on contact force, and show that although microneedle-based electrodes can outperform conventional gel electrodes, the quality of ECG recordings is significantly dependent on temporal and mechanical aspects of the skin-electrode interface. (paper)

A novel Brain Computer Interface for classification of social joint attention in autism and comparison of 3 experimental setups: A feasibility study.

Science.gov (United States)

Amaral, Carlos P; Simões, Marco A; Mouga, Susana; Andrade, João; Castelo-Branco, Miguel

2017-10-01

We present a novel virtual-reality P300-based Brain Computer Interface (BCI) paradigm using social cues to direct the focus of attention. We combined interactive immersive virtual-reality (VR) technology with the properties of P300 signals in a training tool which can be used in social attention disorders such as autism spectrum disorder (ASD). We tested the novel social attention training paradigm (P300-based BCI paradigm for rehabilitation of joint-attention skills) in 13 healthy participants, in 3 EEG systems. The more suitable setup was tested online with 4 ASD subjects. Statistical accuracy was assessed based on the detection of P300, using spatial filtering and a Naïve-Bayes classifier. We compared: 1 - g.Mobilab+ (active dry-electrodes, wireless transmission); 2 - g.Nautilus (active electrodes, wireless transmission); 3 - V-Amp with actiCAP Xpress dry-electrodes. Significant statistical classification was achieved in all systems. g.Nautilus proved to be the best performing system in terms of accuracy in the detection of P300, preparation time, speed and reported comfort. Proof of concept tests in ASD participants proved that this setup is feasible for training joint attention skills in ASD. This work provides a unique combination of 'easy-to-use' BCI systems with new technologies such as VR to train joint-attention skills in autism. Our P300 BCI paradigm is feasible for future Phase I/II clinical trials to train joint-attention skills, with successful classification within few trials, online in ASD participants. The g.Nautilus system is the best performing one to use with the developed BCI setup. Copyright © 2017 Elsevier B.V. All rights reserved.

User’s Emotions and Usability Study of a Brain-Computer Interface Applied to People with Cerebral Palsy

Directory of Open Access Journals (Sweden)

Alejandro Rafael García Ramírez

2018-02-01

Full Text Available People with motor and communication disorders face serious challenges in interacting with computers. To enhance this functionality, new human-computer interfaces are being studied. In this work, a brain-computer interface based on the Emotiv Epoc is used to analyze human-computer interactions in cases of cerebral palsy. The Phrase-Composer software was developed to interact with the brain-computer interface. A system usability evaluation was carried out with the participation of three specialists from The Fundação Catarinense de Educação especial (FCEE and four cerebral palsy volunteers. Even though the System Usability Scale (SUS score was acceptable, several challenges remain. Raw electroencephalography (EEG data were also analyzed in order to assess the user’s emotions during their interaction with the communication device. This study brings new evidences about human-computer interaction related to individuals with cerebral palsy.

Ethics in published brain-computer interface research

Science.gov (United States)

Specker Sullivan, L.; Illes, J.

2018-02-01

Objective. Sophisticated signal processing has opened the doors to more research with human subjects than ever before. The increase in the use of human subjects in research comes with a need for increased human subjects protections. Approach. We quantified the presence or absence of ethics language in published reports of brain-computer interface (BCI) studies that involved human subjects and qualitatively characterized ethics statements. Main results. Reports of BCI studies with human subjects that are published in neural engineering and engineering journals are anchored in the rationale of technological improvement. Ethics language is markedly absent, omitted from 31% of studies published in neural engineering journals and 59% of studies in biomedical engineering journals. Significance. As the integration of technological tools with the capacities of the mind deepens, explicit attention to ethical issues will ensure that broad human benefit is embraced and not eclipsed by technological exclusiveness.

BCILAB: a platform for brain-computer interface development

Science.gov (United States)

Kothe, Christian Andreas; Makeig, Scott

2013-10-01

Objective. The past two decades have seen dramatic progress in our ability to model brain signals recorded by electroencephalography, functional near-infrared spectroscopy, etc., and to derive real-time estimates of user cognitive state, response, or intent for a variety of purposes: to restore communication by the severely disabled, to effect brain-actuated control and, more recently, to augment human-computer interaction. Continuing these advances, largely achieved through increases in computational power and methods, requires software tools to streamline the creation, testing, evaluation and deployment of new data analysis methods. Approach. Here we present BCILAB, an open-source MATLAB-based toolbox built to address the need for the development and testing of brain-computer interface (BCI) methods by providing an organized collection of over 100 pre-implemented methods and method variants, an easily extensible framework for the rapid prototyping of new methods, and a highly automated framework for systematic testing and evaluation of new implementations. Main results. To validate and illustrate the use of the framework, we present two sample analyses of publicly available data sets from recent BCI competitions and from a rapid serial visual presentation task. We demonstrate the straightforward use of BCILAB to obtain results compatible with the current BCI literature. Significance. The aim of the BCILAB toolbox is to provide the BCI community a powerful toolkit for methods research and evaluation, thereby helping to accelerate the pace of innovation in the field, while complementing the existing spectrum of tools for real-time BCI experimentation, deployment and use.

User-customized brain computer interfaces using Bayesian optimization

Science.gov (United States)

Bashashati, Hossein; Ward, Rabab K.; Bashashati, Ali

2016-04-01

Objective. The brain characteristics of different people are not the same. Brain computer interfaces (BCIs) should thus be customized for each individual person. In motor-imagery based synchronous BCIs, a number of parameters (referred to as hyper-parameters) including the EEG frequency bands, the channels and the time intervals from which the features are extracted should be pre-determined based on each subject’s brain characteristics. Approach. To determine the hyper-parameter values, previous work has relied on manual or semi-automatic methods that are not applicable to high-dimensional search spaces. In this paper, we propose a fully automatic, scalable and computationally inexpensive algorithm that uses Bayesian optimization to tune these hyper-parameters. We then build different classifiers trained on the sets of hyper-parameter values proposed by the Bayesian optimization. A final classifier aggregates the results of the different classifiers. Main Results. We have applied our method to 21 subjects from three BCI competition datasets. We have conducted rigorous statistical tests, and have shown the positive impact of hyper-parameter optimization in improving the accuracy of BCIs. Furthermore, We have compared our results to those reported in the literature. Significance. Unlike the best reported results in the literature, which are based on more sophisticated feature extraction and classification methods, and rely on prestudies to determine the hyper-parameter values, our method has the advantage of being fully automated, uses less sophisticated feature extraction and classification methods, and yields similar or superior results compared to the best performing designs in the literature.

Self-Adhesive and Capacitive Carbon Nanotube-Based Electrode to Record Electroencephalograph Signals From the Hairy Scalp.

Science.gov (United States)

Lee, Seung Min; Kim, Jeong Hun; Park, Cheolsoo; Hwang, Ji-Young; Hong, Joung Sook; Lee, Kwang Ho; Lee, Sang Hoon

2016-01-01

We fabricated a carbon nanotube (CNT)/adhesive polydimethylsiloxane (aPDMS) composite-based dry electroencephalograph (EEG) electrode for capacitive measuring of EEG signals. As research related to brain-computer interface applications has advanced, the presence of hairs on a patient's scalp has continued to present an obstacle to recorder EEG signals using dry electrodes. The CNT/aPDMS electrode developed here is elastic, highly conductive, self-adhesive, and capable of making conformal contact with and attaching to a hairy scalp. Onto the conductive disk, hundreds of conductive pillars coated with Parylene C insulation layer were fabricated. A CNT/aPDMS layer was attached on the disk to transmit biosignals to the pillar. The top of disk was designed to be solderable, which enables the electrode to connect with a variety of commercial EEG acquisition systems. The mechanical and electrical characteristics of the electrode were tested, and the performances of the electrodes were evaluated by recording EEGs, including alpha rhythms, auditory-evoked potentials, and steady-state visually-evoked potentials. The results revealed that the electrode provided a high signal-to-noise ratio with good tolerance for motion. Almost no leakage current was observed. Although preamplifiers with ultrahigh input impedance have been essential for previous capacitive electrodes, the EEGs were recorded here by directly connecting a commercially available EEG acquisition system to the electrode to yield high-quality signals comparable to those obtained using conventional wet electrodes.

Intracranial EEG fluctuates over months after implanting electrodes in human brain

Science.gov (United States)

Ung, Hoameng; Baldassano, Steven N.; Bink, Hank; Krieger, Abba M.; Williams, Shawniqua; Vitale, Flavia; Wu, Chengyuan; Freestone, Dean; Nurse, Ewan; Leyde, Kent; Davis, Kathryn A.; Cook, Mark; Litt, Brian

2017-10-01

Objective. Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. Approach. Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient’s recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. Main results. A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. Significance. These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in

Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes.

Science.gov (United States)

Anderson, Daria Nesterovich; Osting, Braxton; Vorwerk, Johannes; Dorval, Alan D; Butson, Christopher R

2018-04-01

Deep brain stimulation (DBS) is a growing treatment option for movement and psychiatric disorders. As DBS technology moves toward directional leads with increased numbers of smaller electrode contacts, trial-and-error methods of manual DBS programming are becoming too time-consuming for clinical feasibility. We propose an algorithm to automate DBS programming in near real-time for a wide range of DBS lead designs. Magnetic resonance imaging and diffusion tensor imaging are used to build finite element models that include anisotropic conductivity. The algorithm maximizes activation of target tissue and utilizes the Hessian matrix of the electric potential to approximate activation of neurons in all directions. We demonstrate our algorithm's ability in an example programming case that targets the subthalamic nucleus (STN) for the treatment of Parkinson's disease for three lead designs: the Medtronic 3389 (four cylindrical contacts), the direct STNAcute (two cylindrical contacts, six directional contacts), and the Medtronic-Sapiens lead (40 directional contacts). The optimization algorithm returns patient-specific contact configurations in near real-time-less than 10 s for even the most complex leads. When the lead was placed centrally in the target STN, the directional leads were able to activate over 50% of the region, whereas the Medtronic 3389 could activate only 40%. When the lead was placed 2 mm lateral to the target, the directional leads performed as well as they did in the central position, but the Medtronic 3389 activated only 2.9% of the STN. This DBS programming algorithm can be applied to cylindrical electrodes as well as novel directional leads that are too complex with modern technology to be manually programmed. This algorithm may reduce clinical programming time and encourage the use of directional leads, since they activate a larger volume of the target area than cylindrical electrodes in central and off-target lead placements.

A primer on brain-machine interfaces, concepts, and technology: a key element in the future of functional neurorestoration.

Science.gov (United States)

Lee, Brian; Liu, Charles Y; Apuzzo, Michael L J

2013-01-01

Conventionally, the practice of neurosurgery has been characterized by the removal of pathology, congenital or acquired. The emerging complement to the removal of pathology is surgery for the specific purpose of restoration of function. Advents in neuroscience, technology, and the understanding of neural circuitry are creating opportunities to intervene in disease processes in a reparative manner, thereby advancing toward the long-sought-after concept of neurorestoration. Approaching the issue of neurorestoration from a biomedical engineering perspective is the rapidly growing arena of implantable devices. Implantable devices are becoming more common in medicine and are making significant advancements to improve a patient's functional outcome. Devices such as deep brain stimulators, vagus nerve stimulators, and spinal cord stimulators are now becoming more commonplace in neurosurgery as we utilize our understanding of the nervous system to interpret neural activity and restore function. One of the most exciting prospects in neurosurgery is the technologically driven field of brain-machine interface, also known as brain-computer interface, or neuroprosthetics. The successful development of this technology will have far-reaching implications for patients suffering from a great number of diseases, including but not limited to spinal cord injury, paralysis, stroke, or loss of limb. This article provides an overview of the issues related to neurorestoration using implantable devices with a specific focus on brain-machine interface technology. Copyright © 2013 Elsevier Inc. All rights reserved.

Brain Tissue Oxygen: In Vivo Monitoring with Carbon Paste Electrodes

Directory of Open Access Journals (Sweden)

John P. Lowry

2005-11-01

Full Text Available In this communication we review selected experiments involving the use ofcarbon paste electrodes (CPEs to monitor and measure brain tissue O2 levels in awakefreely-moving animals. Simultaneous measurements of rCBF were performed using the H2clearance technique. Voltammetric techniques used include both differential pulse (O2 andconstant potential amperometry (rCBF. Mild hypoxia and hyperoxia produced rapidchanges (decrease and increase respectively in the in vivo O2 signal. Neuronal activation(tail pinch and stimulated grooming produced similar increases in both O2 and rCBFindicating that CPE O2 currents provide an index of increases in rCBF when such increasesexceed O2 utilization. Saline injection produced a transient increase in the O2 signal whilechloral hydrate produced slower more long-lasting changes that accompanied the behavioralchanges associated with anaesthesia. Acetazolamide increased O2 levels through an increasein rCBF.

Graphene electrodes for stimulation of neuronal cells

International Nuclear Information System (INIS)

Koerbitzer, Berit; Nick, Christoph; Thielemann, Christiane; Krauss, Peter; Yadav, Sandeep; Schneider, Joerg J

2016-01-01

Graphene has the ability to improve the electrical interface between neuronal cells and electrodes used for recording and stimulation purposes. It provides a biocompatible coating for common electrode materials such as gold and improves the electrode properties. Graphene electrodes are also prepared on SiO 2 substrate to benefit from its optical properties like transparency. We perform electrochemical and Raman characterization of gold electrodes with graphene coating and compare them with graphene on SiO 2 substrate. It was found that the substrate plays an important role in the performance of graphene and show that graphene on SiO 2 substrate is a very promising material combination for stimulation electrodes. (paper)

P300 brain computer interface: current challenges and emerging trends

Science.gov (United States)

Fazel-Rezai, Reza; Allison, Brendan Z.; Guger, Christoph; Sellers, Eric W.; Kleih, Sonja C.; Kübler, Andrea

2012-01-01

A brain-computer interface (BCI) enables communication without movement based on brain signals measured with electroencephalography (EEG). BCIs usually rely on one of three types of signals: the P300 and other components of the event-related potential (ERP), steady state visual evoked potential (SSVEP), or event related desynchronization (ERD). Although P300 BCIs were introduced over twenty years ago, the past few years have seen a strong increase in P300 BCI research. This closed-loop BCI approach relies on the P300 and other components of the ERP, based on an oddball paradigm presented to the subject. In this paper, we overview the current status of P300 BCI technology, and then discuss new directions: paradigms for eliciting P300s; signal processing methods; applications; and hybrid BCIs. We conclude that P300 BCIs are quite promising, as several emerging directions have not yet been fully explored and could lead to improvements in bit rate, reliability, usability, and flexibility. PMID:22822397

Sex and Electrode Configuration in Transcranial Electrical Stimulation

Directory of Open Access Journals (Sweden)

Michael J. Russell

2017-08-01

Full Text Available Transcranial electrical stimulation (tES can be an effective non-invasive neuromodulation procedure. Unfortunately, the considerable variation in reported treatment outcomes, both within and between studies, has made the procedure unreliable for many applications. To determine if individual differences in cranium morphology and tissue conductivity can account for some of this variation, the electrical density at two cortical locations (temporal and frontal directly under scalp electrodes was modeled using a validated MRI modeling procedure in 23 subjects (12 males and 11 females. Three different electrode configurations (non-cephalic, bi-cranial, and ring commonly used in tES were modeled at three current intensities (0.5, 1.0, and 2.0 mA. The aims were to assess the effects of configuration and current intensity on relative current received at a cortical brain target directly under the stimulating electrode and to characterize individual variation. The different electrode configurations resulted in up to a ninefold difference in mean current densities delivered to the brains. The ring configuration delivered the least current and the non-cephalic the most. Female subjects showed much less current to the brain than male subjects. Individual differences in the current received and differences in electrode configurations may account for significant variability in current delivered and, thus, potentially a significant portion of reported variation in clinical outcomes at two commonly targeted regions of the brain.

Optimization of focality and direction in dense electrode array transcranial direct current stimulation (tDCS)

Science.gov (United States)

Guler, Seyhmus; Dannhauer, Moritz; Erem, Burak; Macleod, Rob; Tucker, Don; Turovets, Sergei; Luu, Phan; Erdogmus, Deniz; Brooks, Dana H.

2016-06-01

Objective. Transcranial direct current stimulation (tDCS) aims to alter brain function non-invasively via electrodes placed on the scalp. Conventional tDCS uses two relatively large patch electrodes to deliver electrical current to the brain region of interest (ROI). Recent studies have shown that using dense arrays containing up to 512 smaller electrodes may increase the precision of targeting ROIs. However, this creates a need for methods to determine effective and safe stimulus patterns as the number of degrees of freedom is much higher with such arrays. Several approaches to this problem have appeared in the literature. In this paper, we describe a new method for calculating optimal electrode stimulus patterns for targeted and directional modulation in dense array tDCS which differs in some important aspects with methods reported to date. Approach. We optimize stimulus pattern of dense arrays with fixed electrode placement to maximize the current density in a particular direction in the ROI. We impose a flexible set of safety constraints on the current power in the brain, individual electrode currents, and total injected current, to protect subject safety. The proposed optimization problem is convex and thus efficiently solved using existing optimization software to find unique and globally optimal electrode stimulus patterns. Main results. Solutions for four anatomical ROIs based on a realistic head model are shown as exemplary results. To illustrate the differences between our approach and previously introduced methods, we compare our method with two of the other leading methods in the literature. We also report on extensive simulations that show the effect of the values chosen for each proposed safety constraint bound on the optimized stimulus patterns. Significance. The proposed optimization approach employs volume based ROIs, easily adapts to different sets of safety constraints, and takes negligible time to compute. An in-depth comparison study gives

A novel neural prosthesis providing long-term electrocorticography recording and cortical stimulation for epilepsy and brain-computer interface.

Science.gov (United States)

Romanelli, Pantaleo; Piangerelli, Marco; Ratel, David; Gaude, Christophe; Costecalde, Thomas; Puttilli, Cosimo; Picciafuoco, Mauro; Benabid, Alim; Torres, Napoleon

2018-05-11

OBJECTIVE Wireless technology is a novel tool for the transmission of cortical signals. Wireless electrocorticography (ECoG) aims to improve the safety and diagnostic gain of procedures requiring invasive localization of seizure foci and also to provide long-term recording of brain activity for brain-computer interfaces (BCIs). However, no wireless devices aimed at these clinical applications are currently available. The authors present the application of a fully implantable and externally rechargeable neural prosthesis providing wireless ECoG recording and direct cortical stimulation (DCS). Prolonged wireless ECoG monitoring was tested in nonhuman primates by using a custom-made device (the ECoG implantable wireless 16-electrode [ECOGIW-16E] device) containing a 16-contact subdural grid. This is a preliminary step toward large-scale, long-term wireless ECoG recording in humans. METHODS The authors implanted the ECOGIW-16E device over the left sensorimotor cortex of a nonhuman primate ( Macaca fascicularis), recording ECoG signals over a time span of 6 months. Daily electrode impedances were measured, aiming to maintain the impedance values below a threshold of 100 KΩ. Brain mapping was obtained through wireless cortical stimulation at fixed intervals (1, 3, and 6 months). After 6 months, the device was removed. The authors analyzed cortical tissues by using conventional histological and immunohistological investigation to assess whether there was evidence of damage after the long-term implantation of the grid. RESULTS The implant was well tolerated; no neurological or behavioral consequences were reported in the monkey, which resumed his normal activities within a few hours of the procedure. The signal quality of wireless ECoG remained excellent over the 6-month observation period. Impedance values remained well below the threshold value; the average impedance per contact remains approximately 40 KΩ. Wireless cortical stimulation induced movements of the upper

Novel high-voltage power lateral MOSFET with adaptive buried electrodes

International Nuclear Information System (INIS)

Zhang Wen-Tong; Wu Li-Juan; Qiao Ming; Luo Xiao-Rong; Zhang Bo; Li Zhao-Ji

2012-01-01

A new high-voltage and low-specific on-resistance (R on,sp ) adaptive buried electrode (ABE) silicon-on-insulator (SOI) power lateral MOSFET and its analytical model of the electric fields are proposed. The MOSFET features are that the electrodes are in the buried oxide (BOX) layer, the negative drain voltage V d is divided into many partial voltages and the output to the electrodes is in the buried oxide layer and the potentials on the electrodes change linearly from the drain to the source. Because the interface silicon layer potentials are lower than the neighboring electrode potentials, the electronic potential wells are formed above the electrode regions, and the hole potential wells are formed in the spacing of two neighbouring electrode regions. The interface hole concentration is much higher than the electron concentration through designing the buried layer electrode potentials. Based on the interface charge enhanced dielectric layer field theory, the electric field strength in the buried layer is enhanced. The vertical electric field E I and the breakdown voltage (BV) of ABE SOI are 545 V/μm and −587 V in the 50 μm long drift region and the 1 μm thick dielectric layer, and a low R on,sp is obtained. Furthermore, the structure also alleviates the self-heating effect (SHE). The analytical model matches the simulation results. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

Incorporating an optical waveguide into a neural interface

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-08

An optical waveguide integrated into a multielectrode array (MEA) neural interface includes a device body, at least one electrode in the device body, at least one electrically conducting lead coupled to the at least one electrode, at least one optical channel in the device body, and waveguide material in the at least one optical channel. The fabrication of a neural interface device includes the steps of providing a device body, providing at least one electrode in the device body, providing at least one electrically conducting lead coupled to the at least one electrode, providing at least one optical channel in the device body, and providing a waveguide material in the at least one optical channel.

Anatomy of the western Java plate interface from depth-migrated seismic images

Science.gov (United States)

Kopp, H.; Hindle, D.; Klaeschen, D.; Oncken, O.; Reichert, C.; Scholl, D.

2009-01-01

Newly pre-stack depth-migrated seismic images resolve the structural details of the western Java forearc and plate interface. The structural segmentation of the forearc into discrete mechanical domains correlates with distinct deformation styles. Approximately 2/3 of the trench sediment fill is detached and incorporated into frontal prism imbricates, while the floor sequence is underthrust beneath the d??collement. Western Java, however, differs markedly from margins such as Nankai or Barbados, where a uniform, continuous d??collement reflector has been imaged. In our study area, the plate interface reveals a spatially irregular, nonlinear pattern characterized by the morphological relief of subducted seamounts and thicker than average patches of underthrust sediment. The underthrust sediment is associated with a low velocity zone as determined from wide-angle data. Active underplating is not resolved, but likely contributes to the uplift of the large bivergent wedge that constitutes the forearc high. Our profile is located 100 km west of the 2006 Java tsunami earthquake. The heterogeneous d??collement zone regulates the friction behavior of the shallow subduction environment where the earthquake occurred. The alternating pattern of enhanced frictional contact zones associated with oceanic basement relief and weak material patches of underthrust sediment influences seismic coupling and possibly contributed to the heterogeneous slip distribution. Our seismic images resolve a steeply dipping splay fault, which originates at the d??collement and terminates at the sea floor and which potentially contributes to tsunami generation during co-seismic activity. ?? 2009 Elsevier B.V.

Anatomy of the western Java plate interface from depth-migrated seismic images

Science.gov (United States)

Kopp, H.; Hindle, D.; Klaeschen, D.; Oncken, O.; Reichert, C.; Scholl, D.

2009-11-01

Newly pre-stack depth-migrated seismic images resolve the structural details of the western Java forearc and plate interface. The structural segmentation of the forearc into discrete mechanical domains correlates with distinct deformation styles. Approximately 2/3 of the trench sediment fill is detached and incorporated into frontal prism imbricates, while the floor sequence is underthrust beneath the décollement. Western Java, however, differs markedly from margins such as Nankai or Barbados, where a uniform, continuous décollement reflector has been imaged. In our study area, the plate interface reveals a spatially irregular, nonlinear pattern characterized by the morphological relief of subducted seamounts and thicker than average patches of underthrust sediment. The underthrust sediment is associated with a low velocity zone as determined from wide-angle data. Active underplating is not resolved, but likely contributes to the uplift of the large bivergent wedge that constitutes the forearc high. Our profile is located 100 km west of the 2006 Java tsunami earthquake. The heterogeneous décollement zone regulates the friction behavior of the shallow subduction environment where the earthquake occurred. The alternating pattern of enhanced frictional contact zones associated with oceanic basement relief and weak material patches of underthrust sediment influences seismic coupling and possibly contributed to the heterogeneous slip distribution. Our seismic images resolve a steeply dipping splay fault, which originates at the décollement and terminates at the sea floor and which potentially contributes to tsunami generation during co-seismic activity.

Long-term implantation of deep brain stimulation electrodes in the pontine micturition centre of the Göttingen minipig.

Science.gov (United States)

Jensen, Kristian N; Deding, Dorthe; Sørensen, Jens Christian; Bjarkam, Carsten R

2009-07-01

To implant deep brain stimulation (DBS) electrodes in the porcine pontine micturition centre (PMC) in order to establish a large animal model of PMC-DBS. Brain stems from four Göttingen minipigs were sectioned coronally into 40-mum-thick histological sections and stained with Nissl, auto-metallographic myelin stain, tyrosine hydroxylase and corticotrophin-releasing factor immunohistochemistry in order to identify the porcine PMC. DBS electrodes were then stereotaxically implanted on the right side into the PMC in four Göttingen minipigs, and the bladder response to electrical stimulation was evaluated by subsequent cystometry performed immediately after the operation and several weeks later. A paired CRF-dense area homologous to the PMC in other species was encountered in the rostral pontine tegmentum medial to the locus coeruleus and ventral to the floor of the fourth ventricle. Electrical stimulation of the CRF-dense area resulted in an increased detrusor pressure followed by visible voiding in some instances. The pigs were allowed to survive between 14 and 55 days, and electrical stimulation resulting in an increased detrusor pressure was performed on more than one occasion without affecting consciousness or general thriving. None of the pigs developed postoperative infections or died prematurely. DBS electrodes can be implanted for several weeks in the identified CRF-dense area resulting in a useful large animal model for basic research on micturition and the future clinical use of this treatment modality in neurogenic supra-pontine voiding disorders.

A New Generation of Brain-Computer Interfaces Driven by Discovery of Latent EEG-fMRI Linkages Using Tensor Decomposition

OpenAIRE

Gopikrishna Deshpande; Gopikrishna Deshpande; Gopikrishna Deshpande; D. Rangaprakash; D. Rangaprakash; Luke Oeding; Andrzej Cichocki; Andrzej Cichocki; Andrzej Cichocki; Xiaoping P. Hu

2017-01-01

A Brain-Computer Interface (BCI) is a setup permitting the control of external devices by decoding brain activity. Electroencephalography (EEG) has been extensively used for decoding brain activity since it is non-invasive, cheap, portable, and has high temporal resolution to allow real-time operation. Due to its poor spatial specificity, BCIs based on EEG can require extensive training and multiple trials to decode brain activity (consequently slowing down the operation of the BCI). On the o...

Hybrid Brain-Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review.

Science.gov (United States)

Hong, Keum-Shik; Khan, Muhammad Jawad

2017-01-01

In this article, non-invasive hybrid brain-computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features) relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain-computer interface (BCI) accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP) and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided.

A structural study of solid electrolyte interface on negative electrode of lithium-Ion battery by electron microscopy.

Science.gov (United States)

Matsushita, Tadashi; Watanabe, Jiro; Nakao, Tatsuya; Yamashita, Seiichi

2014-11-01

For the last decades, the performance of the lithium-ion battery (LIB) has been significantly improved and its applications have been expanding rapidly. However, its performance has yet to be enhanced.In the lithium-ion battery development, it is important to elucidate the electrode structure change in detail during the charge and discharge cycling. In particular, solid electrolyte interface (SEI) formed by decomposition of the electrolytes on the graphite negative electrode surface should play an important role for battery properties. Therefore, it is essential to control the structure and composition of SEI to improve the battery performance. Here, we conducted a scanning electron microscope (SEM) and transmission electron microscope (TEM) study to elucidate the structures of the SEI during the charge and discharge process using LiNi1/3Co1/3Mn1/3O2 [1] cathode and graphite anode. [2] Since SEI is a lithium-containing compound with high activity, it was observed without being exposed to the atmosphere. The electrodes including SEI were sampled after dismantling batteries with cutoff voltages of 3V and 4.2V for the charge process and 3V for the discharge process. Fig.1 shows SEM images of the graphite electrode surface during the charge and discharge process. The change of the SEI structure during the process was clearly observed. Further, TEM images showed that the SEI grew thicker during the charge process and becomes thinner when discharged. These results with regard to the reversible SEI structure could give a new insight for the battery development.jmicro;63/suppl_1/i21/DFU056F1F1DFU056F1Fig. 1.SEM images of the graphite electrode surface:(a) before charge process;(b) with charge-cutoff voltage of 3.0V; (c) with charge-cutoff voltage of 4.2V; (d) with discharge-cutoff voltage of 3.0V. © The Author 2014. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A High Density Electrophysiological Data Analysis System for a Peripheral Nerve Interface Communicating with Individual Neurons in the Brain

Science.gov (United States)

2016-11-14

of-the-art instrumentation to communicate with individual neurons in the brain and the peripheral nervous system. The major theme of the research is...Nerve Interface Communicating with Individual Neurons in the Brain The views, opinions and/or findings contained in this report are those of the author... Communicating with Individual Neurons in the Brain Report Title The high density electrophysiological data acquisition system obtained through this

Online LDA BASED brain-computer interface system to aid disabled people

Directory of Open Access Journals (Sweden)

Apdullah Yayık

2017-06-01

Full Text Available This paper aims to develop brain-computer interface system based on electroencephalography that can aid disabled people in daily life. The system relies on one of the most effective event-related potential wave, P300, which can be elicited by oddball paradigm. Developed application has a basic interaction tool that enables disabled people to convey their needs to other people selecting related objects. These objects pseudo-randomly flash in a visual interface on computer screen. The user must focus on related object to convey desired needs. The system can convey desired needs correctly by detecting P300 wave in acquired 14-channel EEG signal and classifying using linear discriminant analysis classifier just in 15 seconds. Experiments have been carried out on 19 volunteers to validate developed BCI system. As a result, accuracy rate of 90.83% is achieved in online performance.

A novel high electrode count spike recording array using an 81,920 pixel transimpedance amplifier-based imaging chip.

Science.gov (United States)

Johnson, Lee J; Cohen, Ethan; Ilg, Doug; Klein, Richard; Skeath, Perry; Scribner, Dean A

2012-04-15

Microelectrode recording arrays of 60-100 electrodes are commonly used to record neuronal biopotentials, and these have aided our understanding of brain function, development and pathology. However, higher density microelectrode recording arrays of larger area are needed to study neuronal function over broader brain regions such as in cerebral cortex or hippocampal slices. Here, we present a novel design of a high electrode count picocurrent imaging array (PIA), based on an 81,920 pixel Indigo ISC9809 readout integrated circuit camera chip. While originally developed for interfacing to infrared photodetector arrays, we have adapted the chip for neuron recording by bonding it to microwire glass resulting in an array with an inter-electrode pixel spacing of 30 μm. In a high density electrode array, the ability to selectively record neural regions at high speed and with good signal to noise ratio are both functionally important. A critical feature of our PIA is that each pixel contains a dedicated low noise transimpedance amplifier (∼0.32 pA rms) which allows recording high signal to noise ratio biocurrents comparable to single electrode voltage amplifier recordings. Using selective sampling of 256 pixel subarray regions, we recorded the extracellular biocurrents of rabbit retinal ganglion cell spikes at sampling rates up to 7.2 kHz. Full array local electroretinogram currents could also be recorded at frame rates up to 100 Hz. A PIA with a full complement of 4 readout circuits would span 1cm and could acquire simultaneous data from selected regions of 1024 electrodes at sampling rates up to 9.3 kHz. Published by Elsevier B.V.

Intention concepts and brain-machine interfacing

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Franziska eThinnes-Elker

2012-11-01

Full Text Available Intentions, including their temporal properties and semantic content, are receiving increased attention, and neuroscientific studies in humans vary with respect to the topography of intention-related neural responses. This may reflect the fact that the kind of intentions investigated in one study may not be exactly the same kind investigated in the other. Fine-grained intention taxonomies developed in the philosophy of mind may be useful to identify the neural correlates of well-defined types of intentions, as well as to disentangle them from other related mental states, such as mere urges to perform an action. Intention-related neural signals may be exploited by brain-machine interfaces (BMIs that are currently being developed to restore speech and motor control in paralyzed subjects. Such BMI devices record the brain activity of the agent, interpret (‘decode’ the agent’s intended action, and send the corresponding execution command to an artificial effector system, e.g., a computer cursor or a robotic arm. In the present paper, we evaluate the potential of intention concepts from philosophy of mind to improve the performance and safety of BMIs based on higher-order, intention-related control signals. To this end, we address the distinction between future-, present-directed, and motor intentions, as well as the organization of intentions in time, specifically to what extent it is sequential or hierarchical. This has consequences as to whether these different types of intentions can be expected to occur simultaneously or not. We further illustrate how it may be useful or even necessary to distinguish types of intentions exposited in philosophy, including yes- vs. no-intentions and oblique vs. direct intentions, to accurately decode the agent’s intentions from neural signals in practical BMI applications.

Intention concepts and brain-machine interfacing.

Science.gov (United States)

Thinnes-Elker, Franziska; Iljina, Olga; Apostolides, John Kyle; Kraemer, Felicitas; Schulze-Bonhage, Andreas; Aertsen, Ad; Ball, Tonio

2012-01-01

Intentions, including their temporal properties and semantic content, are receiving increased attention, and neuroscientific studies in humans vary with respect to the topography of intention-related neural responses. This may reflect the fact that the kind of intentions investigated in one study may not be exactly the same kind investigated in the other. Fine-grained intention taxonomies developed in the philosophy of mind may be useful to identify the neural correlates of well-defined types of intentions, as well as to disentangle them from other related mental states, such as mere urges to perform an action. Intention-related neural signals may be exploited by brain-machine interfaces (BMIs) that are currently being developed to restore speech and motor control in paralyzed patients. Such BMI devices record the brain activity of the agent, interpret ("decode") the agent's intended action, and send the corresponding execution command to an artificial effector system, e.g., a computer cursor or a robotic arm. In the present paper, we evaluate the potential of intention concepts from philosophy of mind to improve the performance and safety of BMIs based on higher-order, intention-related control signals. To this end, we address the distinction between future-, present-directed, and motor intentions, as well as the organization of intentions in time, specifically to what extent it is sequential or hierarchical. This has consequences as to whether these different types of intentions can be expected to occur simultaneously or not. We further illustrate how it may be useful or even necessary to distinguish types of intentions exposited in philosophy, including yes- vs. no-intentions and oblique vs. direct intentions, to accurately decode the agent's intentions from neural signals in practical BMI applications.

Brain-computer interface: changes in performance using virtual reality techniques.

Science.gov (United States)

Ron-Angevin, Ricardo; Díaz-Estrella, Antonio

2009-01-09

The ability to control electroencephalographic (EEG) signals when different mental tasks are carried out would provide a method of communication for people with serious motor function problems. This system is known as a brain-computer interface (BCI). Due to the difficulty of controlling one's own EEG signals, a suitable training protocol is required to motivate subjects, as it is necessary to provide some type of visual feedback allowing subjects to see their progress. Conventional systems of feedback are based on simple visual presentations, such as a horizontal bar extension. However, virtual reality is a powerful tool with graphical possibilities to improve BCI-feedback presentation. The objective of the study is to explore the advantages of the use of feedback based on virtual reality techniques compared to conventional systems of feedback. Sixteen untrained subjects, divided into two groups, participated in the experiment. A group of subjects was trained using a BCI system, which uses conventional feedback (bar extension), and another group was trained using a BCI system, which submits subjects to a more familiar environment, such as controlling a car to avoid obstacles. The obtained results suggest that EEG behaviour can be modified via feedback presentation. Significant differences in classification error rates between both interfaces were obtained during the feedback period, confirming that an interface based on virtual reality techniques can improve the feedback control, specifically for untrained subjects.

EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone

OpenAIRE

Blum, Sarah; Debener, Stefan; Emkes, Reiner; Volkening, Nils; Fudickar, Sebastian; Bleichner, Martin G.

2017-01-01

Objective. Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach. In order to implement a closed-loop brain-computer interface (BCI) on the sma...

Brain-computer interface using P300 and virtual reality: A gaming approach for treating ADHD

DEFF Research Database (Denmark)

Rohani, Darius Adam; Sørensen, Helge Bjarup Dissing; Puthusserypady, Sadasivan

2014-01-01

This paper presents a novel brain-computer interface (BCI) system aiming at the rehabilitation of attention-deficit/hyperactive disorder in children. It uses the P300 potential in a series of feedback games to improve the subjects' attention. We applied a support vector machine (SVM) using temporal...

Proprioceptive feedback and brain computer interface (BCI based neuroprostheses.

Directory of Open Access Journals (Sweden)

Ander Ramos-Murguialday

Full Text Available Brain computer interface (BCI technology has been proposed for motor neurorehabilitation, motor replacement and assistive technologies. It is an open question whether proprioceptive feedback affects the regulation of brain oscillations and therefore BCI control. We developed a BCI coupled on-line with a robotic hand exoskeleton for flexing and extending the fingers. 24 healthy participants performed five different tasks of closing and opening the hand: (1 motor imagery of the hand movement without any overt movement and without feedback, (2 motor imagery with movement as online feedback (participants see and feel their hand, with the exoskeleton moving according to their brain signals, (3 passive (the orthosis passively opens and closes the hand without imagery and (4 active (overt movement of the hand and rest. Performance was defined as the difference in power of the sensorimotor rhythm during motor task and rest and calculated offline for different tasks. Participants were divided in three groups depending on the feedback receiving during task 2 (the other tasks were the same for all participants. Group 1 (n = 9 received contingent positive feedback (participants' sensorimotor rhythm (SMR desynchronization was directly linked to hand orthosis movements, group 2 (n = 8 contingent "negative" feedback (participants' sensorimotor rhythm synchronization was directly linked to hand orthosis movements and group 3 (n = 7 sham feedback (no link between brain oscillations and orthosis movements. We observed that proprioceptive feedback (feeling and seeing hand movements improved BCI performance significantly. Furthermore, in the contingent positive group only a significant motor learning effect was observed enhancing SMR desynchronization during motor imagery without feedback in time. Furthermore, we observed a significantly stronger SMR desynchronization in the contingent positive group compared to the other groups during active and

Proprioceptive feedback and brain computer interface (BCI) based neuroprostheses.

Science.gov (United States)

Ramos-Murguialday, Ander; Schürholz, Markus; Caggiano, Vittorio; Wildgruber, Moritz; Caria, Andrea; Hammer, Eva Maria; Halder, Sebastian; Birbaumer, Niels

2012-01-01

Brain computer interface (BCI) technology has been proposed for motor neurorehabilitation, motor replacement and assistive technologies. It is an open question whether proprioceptive feedback affects the regulation of brain oscillations and therefore BCI control. We developed a BCI coupled on-line with a robotic hand exoskeleton for flexing and extending the fingers. 24 healthy participants performed five different tasks of closing and opening the hand: (1) motor imagery of the hand movement without any overt movement and without feedback, (2) motor imagery with movement as online feedback (participants see and feel their hand, with the exoskeleton moving according to their brain signals, (3) passive (the orthosis passively opens and closes the hand without imagery) and (4) active (overt) movement of the hand and rest. Performance was defined as the difference in power of the sensorimotor rhythm during motor task and rest and calculated offline for different tasks. Participants were divided in three groups depending on the feedback receiving during task 2 (the other tasks were the same for all participants). Group 1 (n = 9) received contingent positive feedback (participants' sensorimotor rhythm (SMR) desynchronization was directly linked to hand orthosis movements), group 2 (n = 8) contingent "negative" feedback (participants' sensorimotor rhythm synchronization was directly linked to hand orthosis movements) and group 3 (n = 7) sham feedback (no link between brain oscillations and orthosis movements). We observed that proprioceptive feedback (feeling and seeing hand movements) improved BCI performance significantly. Furthermore, in the contingent positive group only a significant motor learning effect was observed enhancing SMR desynchronization during motor imagery without feedback in time. Furthermore, we observed a significantly stronger SMR desynchronization in the contingent positive group compared to the other groups during active and passive

Gaze-and-brain-controlled interfaces for human-computer and human-robot interaction

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Shishkin S. L.

2017-09-01

Full Text Available Background. Human-machine interaction technology has greatly evolved during the last decades, but manual and speech modalities remain single output channels with their typical constraints imposed by the motor system’s information transfer limits. Will brain-computer interfaces (BCIs and gaze-based control be able to convey human commands or even intentions to machines in the near future? We provide an overview of basic approaches in this new area of applied cognitive research. Objective. We test the hypothesis that the use of communication paradigms and a combination of eye tracking with unobtrusive forms of registering brain activity can improve human-machine interaction. Methods and Results. Three groups of ongoing experiments at the Kurchatov Institute are reported. First, we discuss the communicative nature of human-robot interaction, and approaches to building a more e cient technology. Specifically, “communicative” patterns of interaction can be based on joint attention paradigms from developmental psychology, including a mutual “eye-to-eye” exchange of looks between human and robot. Further, we provide an example of “eye mouse” superiority over the computer mouse, here in emulating the task of selecting a moving robot from a swarm. Finally, we demonstrate a passive, noninvasive BCI that uses EEG correlates of expectation. This may become an important lter to separate intentional gaze dwells from non-intentional ones. Conclusion. The current noninvasive BCIs are not well suited for human-robot interaction, and their performance, when they are employed by healthy users, is critically dependent on the impact of the gaze on selection of spatial locations. The new approaches discussed show a high potential for creating alternative output pathways for the human brain. When support from passive BCIs becomes mature, the hybrid technology of the eye-brain-computer (EBCI interface will have a chance to enable natural, fluent, and the

A CMOS pressure sensor with integrated interface for passive RFID applications

International Nuclear Information System (INIS)

Deng, Fangming; He, Yigang; Wu, Xiang; Fu, Zhihui

2014-01-01

This paper presents a CMOS pressure sensor with integrated interface for passive RFID sensing applications. The pressure sensor consists of three parts: top electrode, dielectric layer and bottom electrode. The dielectric layer consists of silicon oxide and an air gap. The bottom electrode is made of polysilicon. The gap is formed by sacrificial layer release and the Al vapor process is used to seal the gap and form the top electrode. The sensor interface is based on phase-locked architecture, which allows the use of fully digital blocks. The proposed pressure sensor and interface is fabricated in a 0.18 μm CMOS process. The measurement results show the pressure sensor achieves excellent linearity with a sensitivity of 1.2 fF kPa −1 . The sensor interface consumes only 1.1 µW of power at 0.5 V voltage supply, which is at least an order of magnitude better than state-of-the-art designs. (paper)

Brain-computer interface research a state-of-the-art summary 3

CERN Document Server

Guger, Christoph; Allison, Brendan

2014-01-01

This book provides a cutting-edge overview of the latest developments in Brain-Computer-Interfaces (BCIs), reported by leading research groups. As the reader will discover, BCI research is moving ahead rapidly, with many new ideas, research initiatives, and improved technologies, e.g. BCIs that enable people to communicate just by thinking - without any movement at all. Several different groups are helping severely disabled users communicate using BCIs, and BCI technology is also being extended to facilitate recovery from stroke, epilepsy, and other conditions. Each year, hundreds of the top

Brain Computer Interface for Micro-controller Driven Robot Based on Emotiv Sensors

OpenAIRE

Parth Gargava; Krishna Asawa

2017-01-01

A Brain Computer Interface (BCI) is developed to navigate a micro-controller based robot using Emotiv sensors. The BCI system has a pipeline of 5 stages- signal acquisition, pre-processing, feature extraction, classification and CUDA inter- facing. It shall aid in serving a prototype for physical movement of neurological patients who are unable to control or operate on their muscular movements. All stages of the pipeline are designed to process bodily actions like eye blinks to command naviga...

Helium Ion Microscopy of proton exchange membrane fuel cell electrode structures

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Serguei Chiriaev

2017-12-01

Full Text Available Characterization of composite materials with microscopy techniques is an essential route to understanding their properties and degradation mechanisms, though the observation with a suitable type of microscopy is not always possible. In this work, we present proton exchange membrane fuel cell electrode interface structure dependence on ionomer content, systematically studied by Helium Ion Microscopy (HIM. A special focus was on acquiring high resolution images of the electrode structure and avoiding interface damage from irradiation and tedious sample preparation. HIM demonstrated its advantages in surface imaging, which is paramount in studies of the interface morphology of ionomer covered or absorbed catalyst structures in a combination with electrochemical characterization and accelerated stress test. The electrode porosity was found to depend on the ionomer content. The stressed electrodes demonstrated higher porosity in comparison to the unstressed ones on the condition of no external mechanical pressure. Moreover, formation of additional small grains was observed for the electrodes with the low ionomer content, indicating Pt redeposition through Ostwald ripening. Polymer nanofiber structures were found in the crack regions of the catalyst layer, which appear due to the internal stress originated from the solvent evaporation. These fibers have fairly uniform diameters of a few tens of nanometers, and their density increases with the increasing ionomer content in the electrodes. In the hot-pressed electrodes, we found more closed contact between the electrode components, reduced particle size, polymer coalescence and formation of nano-sized polymer fiber architecture between the particles.