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.

Distributed user interfaces for clinical ubiquitous computing applications.

Science.gov (United States)

Bång, Magnus; Larsson, Anders; Berglund, Erik; Eriksson, Henrik

2005-08-01

Ubiquitous computing with multiple interaction devices requires new interface models that support user-specific modifications to applications and facilitate the fast development of active workspaces. We have developed NOSTOS, a computer-augmented work environment for clinical personnel to explore new user interface paradigms for ubiquitous computing. NOSTOS uses several devices such as digital pens, an active desk, and walk-up displays that allow the system to track documents and activities in the workplace. We present the distributed user interface (DUI) model that allows standalone applications to distribute their user interface components to several devices dynamically at run-time. This mechanism permit clinicians to develop their own user interfaces and forms to clinical information systems to match their specific needs. We discuss the underlying technical concepts of DUIs and show how service discovery, component distribution, events and layout management are dealt with in the NOSTOS system. Our results suggest that DUIs--and similar network-based user interfaces--will be a prerequisite of future mobile user interfaces and essential to develop clinical multi-device environments.

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.

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

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

Human-Computer Interfaces for Wearable Computers: A Systematic Approach to Development and Evaluation

OpenAIRE

Witt, Hendrik

2007-01-01

The research presented in this thesis examines user interfaces for wearable computers.Wearable computers are a special kind of mobile computers that can be worn on the body. Furthermore, they integrate themselves even more seamlessly into different activities than a mobile phone or a personal digital assistant can.The thesis investigates the development and evaluation of user interfaces for wearable computers. In particular, it presents fundamental research results as well as supporting softw...

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.

Integrated multimodal human-computer interface and augmented reality for interactive display applications

Science.gov (United States)

Vassiliou, Marius S.; Sundareswaran, Venkataraman; Chen, S.; Behringer, Reinhold; Tam, Clement K.; Chan, M.; Bangayan, Phil T.; McGee, Joshua H.

2000-08-01

We describe new systems for improved integrated multimodal human-computer interaction and augmented reality for a diverse array of applications, including future advanced cockpits, tactical operations centers, and others. We have developed an integrated display system featuring: speech recognition of multiple concurrent users equipped with both standard air- coupled microphones and novel throat-coupled sensors (developed at Army Research Labs for increased noise immunity); lip reading for improving speech recognition accuracy in noisy environments, three-dimensional spatialized audio for improved display of warnings, alerts, and other information; wireless, coordinated handheld-PC control of a large display; real-time display of data and inferences from wireless integrated networked sensors with on-board signal processing and discrimination; gesture control with disambiguated point-and-speak capability; head- and eye- tracking coupled with speech recognition for 'look-and-speak' interaction; and integrated tetherless augmented reality on a wearable computer. The various interaction modalities (speech recognition, 3D audio, eyetracking, etc.) are implemented a 'modality servers' in an Internet-based client-server architecture. Each modality server encapsulates and exposes commercial and research software packages, presenting a socket network interface that is abstracted to a high-level interface, minimizing both vendor dependencies and required changes on the client side as the server's technology improves.

Computational design of patterned interfaces using reduced order models

International Nuclear Information System (INIS)

Vattre, A.J.; Abdolrahim, N.; Kolluri, K.; Demkowicz, M.J.

2014-01-01

Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids. Many interfaces have non-uniform internal structures comprised of misfit dislocations, which in turn govern interface properties. We develop and validate a computational strategy for designing interfaces with controlled misfit dislocation patterns by tailoring interface crystallography and composition. Our approach relies on a novel method for predicting the internal structure of interfaces: rather than obtaining it from resource-intensive atomistic simulations, we compute it using an efficient reduced order model based on anisotropic elasticity theory. Moreover, our strategy incorporates interface synthesis as a constraint on the design process. As an illustration, we apply our approach to the design of interfaces with rapid, 1-D point defect diffusion. Patterned interfaces may be integrated into the microstructure of composite materials, markedly improving performance. (authors)

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.

Brain-computer interfacing under distraction: an evaluation study

Science.gov (United States)

Brandl, Stephanie; Frølich, Laura; Höhne, Johannes; Müller, Klaus-Robert; Samek, Wojciech

2016-10-01

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. This paper systematically investigates BCI performance under 6 types of distractions that mimic out-of-lab environments. Main results. We report results of 16 participants and show that the performance of the standard common spatial patterns (CSP) + regularized linear discriminant analysis classification pipeline drops significantly in this ‘simulated’ out-of-lab setting. We then investigate three methods for improving the performance: (1) artifact removal, (2) ensemble classification, and (3) a 2-step classification approach. While artifact removal does not enhance the BCI performance significantly, both ensemble classification and the 2-step classification combined with CSP significantly improve the performance compared to the standard procedure. Significance. Systematically analyzing out-of-lab scenarios is crucial when bringing BCI into everyday life. Algorithms must be adapted to overcome nonstationary environments in order to tackle real-world challenges.

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

Science.gov (United States)

... 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 ...

Computer-Based Tools for Evaluating Graphical User Interfaces

Science.gov (United States)

Moore, Loretta A.

1997-01-01

The user interface is the component of a software system that connects two very complex system: humans and computers. Each of these two systems impose certain requirements on the final product. The user is the judge of the usability and utility of the system; the computer software and hardware are the tools with which the interface is constructed. Mistakes are sometimes made in designing and developing user interfaces because the designers and developers have limited knowledge about human performance (e.g., problem solving, decision making, planning, and reasoning). Even those trained in user interface design make mistakes because they are unable to address all of the known requirements and constraints on design. Evaluation of the user inter-face is therefore a critical phase of the user interface development process. Evaluation should not be considered the final phase of design; but it should be part of an iterative design cycle with the output of evaluation being feed back into design. The goal of this research was to develop a set of computer-based tools for objectively evaluating graphical user interfaces. The research was organized into three phases. The first phase resulted in the development of an embedded evaluation tool which evaluates the usability of a graphical user interface based on a user's performance. An expert system to assist in the design and evaluation of user interfaces based upon rules and guidelines was developed during the second phase. During the final phase of the research an automatic layout tool to be used in the initial design of graphical inter- faces was developed. The research was coordinated with NASA Marshall Space Flight Center's Mission Operations Laboratory's efforts in developing onboard payload display specifications for the Space Station.

Guidelines for the integration of audio cues into computer user interfaces

Energy Technology Data Exchange (ETDEWEB)

Sumikawa, D.A.

1985-06-01

Throughout the history of computers, vision has been the main channel through which information is conveyed to the computer user. As the complexities of man-machine interactions increase, more and more information must be transferred from the computer to the user and then successfully interpreted by the user. A logical next step in the evolution of the computer-user interface is the incorporation of sound and thereby using the sense of ''hearing'' in the computer experience. This allows our visual and auditory capabilities to work naturally together in unison leading to more effective and efficient interpretation of all information received by the user from the computer. This thesis presents an initial set of guidelines to assist interface developers in designing an effective sight and sound user interface. This study is a synthesis of various aspects of sound, human communication, computer-user interfaces, and psychoacoustics. We introduce the notion of an earcon. Earcons are audio cues used in the computer-user interface to provide information and feedback to the user about some computer object, operation, or interaction. A possible construction technique for earcons, the use of earcons in the interface, how earcons are learned and remembered, and the affects of earcons on their users are investigated. This study takes the point of view that earcons are a language and human/computer communication issue and are therefore analyzed according to the three dimensions of linguistics; syntactics, semantics, and pragmatics.

Spectrometer user interface to computer systems

International Nuclear Information System (INIS)

Salmon, L.; Davies, M.; Fry, F.A.; Venn, J.B.

1979-01-01

A computer system for use in radiation spectrometry should be designed around the needs and comprehension of the user and his operating environment. To this end, the functions of the system should be built in a modular and independent fashion such that they can be joined to the back end of an appropriate user interface. The point that this interface should be designed rather than just allowed to evolve is illustrated by reference to four related computer systems of differing complexity and function. The physical user interfaces in all cases are keyboard terminals, and the virtues and otherwise of these devices are discussed and compared with others. The language interface needs to satisfy a number of requirements, often conflicting. Among these, simplicity and speed of operation compete with flexibility and scope. Both experienced and novice users need to be considered, and any individual's needs may vary from naive to complex. To be efficient and resilient, the implementation must use an operating system, but the user needs to be protected from its complex and unfamiliar syntax. At the same time the interface must allow the user access to all services appropriate to his needs. The user must also receive an image of privacy in a multi-user system. The interface itself must be stable and exhibit continuity between implementations. Some of these conflicting needs have been overcome by the SABRE interface with languages operating at several levels. The foundation is a simple semimnemonic command language that activates indididual and independent functions. The commands can be used with positional parameters or in an interactive dialogue the precise nature of which depends upon the operating environment and the user's experience. A command procedure or macrolanguage allows combinations of commands with conditional branching and arithmetic features. Thus complex but repetitive operations are easily performed

Brain-computer interfaces for arts

NARCIS (Netherlands)

Gürkök, Hayrettin; Nijholt, Antinus; D' Mello, S.; Pantic, Maja

2013-01-01

We experience positive emotions when our hedonic needs, such as virtuosity or relatedness, are satisfied. Creating art is one way of satisfying these needs, so artistic computer applications can be considered as ‘affective’. Artistic braincomputer interfaces (BCIs), which allow people to create art

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

Investigation of different classifiers and channel configurations of a mobile P300-based brain-computer interface.

Science.gov (United States)

Ludwig, Simone A; Kong, Jun

2017-12-01

Innovative methods and new technologies have significantly improved the quality of our daily life. However, disabled people, for example those that cannot use their arms and legs anymore, often cannot benefit from these developments, since they cannot use their hands to interact with traditional interaction methods (such as mouse or keyboard) to communicate with a computer system. A brain-computer interface (BCI) system allows such a disabled person to control an external device via brain waves. Past research mostly dealt with static interfaces, which limit users to a stationary location. However, since we are living in a world that is highly mobile, this paper evaluates a speller interface on a mobile phone used in a moving condition. The spelling experiments were conducted with 14 able-bodied subjects using visual flashes as the stimulus to spell 47 alphanumeric characters (38 letters and 9 numbers). This data was then used for the classification experiments. In par- ticular, two research directions are pursued. The first investigates the impact of different classification algorithms, and the second direction looks at the channel configuration, i.e., which channels are most beneficial in terms of achieving the highest classification accuracy. The evaluation results indicate that the Bayesian Linear Discriminant Analysis algorithm achieves the best accuracy. Also, the findings of the investigation on the channel configuration, which can potentially reduce the amount of data processing on a mobile device with limited computing capacity, is especially useful in mobile BCIs.

Interfacing the Paramesh Computational Libraries to the Cactus Computational Framework, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We will design and implement an interface between the Paramesh computational libraries, developed and used by groups at NASA GSFC, and the Cactus computational...

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...

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

Digital quality control of the camera computer interface

International Nuclear Information System (INIS)

Todd-Pokropek, A.

1983-01-01

A brief description is given of how the gamma camera-computer interface works and what kind of errors can occur. Quality control tests of the interface are then described which include 1) tests of static performance e.g. uniformity, linearity, 2) tests of dynamic performance e.g. basic timing, interface count-rate, system count-rate, 3) tests of special functions e.g. gated acquisition, 4) tests of the gamma camera head, and 5) tests of the computer software. The tests described are mainly acceptance and routine tests. Many of the tests discussed are those recommended by an IAEA Advisory Group for inclusion in the IAEA control schedules for nuclear medicine instrumentation. (U.K.)

High Performance Computing - Power Application Programming Interface Specification.

Energy Technology Data Exchange (ETDEWEB)

Laros, James H.,; Kelly, Suzanne M.; Pedretti, Kevin; Grant, Ryan; Olivier, Stephen Lecler; Levenhagen, Michael J.; DeBonis, David

2014-08-01

Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area [13, 3, 5, 10, 4, 21, 19, 16, 7, 17, 20, 18, 11, 1, 6, 14, 12]. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

Man-machine interfaces analysis system based on computer simulation

International Nuclear Information System (INIS)

Chen Xiaoming; Gao Zuying; Zhou Zhiwei; Zhao Bingquan

2004-01-01

The paper depicts a software assessment system, Dynamic Interaction Analysis Support (DIAS), based on computer simulation technology for man-machine interfaces (MMI) of a control room. It employs a computer to simulate the operation procedures of operations on man-machine interfaces in a control room, provides quantified assessment, and at the same time carries out analysis on operational error rate of operators by means of techniques for human error rate prediction. The problems of placing man-machine interfaces in a control room and of arranging instruments can be detected from simulation results. DIAS system can provide good technical supports to the design and improvement of man-machine interfaces of the main control room of a nuclear power plant

A USB 2.0 computer interface for the UCO/Lick CCD cameras

Science.gov (United States)

Wei, Mingzhi; Stover, Richard J.

2004-09-01

The new UCO/Lick Observatory CCD camera uses a 200 MHz fiber optic cable to transmit image data and an RS232 serial line for low speed bidirectional command and control. Increasingly RS232 is a legacy interface supported on fewer computers. The fiber optic cable requires either a custom interface board that is plugged into the mainboard of the image acquisition computer to accept the fiber directly or an interface converter that translates the fiber data onto a widely used standard interface. We present here a simple USB 2.0 interface for the UCO/Lick camera. A single USB cable connects to the image acquisition computer and the camera's RS232 serial and fiber optic cables plug into the USB interface. Since most computers now support USB 2.0 the Lick interface makes it possible to use the camera on essentially any modern computer that has the supporting software. No hardware modifications or additions to the computer are needed. The necessary device driver software has been written for the Linux operating system which is now widely used at Lick Observatory. The complete data acquisition software for the Lick CCD camera is running on a variety of PC style computers as well as an HP laptop.

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

Rapid prototyping of an EEG-based brain-computer interface (BCI).

Science.gov (United States)

Guger, C; Schlögl, A; Neuper, C; Walterspacher, D; Strein, T; Pfurtscheller, G

2001-03-01

The electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g., late stage of amyotrophic lateral sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEG-based brain-computer interface (BCI). This paper describes a new type of BCI system that uses rapid prototyping to enable a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. Rapid prototyping is possible by using Matlab, Simulink, and the Real-Time Workshop. It is shown how to automate real-time experiments and perform the interplay between on-line experiments and offline analysis. The system is able to process multiple EEG channels on-line and operates under Windows 95 in real-time on a standard PC without an additional digital signal processor (DSP) board. The BCI can be controlled over the Internet, LAN or modem. This BCI was tested on 3 subjects whose task it was to imagine either left or right hand movement. A classification accuracy between 70% and 95% could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive (AAR) model and linear discriminant analysis (LDA).

Towards User-Friendly Spelling with an Auditory Brain-Computer Interface: The CharStreamer Paradigm

Science.gov (United States)

Höhne, Johannes; Tangermann, Michael

2014-01-01

Realizing the decoding of brain signals into control commands, brain-computer interfaces (BCI) aim to establish an alternative communication pathway for locked-in patients. In contrast to most visual BCI approaches which use event-related potentials (ERP) of the electroencephalogram, auditory BCI systems are challenged with ERP responses, which are less class-discriminant between attended and unattended stimuli. Furthermore, these auditory approaches have more complex interfaces which imposes a substantial workload on their users. Aiming for a maximally user-friendly spelling interface, this study introduces a novel auditory paradigm: “CharStreamer”. The speller can be used with an instruction as simple as “please attend to what you want to spell”. The stimuli of CharStreamer comprise 30 spoken sounds of letters and actions. As each of them is represented by the sound of itself and not by an artificial substitute, it can be selected in a one-step procedure. The mental mapping effort (sound stimuli to actions) is thus minimized. Usability is further accounted for by an alphabetical stimulus presentation: contrary to random presentation orders, the user can foresee the presentation time of the target letter sound. Healthy, normal hearing users (n = 10) of the CharStreamer paradigm displayed ERP responses that systematically differed between target and non-target sounds. Class-discriminant features, however, varied individually from the typical N1-P2 complex and P3 ERP components found in control conditions with random sequences. To fully exploit the sequential presentation structure of CharStreamer, novel data analysis approaches and classification methods were introduced. The results of online spelling tests showed that a competitive spelling speed can be achieved with CharStreamer. With respect to user rating, it clearly outperforms a control setup with random presentation sequences. PMID:24886978

TMS communications software. Volume 1: Computer interfaces

Science.gov (United States)

Brown, J. S.; Lenker, M. D.

1979-01-01

A prototype bus communications system, which is being used to support the Trend Monitoring System (TMS) as well as for evaluation of the bus concept is considered. Hardware and software interfaces to the MODCOMP and NOVA minicomputers are included. The system software required to drive the interfaces in each TMS computer is described. Documentation of other software for bus statistics monitoring and for transferring files across the bus is also included.

Interface between computational fluid dynamics (CFD) and plant analysis computer codes

International Nuclear Information System (INIS)

Coffield, R.D.; Dunckhorst, F.F.; Tomlinson, E.T.; Welch, J.W.

1993-01-01

Computational fluid dynamics (CFD) can provide valuable input to the development of advanced plant analysis computer codes. The types of interfacing discussed in this paper will directly contribute to modeling and accuracy improvements throughout the plant system and should result in significant reduction of design conservatisms that have been applied to such analyses in the past

The Impact of User Interface on Young Children’s Computational Thinking

Directory of Open Access Journals (Sweden)

Amanda Sullivan

2017-07-01

Full Text Available Aim/Purpose: Over the past few years, new approaches to introducing young children to computational thinking have grown in popularity. This paper examines the role that user interfaces have on children’s mastery of computational thinking concepts and positive interpersonal behaviors. Background: There is a growing pressure to begin teaching computational thinking at a young age. This study explores the affordances of two very different programming interfaces for teaching computational thinking: a graphical coding application on the iPad (ScratchJr and tangible programmable robotics kit (KIBO. Methodology\t: This study used a mixed-method approach to explore the learning experiences that young children have with tangible and graphical coding interfaces. A sample of children ages four to seven (N = 28 participated. Findings: Results suggest that type of user interface does have an impact on children’s learning, but is only one of many factors that affect positive academic and socio-emotional experiences. Tangible and graphical interfaces each have qualities that foster different types of learning

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

RC Circuits: Some Computer-Interfaced Experiments.

Science.gov (United States)

Jolly, Pratibha; Verma, Mallika

1994-01-01

Describes a simple computer-interface experiment for recording the response of an RC network to an arbitrary input excitation. The setup is used to pose a variety of open-ended investigations in network modeling by varying the initial conditions, input signal waveform, and the circuit topology. (DDR)

Selective sensation based brain-computer interface via mechanical vibrotactile stimulation.

Science.gov (United States)

Yao, Lin; Meng, Jianjun; Zhang, Dingguo; Sheng, Xinjun; Zhu, Xiangyang

2013-01-01

In this work, mechanical vibrotactile stimulation was applied to subjects' left and right wrist skins with equal intensity, and a selective sensation perception task was performed to achieve two types of selections similar to motor imagery Brain-Computer Interface. The proposed system was based on event-related desynchronization/synchronization (ERD/ERS), which had a correlation with processing of afferent inflow in human somatosensory system, and attentional effect which modulated the ERD/ERS. The experiments were carried out on nine subjects (without experience in selective sensation), and six of them showed a discrimination accuracy above 80%, three of them above 95%. Comparative experiments with motor imagery (with and without presence of stimulation) were also carried out, which further showed the feasibility of selective sensation as an alternative BCI task complementary to motor imagery. Specifically there was significant improvement ([Formula: see text]) from near 65% in motor imagery (with and without presence of stimulation) to above 80% in selective sensation on some subjects. The proposed BCI modality might well cooperate with existing BCI modalities in the literature in enlarging the widespread usage of BCI system.

Selective Sensation Based Brain-Computer Interface via Mechanical Vibrotactile Stimulation

Science.gov (United States)

Yao, Lin; Meng, Jianjun; Zhang, Dingguo; Sheng, Xinjun; Zhu, Xiangyang

2013-01-01

In this work, mechanical vibrotactile stimulation was applied to subjects’ left and right wrist skins with equal intensity, and a selective sensation perception task was performed to achieve two types of selections similar to motor imagery Brain-Computer Interface. The proposed system was based on event-related desynchronization/synchronization (ERD/ERS), which had a correlation with processing of afferent inflow in human somatosensory system, and attentional effect which modulated the ERD/ERS. The experiments were carried out on nine subjects (without experience in selective sensation), and six of them showed a discrimination accuracy above 80%, three of them above 95%. Comparative experiments with motor imagery (with and without presence of stimulation) were also carried out, which further showed the feasibility of selective sensation as an alternative BCI task complementary to motor imagery. Specifically there was significant improvement () from near 65% in motor imagery (with and without presence of stimulation) to above 80% in selective sensation on some subjects. The proposed BCI modality might well cooperate with existing BCI modalities in the literature in enlarging the widespread usage of BCI system. PMID:23762253

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

An online three-class Transcranial Doppler ultrasound brain computer interface.

Science.gov (United States)

Goyal, Anuja; Samadani, Ali-Akbar; Guerguerian, Anne-Marie; Chau, Tom

2016-06-01

Brain computer interfaces (BCI) can provide communication opportunities for individuals with severe motor disabilities. Transcranial Doppler ultrasound (TCD) measures cerebral blood flow velocities and can be used to develop a BCI. A previously implemented TCD BCI system used verbal and spatial tasks as control signals; however, the spatial task involved a visual cue that awkwardly diverted the user's attention away from the communication interface. Therefore, vision-independent right-lateralized tasks were investigated. Using a bilateral TCD BCI, ten participants controlled online, an on-screen keyboard using a left-lateralized task (verbal fluency), a right-lateralized task (fist motor imagery or 3D-shape tracing), and unconstrained rest. 3D-shape tracing was generally more discernible from other tasks than was fist motor imagery. Verbal fluency, 3D-shape tracing and unconstrained rest were distinguished from each other using a linear discriminant classifier, achieving a mean agreement of κ=0.43±0.17. These rates are comparable to the best offline three-class TCD BCI accuracies reported thus far. The online communication system achieved a mean information transfer rate (ITR) of 1.08±0.69bits/min with values reaching up to 2.46bits/min, thereby exceeding the ITR of previous online TCD BCIs. These findings demonstrate the potential of a three-class online TCD BCI that does not require visual task cues. Copyright © 2016 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

Electrostatics with Computer-Interfaced Charge Sensors

Science.gov (United States)

Morse, Robert A.

2006-01-01

Computer interfaced electrostatic charge sensors allow both qualitative and quantitative measurements of electrostatic charge but are quite sensitive to charges accumulating on modern synthetic materials. They need to be used with care so that students can correctly interpret their measurements. This paper describes the operation of the sensors,…

User Adapted Motor-Imaginary Brain-Computer Interface by means of EEG Channel Selection Based on Estimation of Distributed Algorithms

Directory of Open Access Journals (Sweden)

Aitzol Astigarraga

2016-01-01

Full Text Available Brain-Computer Interfaces (BCIs have become a research field with interesting applications, and it can be inferred from published papers that different persons activate different parts of the brain to perform the same action. This paper presents a personalized interface design method, for electroencephalogram- (EEG- based BCIs, based on channel selection. We describe a novel two-step method in which firstly a computationally inexpensive greedy algorithm finds an adequate search range; and, then, an Estimation of Distribution Algorithm (EDA is applied in the reduced range to obtain the optimal channel subset. The use of the EDA allows us to select the most interacting channels subset, removing the irrelevant and noisy ones, thus selecting the most discriminative subset of channels for each user improving accuracy. The method is tested on the IIIa dataset from the BCI competition III. Experimental results show that the resulting channel subset is consistent with motor-imaginary-related neurophysiological principles and, on the other hand, optimizes performance reducing the number of channels.

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

Human-computer interfaces applied to numerical solution of the Plateau problem

Science.gov (United States)

Elias Fabris, Antonio; Soares Bandeira, Ivana; Ramos Batista, Valério

2015-09-01

In this work we present a code in Matlab to solve the Problem of Plateau numerically, and the code will include human-computer interface. The Problem of Plateau has applications in areas of knowledge like, for instance, Computer Graphics. The solution method will be the same one of the Surface Evolver, but the difference will be a complete graphical interface with the user. This will enable us to implement other kinds of interface like ocular mouse, voice, touch, etc. To date, Evolver does not include any graphical interface, which restricts its use by the scientific community. Specially, its use is practically impossible for most of the Physically Challenged People.

Principles of interfacing computers to medical equipment.

Science.gov (United States)

Francis, J L; Martin, T R

1990-12-01

Table 3 shows a comparison of the interface standards considered. RS232 has the advantages of availability, flexibility and low cost. Variants on the standard overcome its limitations in data-rate and distance. The Centronics parallel standard is available on most personal computers and is particularly suitable for high data-rates over short distances. Other PC standards such as SCSI are special-purpose interfaces and therefore more difficult to use. GPIB is a robust and well-specified standard often used for the control of laboratory instruments.

Computer organization and design the hardware/software interface

CERN Document Server

Hennessy, John L

1994-01-01

Computer Organization and Design: The Hardware/Software Interface presents the interaction between hardware and software at a variety of levels, which offers a framework for understanding the fundamentals of computing. This book focuses on the concepts that are the basis for computers.Organized into nine chapters, this book begins with an overview of the computer revolution. This text then explains the concepts and algorithms used in modern computer arithmetic. Other chapters consider the abstractions and concepts in memory hierarchies by starting with the simplest possible cache. This book di

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

Digital interface for bi-directional communication between a computer and a peripheral device

Science.gov (United States)

Bond, H. H., Jr. (Inventor); Franklin, C. R.

1984-01-01

For transmission of data from the computer to the peripheral, the computer initially clears a flipflop which provides a select signal to a multiplexer. A data available signal or data strobe signal is produced while tht data is being provided to the interface. Setting of the flipflop causes a gate to provide to the peripherial a signal indicating that the interface has data available for transmission. The peripheral provides an acknowledge or strobe signal to transfer the data to the peripheral. For transmission of data from the peripheral to the computer, the computer presents the initially cleared flipflop. A data request signal from the peripheral indicates that the peripheral has data available for transmission to the computer. An acknowledge signal indicates that the interface is ready to receive data from the peripheral and to strobe that data into the interface.

Preface (to: Towards Practical Brain-Computer Interfaces)

NARCIS (Netherlands)

Allison, Brendan Z.; Dunne, Stephen; Leeb, Robert; Millán, Jose del R.; Allison, Brendan Z.; Dunne, Stephen; Leeb, Robert; Millán, Jose del R.; Nijholt, Antinus

2012-01-01

Brain–computer interface (BCI) research is advancing rapidly. The last few years have seen a dramatic rise in journal publications, academic workshops and conferences, books, new products aimed at both healthy and disabled users, research funding from different sources, and media attention. This

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

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.

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.

High Performance Computing - Power Application Programming Interface Specification Version 2.0.

Energy Technology Data Exchange (ETDEWEB)

Laros, James H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Levenhagen, Michael J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Olivier, Stephen Lecler [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pedretti, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ward, H. Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Younge, Andrew J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-03-01

Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

PHREEQCI; a graphical user interface for the geochemical computer program PHREEQC

Science.gov (United States)

Charlton, Scott R.; Macklin, Clifford L.; Parkhurst, David L.

1997-01-01

PhreeqcI is a Windows-based graphical user interface for the geochemical computer program PHREEQC. PhreeqcI provides the capability to generate and edit input data files, run simulations, and view text files containing simulation results, all within the framework of a single interface. PHREEQC is a multipurpose geochemical program that can perform speciation, inverse, reaction-path, and 1D advective reaction-transport modeling. Interactive access to all of the capabilities of PHREEQC is available with PhreeqcI. The interface is written in Visual Basic and will run on personal computers under the Windows(3.1), Windows95, and WindowsNT operating systems.

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

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

A computational method for sharp interface advection

DEFF Research Database (Denmark)

Roenby, Johan; Bredmose, Henrik; Jasak, Hrvoje

2016-01-01

We devise a numerical method for passive advection of a surface, such as the interface between two incompressible fluids, across a computational mesh. The method is called isoAdvector, and is developed for general meshes consisting of arbitrary polyhedral cells. The algorithm is based on the volu...

Cost-effective computations with boundary interface operators in elliptic problems

International Nuclear Information System (INIS)

Khoromskij, B.N.; Mazurkevich, G.E.; Nikonov, E.G.

1993-01-01

The numerical algorithm for fast computations with interface operators associated with the elliptic boundary value problems (BVP) defined on step-type domains is presented. The algorithm is based on the asymptotically almost optimal technique developed for treatment of the discrete Poincare-Steklov (PS) operators associated with the finite-difference Laplacian on rectangles when using the uniform grid with a 'displacement by h/2'. The approach can be regarded as an extension of the method proposed for the partial solution of the finite-difference Laplace equation to the case of displaced grids and mixed boundary conditions. It is shown that the action of the PS operator for the Dirichlet problem and mixed BVP can be computed with expenses of the order of O(Nlog 2 N) both for arithmetical operations and computer memory needs, where N is the number of unknowns on the rectangle boundary. The single domain algorithm is applied to solving the multidomain elliptic interface problems with piecewise constant coefficients. The numerical experiments presented confirm almost linear growth of the computational costs and memory needs with respect to the dimension of the discrete interface problem. 14 refs., 3 figs., 4 tabs

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

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.

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.

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.

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.

Usability of Three Electroencephalogram Headsets for Brain-Computer Interfaces: A Within Subject Comparison

NARCIS (Netherlands)

Gamboa, H.; Nijboer, Femke; van de Laar, B.L.A.; Plácido da Silva, H.; Gilleade, K.; Gerritsen, Steven; Nijholt, Antinus; Bermúdez i Badia, S.; Poel, Mannes; Fairclough, S.

Currently the field of brain–computer interfacing is increasingly focused on developing usable brain–computer interfaces (BCIs) to better ensure technology transfer and acceptance. Many studies have investigated the usability of BCI applications as a whole. Here we aim to investigate one specific

Workshops of the Sixth International Brain–Computer Interface Meeting: brain–computer interfaces past, present, and future

Science.gov (United States)

Huggins, Jane E.; Guger, Christoph; Ziat, Mounia; Zander, Thorsten O.; Taylor, Denise; Tangermann, Michael; Soria-Frisch, Aureli; Simeral, John; Scherer, Reinhold; Rupp, Rüdiger; Ruffini, Giulio; Robinson, Douglas K. R.; Ramsey, Nick F.; Nijholt, Anton; Müller-Putz, Gernot; McFarland, Dennis J.; Mattia, Donatella; Lance, Brent J.; Kindermans, Pieter-Jan; Iturrate, Iñaki; Herff, Christian; Gupta, Disha; Do, An H.; Collinger, Jennifer L.; Chavarriaga, Ricardo; Chase, Steven M.; Bleichner, Martin G.; Batista, Aaron; Anderson, Charles W.; Aarnoutse, Erik J.

2017-01-01

The Sixth International Brain–Computer Interface (BCI) Meeting was held 30 May–3 June 2016 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 28 workshops covering topics in BCI and brain–machine interface research. Topics included BCI for specific populations or applications, advancing BCI research through use of specific signals or technological advances, and translational and commercial issues to bring both implanted and non-invasive BCIs to market. BCI research is growing and expanding in the breadth of its applications, the depth of knowledge it can produce, and the practical benefit it can provide both for those with physical impairments and the general public. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and highlighting important issues and calls for action to support future research and development. PMID:29152523

Workshops of the Sixth International Brain-Computer Interface Meeting: brain-computer interfaces past, present, and future.

Science.gov (United States)

Huggins, Jane E; Guger, Christoph; Ziat, Mounia; Zander, Thorsten O; Taylor, Denise; Tangermann, Michael; Soria-Frisch, Aureli; Simeral, John; Scherer, Reinhold; Rupp, Rüdiger; Ruffini, Giulio; Robinson, Douglas K R; Ramsey, Nick F; Nijholt, Anton; Müller-Putz, Gernot; McFarland, Dennis J; Mattia, Donatella; Lance, Brent J; Kindermans, Pieter-Jan; Iturrate, Iñaki; Herff, Christian; Gupta, Disha; Do, An H; Collinger, Jennifer L; Chavarriaga, Ricardo; Chase, Steven M; Bleichner, Martin G; Batista, Aaron; Anderson, Charles W; Aarnoutse, Erik J

2017-01-01

The Sixth International Brain-Computer Interface (BCI) Meeting was held 30 May-3 June 2016 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 28 workshops covering topics in BCI and brain-machine interface research. Topics included BCI for specific populations or applications, advancing BCI research through use of specific signals or technological advances, and translational and commercial issues to bring both implanted and non-invasive BCIs to market. BCI research is growing and expanding in the breadth of its applications, the depth of knowledge it can produce, and the practical benefit it can provide both for those with physical impairments and the general public. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and highlighting important issues and calls for action to support future research and development.

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.

APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

DEFF Research Database (Denmark)

Sonnenwald, Diane H.

1988-01-01

A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

Human-computer interface incorporating personal and application domains

Science.gov (United States)

Anderson, Thomas G [Albuquerque, NM

2011-03-29

The present invention provides a human-computer interface. The interface includes provision of an application domain, for example corresponding to a three-dimensional application. The user is allowed to navigate and interact with the application domain. The interface also includes a personal domain, offering the user controls and interaction distinct from the application domain. The separation into two domains allows the most suitable interface methods in each: for example, three-dimensional navigation in the application domain, and two- or three-dimensional controls in the personal domain. Transitions between the application domain and the personal domain are under control of the user, and the transition method is substantially independent of the navigation in the application domain. For example, the user can fly through a three-dimensional application domain, and always move to the personal domain by moving a cursor near one extreme of the display.

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.

Nanostructured interfaces for enhancing mechanical properties of composites: Computational micromechanical studies

DEFF Research Database (Denmark)

Mishnaevsky, Leon

2015-01-01

Computational micromechanical studies of the effect of nanostructuring and nanoengineering of interfaces, phase and grain boundaries of materials on the mechanical properties and strength of materials and the potential of interface nanostructuring to enhance the materials properties are reviewed....

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.

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...

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

High Performance Computing - Power Application Programming Interface Specification Version 1.4

Energy Technology Data Exchange (ETDEWEB)

Laros III, James H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); DeBonis, David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kelly, Suzanne M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Levenhagen, Michael J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Olivier, Stephen Lecler [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pedretti, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-10-01

Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area [13, 3, 5, 10, 4, 21, 19, 16, 7, 17, 20, 18, 11, 1, 6, 14, 12]. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

A Gaussian mixture model based adaptive classifier for fNIRS brain-computer interfaces and its testing via simulation

Science.gov (United States)

Li, Zheng; Jiang, Yi-han; Duan, Lian; Zhu, Chao-zhe

2017-08-01

Objective. Functional near infra-red spectroscopy (fNIRS) is a promising brain imaging technology for brain-computer interfaces (BCI). Future clinical uses of fNIRS will likely require operation over long time spans, during which neural activation patterns may change. However, current decoders for fNIRS signals are not designed to handle changing activation patterns. The objective of this study is to test via simulations a new adaptive decoder for fNIRS signals, the Gaussian mixture model adaptive classifier (GMMAC). Approach. GMMAC can simultaneously classify and track activation pattern changes without the need for ground-truth labels. This adaptive classifier uses computationally efficient variational Bayesian inference to label new data points and update mixture model parameters, using the previous model parameters as priors. We test GMMAC in simulations in which neural activation patterns change over time and compare to static decoders and unsupervised adaptive linear discriminant analysis classifiers. Main results. Our simulation experiments show GMMAC can accurately decode under time-varying activation patterns: shifts of activation region, expansions of activation region, and combined contractions and shifts of activation region. Furthermore, the experiments show the proposed method can track the changing shape of the activation region. Compared to prior work, GMMAC performed significantly better than the other unsupervised adaptive classifiers on a difficult activation pattern change simulation: 99% versus  brain-computer interfaces, including neurofeedback training systems, where operation over long time spans is required.

CAMAPPLE: CAMAC interface to the Apple computer

International Nuclear Information System (INIS)

Oxoby, G.J.; Trang, Q.H.; Williams, S.H.

1981-04-01

The advent of the personal microcomputer provides a new tool for the debugging, calibration and monitoring of small scale physics apparatus, e.g., a single detector being developed for a larger physics apparatus. With an appropriate interface these microcomputer systems provide a low cost (1/3 the cost of a comparable minicomputer system), convenient, dedicated, portable system which can be used in a fashion similar to that of portable oscilloscopes. Here, an interface between the Apple computer and CAMAC which is now being used to study the detector for a Cerenkov ring-imaging device is described. The Apple is particularly well-suited to this application because of its ease of use, hi-resolution graphics, peripheral bus and documentation support

Interfacing computers and the internet with your allergy practice.

Science.gov (United States)

Bernstein, Jonathan A

2004-10-01

Computers and the internet have begun to play a prominent role in the medical profession and, in particular, the allergy specialty. Computer technology is being used more frequently for patient and physician education, asthma management in children and adults, including environmental control, generating patient databases for research and clinical practice and in marketing and e-commerce. This article will review how computers and the internet have begun to interface with the allergy subspecialty practice in these various areas.

Personal computer interface for temmperature measuring in the cutting process with turning

International Nuclear Information System (INIS)

Trajchevski, Neven; Filipovski, Velimir; Kuzinonovski, Mikolaj

2004-01-01

The computer development aided reserch systems in the investigations of the characteristics of the surface layar forms conditions for decreasing of the measuring uncertainty. Especially important is the fact that the usage of open and self made measuring systems accomplishes the demands for a total control of the research process. This paper describes an original personal computer interface which is used in the newly built computer aided reserrch system for temperatute measuring in the machining with turning. This interface consists of optically-coupled linear isolation amplifier and an analog to digital (A/D) converter. It is designed for measuring of the themo- voltage that is a generated from the natural thermocouple workpiece-cutting tool. That is achived by digitalizing the value of the thermo-voltage in data which is transmitted to the personal computer. The interface realization is a result of the research activity of the faculty of Mechanical Engineering and the Faculty of Electrical Engineering in Skopje.

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...

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

The Impact of User Interface on Young Children's Computational Thinking

Science.gov (United States)

Pugnali, Alex; Sullivan, Amanda; Bers, Marina Umaschi

2017-01-01

Aim/Purpose: Over the past few years, new approaches to introducing young children to computational thinking have grown in popularity. This paper examines the role that user interfaces have on children's mastery of computational thinking concepts and positive interpersonal behaviors. Background: There is a growing pressure to begin teaching…

Conditional associative learning examined in a paralyzed patient with amyotrophic lateral sclerosis using brain-computer interface technology

Directory of Open Access Journals (Sweden)

Birbaumer N

2008-11-01

Full Text Available Abstract Background Brain-computer interface methodology based on self-regulation of slow-cortical potentials (SCPs of the EEG (electroencephalogram was used to assess conditional associative learning in one severely paralyzed, late-stage ALS patient. After having been taught arbitrary stimulus relations, he was evaluated for formation of equivalence classes among the trained stimuli. Methods A monitor presented visual information in two targets. The method of teaching was matching to sample. Three types of stimuli were presented: signs (A, colored disks (B, and geometrical shapes (C. The sample was one type, and the choice was between two stimuli from another type. The patient used his SCP to steer a cursor to one of the targets. A smiley was presented as a reward when he hit the correct target. The patient was taught A-B and B-C (sample – comparison matching with three stimuli of each type. Tests for stimulus equivalence involved the untaught B-A, C-B, A-C, and C-A relations. An additional test was discrimination between all three stimuli of one equivalence class presented together versus three unrelated stimuli. The patient also had sessions with identity matching using the same stimuli. Results The patient showed high accuracy, close to 100%, on identity matching and could therefore discriminate the stimuli and control the cursor correctly. Acquisition of A-B matching took 11 sessions (of 70 trials each and had to be broken into simpler units before he could learn it. Acquisition of B-C matching took two sessions. The patient passed all equivalence class tests at 90% or higher. Conclusion The patient may have had a deficit in acquisition of the first conditional association of signs and colored disks. In contrast, the patient showed clear evidence that A-B and B-C training had resulted in formation of equivalence classes. The brain-computer interface technology combined with the matching to sample method is a useful way to assess various

Conditional associative learning examined in a paralyzed patient with amyotrophic lateral sclerosis using brain-computer interface technology.

Science.gov (United States)

Iversen, Ih; Ghanayim, N; Kübler, A; Neumann, N; Birbaumer, N; Kaiser, J

2008-11-24

Brain-computer interface methodology based on self-regulation of slow-cortical potentials (SCPs) of the EEG (electroencephalogram) was used to assess conditional associative learning in one severely paralyzed, late-stage ALS patient. After having been taught arbitrary stimulus relations, he was evaluated for formation of equivalence classes among the trained stimuli. A monitor presented visual information in two targets. The method of teaching was matching to sample. Three types of stimuli were presented: signs (A), colored disks (B), and geometrical shapes (C). The sample was one type, and the choice was between two stimuli from another type. The patient used his SCP to steer a cursor to one of the targets. A smiley was presented as a reward when he hit the correct target. The patient was taught A-B and B-C (sample - comparison) matching with three stimuli of each type. Tests for stimulus equivalence involved the untaught B-A, C-B, A-C, and C-A relations. An additional test was discrimination between all three stimuli of one equivalence class presented together versus three unrelated stimuli. The patient also had sessions with identity matching using the same stimuli. The patient showed high accuracy, close to 100%, on identity matching and could therefore discriminate the stimuli and control the cursor correctly. Acquisition of A-B matching took 11 sessions (of 70 trials each) and had to be broken into simpler units before he could learn it. Acquisition of B-C matching took two sessions. The patient passed all equivalence class tests at 90% or higher. The patient may have had a deficit in acquisition of the first conditional association of signs and colored disks. In contrast, the patient showed clear evidence that A-B and B-C training had resulted in formation of equivalence classes. The brain-computer interface technology combined with the matching to sample method is a useful way to assess various cognitive abilities of severely paralyzed patients, who are

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...

On the tip of the tongue: learning typing and pointing with an intra-oral computer interface.

Science.gov (United States)

Caltenco, Héctor A; Breidegard, Björn; Struijk, Lotte N S Andreasen

2014-07-01

To evaluate typing and pointing performance and improvement over time of four able-bodied participants using an intra-oral tongue-computer interface for computer control. A physically disabled individual may lack the ability to efficiently control standard computer input devices. There have been several efforts to produce and evaluate interfaces that provide individuals with physical disabilities the possibility to control personal computers. Training with the intra-oral tongue-computer interface was performed by playing games over 18 sessions. Skill improvement was measured through typing and pointing exercises at the end of each training session. Typing throughput improved from averages of 2.36 to 5.43 correct words per minute. Pointing throughput improved from averages of 0.47 to 0.85 bits/s. Target tracking performance, measured as relative time on target, improved from averages of 36% to 47%. Path following throughput improved from averages of 0.31 to 0.83 bits/s and decreased to 0.53 bits/s with more difficult tasks. Learning curves support the notion that the tongue can rapidly learn novel motor tasks. Typing and pointing performance of the tongue-computer interface is comparable to performances of other proficient assistive devices, which makes the tongue a feasible input organ for computer control. Intra-oral computer interfaces could provide individuals with severe upper-limb mobility impairments the opportunity to control computers and automatic equipment. Typing and pointing performance of the tongue-computer interface is comparable to performances of other proficient assistive devices, but does not cause fatigue easily and might be invisible to other people, which is highly prioritized by assistive device users. Combination of visual and auditory feedback is vital for a good performance of an intra-oral computer interface and helps to reduce involuntary or erroneous activations.

Camapple: CAMAC interface to the Apple computer

International Nuclear Information System (INIS)

Oxoby, G.J.; Trang, Q.H.; Williams, S.H.

1981-01-01

The advent of the 'personal' microcomputer provides a new tool for the debugging, calibration and monitoring of small scale physics apparatus, e.g., a single detector being developed for a larger physics apparatus. With an appropriate interface these microcomputer systems provide a low cost (1/3 the cost of a comparable minicomputer system), convenient, dedicated, portable system which can be used in a fashion similar to that of portable oscilliscopes. Here we describe an interface between the Apple computer and CAMAC which is now being used to study the detector for a Cerenkov ring-imaging device. The Apple is particularly well-suited to this application because of its ease of use, hi-resolution graphics, peripheral bus and documentation support. (orig.)

A computational method for sharp interface advection

Science.gov (United States)

Bredmose, Henrik; Jasak, Hrvoje

2016-01-01

We devise a numerical method for passive advection of a surface, such as the interface between two incompressible fluids, across a computational mesh. The method is called isoAdvector, and is developed for general meshes consisting of arbitrary polyhedral cells. The algorithm is based on the volume of fluid (VOF) idea of calculating the volume of one of the fluids transported across the mesh faces during a time step. The novelty of the isoAdvector concept consists of two parts. First, we exploit an isosurface concept for modelling the interface inside cells in a geometric surface reconstruction step. Second, from the reconstructed surface, we model the motion of the face–interface intersection line for a general polygonal face to obtain the time evolution within a time step of the submerged face area. Integrating this submerged area over the time step leads to an accurate estimate for the total volume of fluid transported across the face. The method was tested on simple two-dimensional and three-dimensional interface advection problems on both structured and unstructured meshes. The results are very satisfactory in terms of volume conservation, boundedness, surface sharpness and efficiency. The isoAdvector method was implemented as an OpenFOAM® extension and is published as open source. PMID:28018619

A computational method for sharp interface advection.

Science.gov (United States)

Roenby, Johan; Bredmose, Henrik; Jasak, Hrvoje

2016-11-01

We devise a numerical method for passive advection of a surface, such as the interface between two incompressible fluids, across a computational mesh. The method is called isoAdvector, and is developed for general meshes consisting of arbitrary polyhedral cells. The algorithm is based on the volume of fluid (VOF) idea of calculating the volume of one of the fluids transported across the mesh faces during a time step. The novelty of the isoAdvector concept consists of two parts. First, we exploit an isosurface concept for modelling the interface inside cells in a geometric surface reconstruction step. Second, from the reconstructed surface, we model the motion of the face-interface intersection line for a general polygonal face to obtain the time evolution within a time step of the submerged face area. Integrating this submerged area over the time step leads to an accurate estimate for the total volume of fluid transported across the face. The method was tested on simple two-dimensional and three-dimensional interface advection problems on both structured and unstructured meshes. The results are very satisfactory in terms of volume conservation, boundedness, surface sharpness and efficiency. The isoAdvector method was implemented as an OpenFOAM ® extension and is published as open source.

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

Design guidelines for the use of audio cues in computer interfaces

Energy Technology Data Exchange (ETDEWEB)

Sumikawa, D.A.; Blattner, M.M.; Joy, K.I.; Greenberg, R.M.

1985-07-01

A logical next step in the evolution of the computer-user interface is the incorporation of sound thereby using our senses of ''hearing'' in our communication with the computer. This allows our visual and auditory capacities to work in unison leading to a more effective and efficient interpretation of information received from the computer than by sight alone. In this paper we examine earcons, which are audio cues, used in the computer-user interface to provide information and feedback to the user about computer entities (these include messages and functions, as well as states and labels). The material in this paper is part of a larger study that recommends guidelines for the design and use of audio cues in the computer-user interface. The complete work examines the disciplines of music, psychology, communication theory, advertising, and psychoacoustics to discover how sound is utilized and analyzed in those areas. The resulting information is organized according to the theory of semiotics, the theory of signs, into the syntax, semantics, and pragmatics of communication by sound. Here we present design guidelines for the syntax of earcons. Earcons are constructed from motives, short sequences of notes with a specific rhythm and pitch, embellished by timbre, dynamics, and register. Compound earcons and family earcons are introduced. These are related motives that serve to identify a family of related cues. Examples of earcons are given.

Ecological Interface Design for Computer Network Defense.

Science.gov (United States)

Bennett, Kevin B; Bryant, Adam; Sushereba, Christen

2018-05-01

A prototype ecological interface for computer network defense (CND) was developed. Concerns about CND run high. Although there is a vast literature on CND, there is some indication that this research is not being translated into operational contexts. Part of the reason may be that CND has historically been treated as a strictly technical problem, rather than as a socio-technical problem. The cognitive systems engineering (CSE)/ecological interface design (EID) framework was used in the analysis and design of the prototype interface. A brief overview of CSE/EID is provided. EID principles of design (i.e., direct perception, direct manipulation and visual momentum) are described and illustrated through concrete examples from the ecological interface. Key features of the ecological interface include (a) a wide variety of alternative visual displays, (b) controls that allow easy, dynamic reconfiguration of these displays, (c) visual highlighting of functionally related information across displays, (d) control mechanisms to selectively filter massive data sets, and (e) the capability for easy expansion. Cyber attacks from a well-known data set are illustrated through screen shots. CND support needs to be developed with a triadic focus (i.e., humans interacting with technology to accomplish work) if it is to be effective. Iterative design and formal evaluation is also required. The discipline of human factors has a long tradition of success on both counts; it is time that HF became fully involved in CND. Direct application in supporting cyber analysts.

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.

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...

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.

Improvement of computer complex and interface system for compact nuclear simulator

International Nuclear Information System (INIS)

Lee, D. Y.; Park, W. M.; Cha, K. H.; Jung, C. H.; Park, J. C.

1999-01-01

CNS(Compact Nuclear Simulator) was developed at the end of 1980s, and have been used as training simulator for staffs of KAERI during 10 years. The operator panel interface cards and the graphic interface cards were designed with special purpose only for CNS. As these interface cards were worn out for 10 years, it was very difficult to get spare parts and to repair them. And the interface cards were damaged by over current happened by shortage of lamp in the operator panel. To solve these problem, the project 'Improvement of Compact Nuclear Simulator' was started from 1997. This paper only introduces about the improvement of computer complex and interface system

Computational analysis of RNA-protein interaction interfaces via the Voronoi diagram.

Science.gov (United States)

Mahdavi, Sedigheh; Mohades, Ali; Salehzadeh Yazdi, Ali; Jahandideh, Samad; Masoudi-Nejad, Ali

2012-01-21

Cellular functions are mediated by various biological processes including biomolecular interactions, such as protein-protein, DNA-protein and RNA-protein interactions in which RNA-Protein interactions are indispensable for many biological processes like cell development and viral replication. Unlike the protein-protein and protein-DNA interactions, accurate mechanisms and structures of the RNA-Protein complexes are not fully understood. A large amount of theoretical evidence have shown during the past several years that computational geometry is the first pace in understanding the binding profiles and plays a key role in the study of intricate biological structures, interactions and complexes. In this paper, RNA-Protein interaction interface surface is computed via the weighted Voronoi diagram of atoms. Using two filter operations provides a natural definition for interface atoms as classic methods. Unbounded parts of Voronoi facets that are far from the complex are trimmed using modified convex hull of atom centers. This algorithm is implemented to a database with different RNA-Protein complexes extracted from Protein Data Bank (PDB). Afterward, the features of interfaces have been computed and compared with classic method. The results show high correlation coefficients between interface size in the Voronoi model and the classical model based on solvent accessibility, as well as high accuracy and precision in comparison to classical model. Copyright © 2011 Elsevier Ltd. All rights reserved.

DIRProt: a computational approach for discriminating insecticide resistant proteins from non-resistant proteins.

Science.gov (United States)

Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Banchariya, Anjali; Rao, Atmakuri Ramakrishna

2017-03-24

Insecticide resistance is a major challenge for the control program of insect pests in the fields of crop protection, human and animal health etc. Resistance to different insecticides is conferred by the proteins encoded from certain class of genes of the insects. To distinguish the insecticide resistant proteins from non-resistant proteins, no computational tool is available till date. Thus, development of such a computational tool will be helpful in predicting the insecticide resistant proteins, which can be targeted for developing appropriate insecticides. Five different sets of feature viz., amino acid composition (AAC), di-peptide composition (DPC), pseudo amino acid composition (PAAC), composition-transition-distribution (CTD) and auto-correlation function (ACF) were used to map the protein sequences into numeric feature vectors. The encoded numeric vectors were then used as input in support vector machine (SVM) for classification of insecticide resistant and non-resistant proteins. Higher accuracies were obtained under RBF kernel than that of other kernels. Further, accuracies were observed to be higher for DPC feature set as compared to others. The proposed approach achieved an overall accuracy of >90% in discriminating resistant from non-resistant proteins. Further, the two classes of resistant proteins i.e., detoxification-based and target-based were discriminated from non-resistant proteins with >95% accuracy. Besides, >95% accuracy was also observed for discrimination of proteins involved in detoxification- and target-based resistance mechanisms. The proposed approach not only outperformed Blastp, PSI-Blast and Delta-Blast algorithms, but also achieved >92% accuracy while assessed using an independent dataset of 75 insecticide resistant proteins. This paper presents the first computational approach for discriminating the insecticide resistant proteins from non-resistant proteins. Based on the proposed approach, an online prediction server DIRProt has

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...

Binary particle swarm optimization for frequency band selection in motor imagery based brain-computer interfaces.

Science.gov (United States)

Wei, Qingguo; Wei, Zhonghai

2015-01-01

A brain-computer interface (BCI) enables people suffering from affective neurological diseases to communicate with the external world. Common spatial pattern (CSP) is an effective algorithm for feature extraction in motor imagery based BCI systems. However, many studies have proved that the performance of CSP depends heavily on the frequency band of EEG signals used for the construction of covariance matrices. The use of different frequency bands to extract signal features may lead to different classification performances, which are determined by the discriminative and complementary information they contain. In this study, the broad frequency band (8-30 Hz) is divided into 10 sub-bands of band width 4 Hz and overlapping 2 Hz. Binary particle swarm optimization (BPSO) is used to find the best sub-band set to improve the performance of CSP and subsequent classification. Experimental results demonstrate that the proposed method achieved an average improvement of 6.91% in cross-validation accuracy when compared to broad band CSP.

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.

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.

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.

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.

The Emotiv EPOC interface paradigm in Human-Computer Interaction

OpenAIRE

Ancău Dorina; Roman Nicolae-Marius; Ancău Mircea

2017-01-01

Numerous studies have suggested the use of decoded error potentials in the brain to improve human-computer communication. Together with state-of-the-art scientific equipment, experiments have also tested instruments with more limited performance for the time being, such as Emotiv EPOC. This study presents a review of these trials and a summary of the results obtained. However, the level of these results indicates a promising prospect for using this headset as a human-computer interface for er...

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

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.

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.

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...

Open-Box Muscle-Computer Interface: Introduction to Human-Computer Interactions in Bioengineering, Physiology, and Neuroscience Courses

Science.gov (United States)

Landa-Jiménez, M. A.; González-Gaspar, P.; Pérez-Estudillo, C.; López-Meraz, M. L.; Morgado-Valle, C.; Beltran-Parrazal, L.

2016-01-01

A Muscle-Computer Interface (muCI) is a human-machine system that uses electromyographic (EMG) signals to communicate with a computer. Surface EMG (sEMG) signals are currently used to command robotic devices, such as robotic arms and hands, and mobile robots, such as wheelchairs. These signals reflect the motor intention of a user before the…

A visual interface to computer programs for linkage analysis.

Science.gov (United States)

Chapman, C J

1990-06-01

This paper describes a visual approach to the input of information about human families into computer data bases, making use of the GEM graphic interface on the Atari ST. Similar approaches could be used on the Apple Macintosh or on the IBM PC AT (to which it has been transferred). For occasional users of pedigree analysis programs, this approach has considerable advantages in ease of use and accessibility. An example of such use might be the analysis of risk in families with Huntington disease using linked RFLPs. However, graphic interfaces do make much greater demands on the programmers of these systems.

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 ...

The Emotiv EPOC interface paradigm in Human-Computer Interaction

Directory of Open Access Journals (Sweden)

Ancău Dorina

2017-01-01

Full Text Available Numerous studies have suggested the use of decoded error potentials in the brain to improve human-computer communication. Together with state-of-the-art scientific equipment, experiments have also tested instruments with more limited performance for the time being, such as Emotiv EPOC. This study presents a review of these trials and a summary of the results obtained. However, the level of these results indicates a promising prospect for using this headset as a human-computer interface for error decoding.

[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.

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.

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.

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...

MULTI - multifunctional interface of the IBM XT and AT type personal computers

International Nuclear Information System (INIS)

Gross, T.; Kalavski, D.; Rubin, D.; Tulaev, A.B.; Tumanov, A.V.

1988-01-01

MULTI multifunctional interface which enables to solve problems of personal computer connestion with physical equipment without application of intermediate buses is described. Parallel 32-digit bidirectional 1/10 register and buffered bus of personal computer represent MULTI base. Ways of MULTI application are described

Fully Implanted Brain-Computer Interface in a Locked-In Patient with ALS.

Science.gov (United States)

Vansteensel, Mariska J; Pels, Elmar G M; Bleichner, Martin G; Branco, Mariana P; Denison, Timothy; Freudenburg, Zachary V; Gosselaar, Peter; Leinders, Sacha; Ottens, Thomas H; Van Den Boom, Max A; Van Rijen, Peter C; Aarnoutse, Erik J; Ramsey, Nick F

2016-11-24

Options for people with severe paralysis who have lost the ability to communicate orally are limited. We describe a method for communication in a patient with late-stage amyotrophic lateral sclerosis (ALS), involving a fully implanted brain-computer interface that consists of subdural electrodes placed over the motor cortex and a transmitter placed subcutaneously in the left side of the thorax. By attempting to move the hand on the side opposite the implanted electrodes, the patient accurately and independently controlled a computer typing program 28 weeks after electrode placement, at the equivalent of two letters per minute. The brain-computer interface offered autonomous communication that supplemented and at times supplanted the patient's eye-tracking device. (Funded by the Government of the Netherlands and the European Union; ClinicalTrials.gov number, NCT02224469 .).

A Novel Audiovisual Brain-Computer Interface and Its Application in Awareness Detection

Science.gov (United States)

Wang, Fei; He, Yanbin; Pan, Jiahui; Xie, Qiuyou; Yu, Ronghao; Zhang, Rui; Li, Yuanqing

2015-01-01

Currently, detecting awareness in patients with disorders of consciousness (DOC) is a challenging task, which is commonly addressed through behavioral observation scales such as the JFK Coma Recovery Scale-Revised. Brain-computer interfaces (BCIs) provide an alternative approach to detect awareness in patients with DOC. However, these patients have a much lower capability of using BCIs compared to healthy individuals. This study proposed a novel BCI using temporally, spatially, and semantically congruent audiovisual stimuli involving numbers (i.e., visual and spoken numbers). Subjects were instructed to selectively attend to the target stimuli cued by instruction. Ten healthy subjects first participated in the experiment to evaluate the system. The results indicated that the audiovisual BCI system outperformed auditory-only and visual-only systems. Through event-related potential analysis, we observed audiovisual integration effects for target stimuli, which enhanced the discriminability between brain responses for target and nontarget stimuli and thus improved the performance of the audiovisual BCI. This system was then applied to detect the awareness of seven DOC patients, five of whom exhibited command following as well as number recognition. Thus, this audiovisual BCI system may be used as a supportive bedside tool for awareness detection in patients with DOC. PMID:26123281

Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification

Science.gov (United States)

Dai, Mengxi; Liu, Shucong; Zhang, Pengju

2018-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods. PMID:29743934

Brain-computer interface (BCI) evaluation in people with amyotrophic lateral sclerosis.

Science.gov (United States)

McCane, Lynn M; Sellers, Eric W; McFarland, Dennis J; Mak, Joseph N; Carmack, C Steve; Zeitlin, Debra; Wolpaw, Jonathan R; Vaughan, Theresa M

2014-06-01

Brain-computer interfaces (BCIs) might restore communication to people severely disabled by amyotrophic lateral sclerosis (ALS) or other disorders. We sought to: 1) define a protocol for determining whether a person with ALS can use a visual P300-based BCI; 2) determine what proportion of this population can use the BCI; and 3) identify factors affecting BCI performance. Twenty-five individuals with ALS completed an evaluation protocol using a standard 6 × 6 matrix and parameters selected by stepwise linear discrimination. With an 8-channel EEG montage, the subjects fell into two groups in BCI accuracy (chance accuracy 3%). Seventeen averaged 92 (± 3)% (range 71-100%), which is adequate for communication (G70 group). Eight averaged 12 (± 6)% (range 0-36%), inadequate for communication (L40 subject group). Performance did not correlate with disability: 11/17 (65%) of G70 subjects were severely disabled (i.e. ALSFRS-R < 5). All L40 subjects had visual impairments (e.g. nystagmus, diplopia, ptosis). P300 was larger and more anterior in G70 subjects. A 16-channel montage did not significantly improve accuracy. In conclusion, most people severely disabled by ALS could use a visual P300-based BCI for communication. In those who could not, visual impairment was the principal obstacle. For these individuals, auditory P300-based BCIs might be effective.

A Graphical User Interface for the Computational Fluid Dynamics Software OpenFOAM

OpenAIRE

Melbø, Henrik Kaald

2014-01-01

A graphical user interface for the computational fluid dynamics software OpenFOAM has been constructed. OpenFOAM is a open source and powerful numerical software, but has much to be wanted in the field of user friendliness. In this thesis the basic operation of OpenFOAM will be introduced and the thesis will emerge in a graphical user interface written in PyQt. The graphical user interface will make the use of OpenFOAM simpler, and hopefully make this powerful tool more available for the gene...

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...

Design of a Computer-Controlled, Random-Access Slide Projector Interface. Final Report (April 1974 - November 1974).

Science.gov (United States)

Kirby, Paul J.; And Others

The design, development, test, and evaluation of an electronic hardware device interfacing a commercially available slide projector with a plasma panel computer terminal is reported. The interface device allows an instructional computer program to select slides for viewing based upon the lesson student situation parameters of the instructional…

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.

Measuring Emotion Regulation with Single Dry Electrode Brain Computer Interface

NARCIS (Netherlands)

van der Wal, C.N.; Irrmischer, M.; Guo, Y.; Friston, K.; Faisal, A.; Hill, S.; Peng, H.

2015-01-01

Wireless brain computer interfaces (BCI’s) are promising for new intelligent applications in which emotions are detected by measuring brain activity. Applications, such as serious games and video game therapy, are measuring and using the user’s emotional state in order to determine the intensity

Mechatronics Interface for Computer Assisted Prostate Surgery Training

Science.gov (United States)

Altamirano del Monte, Felipe; Padilla Castañeda, Miguel A.; Arámbula Cosío, Fernando

2006-09-01

In this work is presented the development of a mechatronics device to simulate the interaction of the surgeon with the surgical instrument (resectoscope) used during a Transurethral Resection of the Prostate (TURP). Our mechatronics interface is part of a computer assisted system for training in TURP, which is based on a 3D graphics model of the prostate which can be deformed and resected interactively by the user. The mechatronics interface, is the device that the urology residents will manipulate to simulate the movements performed during surgery. Our current prototype has five degrees of freedom, which are enough to have a realistic simulation of the surgery movements. Two of these degrees of freedom are linear, to determinate the linear displacement of the resecting loop and the other three are rotational to determinate three directions and amounts of rotation.

An automated meta-monitoring mobile application and front-end interface for the ATLAS computing model

Energy Technology Data Exchange (ETDEWEB)

Kawamura, Gen; Quadt, Arnulf [II. Physikalisches Institut, Georg-August-Universitaet Goettingen (Germany)

2016-07-01

Efficient administration of computing centres requires advanced tools for the monitoring and front-end interface of the infrastructure. Providing the large-scale distributed systems as a global grid infrastructure, like the Worldwide LHC Computing Grid (WLCG) and ATLAS computing, is offering many existing web pages and information sources indicating the status of the services, systems and user jobs at grid sites. A meta-monitoring mobile application which automatically collects the information could give every administrator a sophisticated and flexible interface of the infrastructure. We describe such a solution; the MadFace mobile application developed at Goettingen. It is a HappyFace compatible mobile application which has a user-friendly interface. It also becomes very feasible to automatically investigate the status and problem from different sources and provides access of the administration roles for non-experts.

Software and man-machine interface considerations for a nuclear plant computer replacement and upgrade project

International Nuclear Information System (INIS)

Diamond, G.; Robinson, E.

1984-01-01

Some of the key software functions and Man-Machine Interface considerations in a computer replacement and upgrade project for a nuclear power plant are described. The project involves the installation of two separate computer systems: an Emergency Response Facilities Computer System (ERFCS) and a Plant Process Computer System (PPCS). These systems employ state-of-the-art computer hardware and software. The ERFCS is a new system intended to provide enhanced functions to meet NRC post-TMI guidelines. The PPCS is intended to replace and upgrade an existing obsolete plant computer system. A general overview of the hardware and software aspects of the replacement and upgrade is presented. The work done to develop the upgraded Man-Machine Interface is described. For the ERFCS, a detailed discussion is presented of the work done to develop logic to evaluate the readiness and performance of safety systems and their supporting functions. The Man-Machine Interface considerations of reporting readiness and performance to the operator are discussed. Finally, the considerations involved in the implementation of this logic in real-time software are discussed.. For the PPCS, a detailed discussion is presented of some new features

Improved Targeting Through Collaborative Decision-Making and Brain Computer Interfaces

Science.gov (United States)

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.

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.

Development and functional demonstration of a wireless intraoral inductive tongue computer interface for severely disabled persons.

Science.gov (United States)

N S Andreasen Struijk, Lotte; Lontis, Eugen R; Gaihede, Michael; Caltenco, Hector A; Lund, Morten Enemark; Schioeler, Henrik; Bentsen, Bo

2017-08-01

Individuals with tetraplegia depend on alternative interfaces in order to control computers and other electronic equipment. Current interfaces are often limited in the number of available control commands, and may compromise the social identity of an individual due to their undesirable appearance. The purpose of this study was to implement an alternative computer interface, which was fully embedded into the oral cavity and which provided multiple control commands. The development of a wireless, intraoral, inductive tongue computer was described. The interface encompassed a 10-key keypad area and a mouse pad area. This system was embedded wirelessly into the oral cavity of the user. The functionality of the system was demonstrated in two tetraplegic individuals and two able-bodied individuals Results: The system was invisible during use and allowed the user to type on a computer using either the keypad area or the mouse pad. The maximal typing rate was 1.8 s for repetitively typing a correct character with the keypad area and 1.4 s for repetitively typing a correct character with the mouse pad area. The results suggest that this inductive tongue computer interface provides an esthetically acceptable and functionally efficient environmental control for a severely disabled user. Implications for Rehabilitation New Design, Implementation and detection methods for intra oral assistive devices. Demonstration of wireless, powering and encapsulation techniques suitable for intra oral embedment of assistive devices. Demonstration of the functionality of a rechargeable and fully embedded intra oral tongue controlled computer input device.

Operation of a P300-based brain-computer interface by patients with spinocerebellar ataxia

Directory of Open Access Journals (Sweden)

Yoji Okahara

Full Text Available Objective: We investigated the efficacy of a P300-based brain-computer interface (BCI for patients with spinocerebellar ataxia (SCA, which is often accompanied by cerebellar impairment. Methods: Eight patients with SCA and eight age- and gender-matched healthy controls were instructed to input Japanese hiragana characters using the P300-based BCI with green/blue flicker. All patients depended on some assistance in their daily lives (modified Rankin scale: mean 3.5. The chief symptom was cerebellar ataxia; no cognitive deterioration was present. A region-based, two-step P300-based BCI was used. During the P300 task, eight-channel EEG data were recorded, and a linear discriminant analysis distinguished the target from other nontarget regions of the matrix. Results: The mean online accuracy in BCI operation was 82.9% for patients with SCA and 83.2% for controls; no significant difference was detected. Conclusion: The P300-based BCI was operated successfully not only by healthy controls but also by individuals with SCA. Significance: These results suggest that the P300-based BCI may be applicable for patients with SCA. Keywords: BCI, BMI, P300, Visual stimuli, Spinocerebellar ataxia

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

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

NARCIS (Netherlands)

Vlek, R.J.; Steines, D.; Szibbo, D.; Kübler, A.; Schneider, M.J.; Haselager, W.F.G.; Nijboer, F.

2012-01-01

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

Experimental evaluation of multimodal human computer interface for tactical audio applications

NARCIS (Netherlands)

Obrenovic, Z.; Starcevic, D.; Jovanov, E.; Oy, S.

2002-01-01

Mission critical and information overwhelming applications require careful design of the human computer interface. Typical applications include night vision or low visibility mission navigation, guidance through a hostile territory, and flight navigation and orientation. Additional channels of

Catalyzing Inquiry at the Interface of Computing and Biology

Energy Technology Data Exchange (ETDEWEB)

John Wooley; Herbert S. Lin

2005-10-30

This study is the first comprehensive NRC study that suggests a high-level intellectual structure for Federal agencies for supporting work at the biology/computing interface. The report seeks to establish the intellectual legitimacy of a fundamentally cross-disciplinary collaboration between biologists and computer scientists. That is, while some universities are increasingly favorable to research at the intersection, life science researchers at other universities are strongly impeded in their efforts to collaborate. This report addresses these impediments and describes proven strategies for overcoming them. An important feature of the report is the use of well-documented examples that describe clearly to individuals not trained in computer science the value and usage of computing across the biological sciences, from genes and proteins to networks and pathways, from organelles to cells, and from individual organisms to populations and ecosystems. It is hoped that these examples will be useful to students in the life sciences to motivate (continued) study in computer science that will enable them to be more facile users of computing in their future biological studies.

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.

UIMX: A User Interface Management System For Scientific Computing With X Windows

Science.gov (United States)

Foody, Michael

1989-09-01

Applications with iconic user interfaces, (for example, interfaces with pulldown menus, radio buttons, and scroll bars), such as those found on Apple's Macintosh computer and the IBM PC under Microsoft's Presentation Manager, have become very popular, and for good reason. They are much easier to use than applications with traditional keyboard-oriented interfaces, so training costs are much lower and just about anyone can use them. They are standardized between applications, so once you learn one application you are well along the way to learning another. The use of one reinforces the common elements between applications of the interface, and, as a result, you remember how to use them longer. Finally, for the developer, their support costs can be much lower because of their ease of use.

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

Science.gov (United States)

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

2015-01-01

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

Optimal design method for a digital human–computer interface based on human reliability in a nuclear power plant. Part 3: Optimization method for interface task layout

International Nuclear Information System (INIS)

Jiang, Jianjun; Wang, Yiqun; Zhang, Li; Xie, Tian; Li, Min; Peng, Yuyuan; Wu, Daqing; Li, Peiyao; Ma, Congmin; Shen, Mengxu; Wu, Xing; Weng, Mengyun; Wang, Shiwei; Xie, Cen

2016-01-01

Highlights: • The authors present an optimization algorithm for interface task layout. • The performing process of the proposed algorithm was depicted. • The performance evaluation method adopted neural network method. • The optimization layouts of an event interface tasks were obtained by experiments. - Abstract: This is the last in a series of papers describing the optimal design for a digital human–computer interface of a nuclear power plant (NPP) from three different points based on human reliability. The purpose of this series is to propose different optimization methods from varying perspectives to decrease human factor events that arise from the defects of a human–computer interface. The present paper mainly solves the optimization method as to how to effectively layout interface tasks into different screens. The purpose of this paper is to decrease human errors by reducing the distance that an operator moves among different screens in each operation. In order to resolve the problem, the authors propose an optimization process of interface task layout for digital human–computer interface of a NPP. As to how to automatically layout each interface task into one of screens in each operation, the paper presents a shortest moving path optimization algorithm with dynamic flag based on human reliability. To test the algorithm performance, the evaluation method uses neural network based on human reliability. The less the human error probabilities are, the better the interface task layouts among different screens are. Thus, by analyzing the performance of each interface task layout, the optimization result is obtained. Finally, the optimization layouts of spurious safety injection event interface tasks of the NPP are obtained by an experiment, the proposed methods has a good accuracy and stabilization.

Human-computer interface glove using flexible piezoelectric sensors

Science.gov (United States)

Cha, Youngsu; Seo, Jeonggyu; Kim, Jun-Sik; Park, Jung-Min

2017-05-01

In this note, we propose a human-computer interface glove based on flexible piezoelectric sensors. We select polyvinylidene fluoride as the piezoelectric material for the sensors because of advantages such as a steady piezoelectric characteristic and good flexibility. The sensors are installed in a fabric glove by means of pockets and Velcro bands. We detect changes in the angles of the finger joints from the outputs of the sensors, and use them for controlling a virtual hand that is utilized in virtual object manipulation. To assess the sensing ability of the piezoelectric sensors, we compare the processed angles from the sensor outputs with the real angles from a camera recoding. With good agreement between the processed and real angles, we successfully demonstrate the user interaction system with the virtual hand and interface glove based on the flexible piezoelectric sensors, for four hand motions: fist clenching, pinching, touching, and grasping.

Brain-Computer Interfaces With Multi-Sensory Feedback for Stroke Rehabilitation: A Case Study.

Science.gov (United States)

Irimia, Danut C; Cho, Woosang; Ortner, Rupert; Allison, Brendan Z; Ignat, Bogdan E; Edlinger, Guenter; Guger, Christoph

2017-11-01

Conventional therapies do not provide paralyzed patients with closed-loop sensorimotor integration for motor rehabilitation. This work presents the recoveriX system, a hardware and software platform that combines a motor imagery (MI)-based brain-computer interface (BCI), functional electrical stimulation (FES), and visual feedback technologies for a complete sensorimotor closed-loop therapy system for poststroke rehabilitation. The proposed system was tested on two chronic stroke patients in a clinical environment. The patients were instructed to imagine the movement of either the left or right hand in random order. During these two MI tasks, two types of feedback were provided: a bar extending to the left or right side of a monitor as visual feedback and passive hand opening stimulated from FES as proprioceptive feedback. Both types of feedback relied on the BCI classification result achieved using common spatial patterns and a linear discriminant analysis classifier. After 10 sessions of recoveriX training, one patient partially regained control of wrist extension in her paretic wrist and the other patient increased the range of middle finger movement by 1 cm. A controlled group study is planned with a new version of the recoveriX system, which will have several improvements. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Interfacing a fieldable multichannel analyzer to a MicroVAX computer

International Nuclear Information System (INIS)

Litherland, K.R.; Johnson, M.W.

1990-01-01

This paper reports on software written for interfacing the D.S. Davidson Model 2056 portable multichannel analyzer to a MicroVAX computer running the VMS operating system. The operational objective of the software is to give the user a nearly transparent mechanism for controlling the analyzer with functions equivalent to those on the analyzer's own keyboard, thus minimizing the training requirement for the user. The software is written in VMS enhanced Fortran and consists of a main control program, several subprocesses, and libraries containing graphics commands and other information. Interfaces to other commercially available software packages for data storage and manipulation are provided. Problems encountered and their programming solutions are discussed

Sensory System for Implementing a Human—Computer Interface Based on Electrooculography

Directory of Open Access Journals (Sweden)

Sergio Ortega

2010-12-01

Full Text Available This paper describes a sensory system for implementing a human–computer interface based on electrooculography. An acquisition system captures electrooculograms and transmits them via the ZigBee protocol. The data acquired are analysed in real time using a microcontroller-based platform running the Linux operating system. The continuous wavelet transform and neural network are used to process and analyse the signals to obtain highly reliable results in real time. To enhance system usability, the graphical interface is projected onto special eyewear, which is also used to position the signal-capturing electrodes.

User Interface History

DEFF Research Database (Denmark)

Jørgensen, Anker Helms; Myers, Brad A

2008-01-01

User Interfaces have been around as long as computers have existed, even well before the field of Human-Computer Interaction was established. Over the years, some papers on the history of Human-Computer Interaction and User Interfaces have appeared, primarily focusing on the graphical interface e...

Treatment of human-computer interface in a decision support system

International Nuclear Information System (INIS)

Heger, A.S.; Duran, F.A.; Cox, R.G.

1992-01-01

One of the most challenging applications facing the computer community is development of effective adaptive human-computer interface. This challenge stems from the complex nature of the human part of this symbiosis. The application of this discipline to the environmental restoration and waste management is further complicated due to the nature of environmental data. The information that is required to manage environmental impacts of human activity is fundamentally complex. This paper will discuss the efforts at Sandia National Laboratories in developing the adaptive conceptual model manager within the constraint of the environmental decision-making. A computer workstation, that hosts the Conceptual Model Manager and the Sandia Environmental Decision Support System will also be discussed

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.

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.

Brain–Computer Interface Spellers: A Review

Science.gov (United States)

Gembler, Felix; Saboor, Abdul

2018-01-01

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. PMID:29601538

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.

The computer-controlled GPIB-RS232 interface for data transmission

International Nuclear Information System (INIS)

Bai Xiaowei

1993-01-01

A kind of RS232-GPIB interface circuit is introduced, which provides communication between the serial system and the instrument with GPIB. Port P 1 of 8031 is used to select function mode as listener, talker or others. Under the control of a personal computer, the data communication is completed both in serial and the parallel modes

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.

Investigation and evaluation into the usability of human-computer interfaces using a typical CAD system

Energy Technology Data Exchange (ETDEWEB)

Rickett, J D

1987-01-01

This research program covers three topics relating to the human-computer interface namely, voice recognition, tools and techniques for evaluation, and user and interface modeling. An investigation into the implementation of voice-recognition technologies examines how voice recognizers may be evaluated in commercial software. A prototype system was developed with the collaboration of FEMVIEW Ltd. (marketing a CAD package). A theoretical approach to evaluation leads to the hypothesis that human-computer interaction is affected by personality, influencing types of dialogue, preferred methods for providing helps, etc. A user model based on personality traits, or habitual-behavior patterns (HBP) is presented. Finally, a practical framework is provided for the evaluation of human-computer interfaces. It suggests that evaluation is an integral part of design and that the iterative use of evaluation techniques throughout the conceptualization, design, implementation and post-implementation stages will ensure systems that satisfy the needs of the users and fulfill the goal of usability.

Myndplay: Measuring Attention Regulation with Single Dry Electrode Brain Computer Interface

NARCIS (Netherlands)

van der Wal, C.N.; Irrmischer, M.; Guo, Y.; Friston, K.; Faisal, A.; Hill, S.; Peng, H.

2015-01-01

Future applications for the detection of attention can be helped by the development and validation of single electrode brain computer interfaces that are small and user-friendly. The two objectives of this study were: to (1) understand the correlates of attention regulation as detected with the

An embedded implementation based on adaptive filter bank for brain-computer interface systems.

Science.gov (United States)

Belwafi, Kais; Romain, Olivier; Gannouni, Sofien; Ghaffari, Fakhreddine; Djemal, Ridha; Ouni, Bouraoui

2018-07-15

Brain-computer interface (BCI) is a new communication pathway for users with neurological deficiencies. The implementation of a BCI system requires complex electroencephalography (EEG) signal processing including filtering, feature extraction and classification algorithms. Most of current BCI systems are implemented on personal computers. Therefore, there is a great interest in implementing BCI on embedded platforms to meet system specifications in terms of time response, cost effectiveness, power consumption, and accuracy. This article presents an embedded-BCI (EBCI) system based on a Stratix-IV field programmable gate array. The proposed system relays on the weighted overlap-add (WOLA) algorithm to perform dynamic filtering of EEG-signals by analyzing the event-related desynchronization/synchronization (ERD/ERS). The EEG-signals are classified, using the linear discriminant analysis algorithm, based on their spatial features. The proposed system performs fast classification within a time delay of 0.430 s/trial, achieving an average accuracy of 76.80% according to an offline approach and 80.25% using our own recording. The estimated power consumption of the prototype is approximately 0.7 W. Results show that the proposed EBCI system reduces the overall classification error rate for the three datasets of the BCI-competition by 5% compared to other similar implementations. Moreover, experiment shows that the proposed system maintains a high accuracy rate with a short processing time, a low power consumption, and a low cost. Performing dynamic filtering of EEG-signals using WOLA increases the recognition rate of ERD/ERS patterns of motor imagery brain activity. This approach allows to develop a complete prototype of a EBCI system that achieves excellent accuracy rates. Copyright © 2018 Elsevier B.V. All rights reserved.

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)

Overview Electrotactile Feedback for Enhancing Human Computer Interface

Science.gov (United States)

Pamungkas, Daniel S.; Caesarendra, Wahyu

2018-04-01

To achieve effective interaction between a human and a computing device or machine, adequate feedback from the computing device or machine is required. Recently, haptic feedback is increasingly being utilised to improve the interactivity of the Human Computer Interface (HCI). Most existing haptic feedback enhancements aim at producing forces or vibrations to enrich the user’s interactive experience. However, these force and/or vibration actuated haptic feedback systems can be bulky and uncomfortable to wear and only capable of delivering a limited amount of information to the user which can limit both their effectiveness and the applications they can be applied to. To address this deficiency, electrotactile feedback is used. This involves delivering haptic sensations to the user by electrically stimulating nerves in the skin via electrodes placed on the surface of the skin. This paper presents a review and explores the capability of electrotactile feedback for HCI applications. In addition, a description of the sensory receptors within the skin for sensing tactile stimulus and electric currents alsoseveral factors which influenced electric signal to transmit to the brain via human skinare explained.

Learning Auditory Discrimination with Computer-Assisted Instruction: A Comparison of Two Different Performance Objectives.

Science.gov (United States)

Steinhaus, Kurt A.

A 12-week study of two groups of 14 college freshmen music majors was conducted to determine which group demonstrated greater achievement in learning auditory discrimination using computer-assisted instruction (CAI). The method employed was a pre-/post-test experimental design using subjects randomly assigned to a control group or an experimental…

Interface design of VSOP'94 computer code for safety analysis

International Nuclear Information System (INIS)

Natsir, Khairina; Andiwijayakusuma, D.; Wahanani, Nursinta Adi; Yazid, Putranto Ilham

2014-01-01

Today, most software applications, also in the nuclear field, come with a graphical user interface. VSOP'94 (Very Superior Old Program), was designed to simplify the process of performing reactor simulation. VSOP is a integrated code system to simulate the life history of a nuclear reactor that is devoted in education and research. One advantage of VSOP program is its ability to calculate the neutron spectrum estimation, fuel cycle, 2-D diffusion, resonance integral, estimation of reactors fuel costs, and integrated thermal hydraulics. VSOP also can be used to comparative studies and simulation of reactor safety. However, existing VSOP is a conventional program, which was developed using Fortran 65 and have several problems in using it, for example, it is only operated on Dec Alpha mainframe platforms and provide text-based output, difficult to use, especially in data preparation and interpretation of results. We develop a GUI-VSOP, which is an interface program to facilitate the preparation of data, run the VSOP code and read the results in a more user friendly way and useable on the Personal 'Computer (PC). Modifications include the development of interfaces on preprocessing, processing and postprocessing. GUI-based interface for preprocessing aims to provide a convenience way in preparing data. Processing interface is intended to provide convenience in configuring input files and libraries and do compiling VSOP code. Postprocessing interface designed to visualized the VSOP output in table and graphic forms. GUI-VSOP expected to be useful to simplify and speed up the process and analysis of safety aspects

Interface design of VSOP'94 computer code for safety analysis

Science.gov (United States)

Natsir, Khairina; Yazid, Putranto Ilham; Andiwijayakusuma, D.; Wahanani, Nursinta Adi

2014-09-01

Today, most software applications, also in the nuclear field, come with a graphical user interface. VSOP'94 (Very Superior Old Program), was designed to simplify the process of performing reactor simulation. VSOP is a integrated code system to simulate the life history of a nuclear reactor that is devoted in education and research. One advantage of VSOP program is its ability to calculate the neutron spectrum estimation, fuel cycle, 2-D diffusion, resonance integral, estimation of reactors fuel costs, and integrated thermal hydraulics. VSOP also can be used to comparative studies and simulation of reactor safety. However, existing VSOP is a conventional program, which was developed using Fortran 65 and have several problems in using it, for example, it is only operated on Dec Alpha mainframe platforms and provide text-based output, difficult to use, especially in data preparation and interpretation of results. We develop a GUI-VSOP, which is an interface program to facilitate the preparation of data, run the VSOP code and read the results in a more user friendly way and useable on the Personal 'Computer (PC). Modifications include the development of interfaces on preprocessing, processing and postprocessing. GUI-based interface for preprocessing aims to provide a convenience way in preparing data. Processing interface is intended to provide convenience in configuring input files and libraries and do compiling VSOP code. Postprocessing interface designed to visualized the VSOP output in table and graphic forms. GUI-VSOP expected to be useful to simplify and speed up the process and analysis of safety aspects.

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.

Electrophysiological Brain Activity during the Control of a Motor Imagery-Based Brain–Computer Interface

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Aziatskaya, G.A.; Bobrov, P.D.; Luykmanov, R. Kh.; Fedotova, I.R.; Húsek, Dušan; Snášel, V.

2017-01-01

Roč. 43, č. 5 (2017), s. 501-511 ISSN 0362-1197 Institutional support: RVO:67985807 Keywords : brain–computer interface * neurointerface * EEG * motor imagery * EEG rhythm synchronization and desynchronization * independent component analysis * EEG inverse problem * neurorehabilitation Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

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.

User interfaces for computational science: A domain specific language for OOMMF embedded in Python

Science.gov (United States)

Beg, Marijan; Pepper, Ryan A.; Fangohr, Hans

2017-05-01

Computer simulations are used widely across the engineering and science disciplines, including in the research and development of magnetic devices using computational micromagnetics. In this work, we identify and review different approaches to configuring simulation runs: (i) the re-compilation of source code, (ii) the use of configuration files, (iii) the graphical user interface, and (iv) embedding the simulation specification in an existing programming language to express the computational problem. We identify the advantages and disadvantages of different approaches and discuss their implications on effectiveness and reproducibility of computational studies and results. Following on from this, we design and describe a domain specific language for micromagnetics that is embedded in the Python language, and allows users to define the micromagnetic simulations they want to carry out in a flexible way. We have implemented this micromagnetic simulation description language together with a computational backend that executes the simulation task using the Object Oriented MicroMagnetic Framework (OOMMF). We illustrate the use of this Python interface for OOMMF by solving the micromagnetic standard problem 4. All the code is publicly available and is open source.

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.

sw-SVM: sensor weighting support vector machines for EEG-based brain-computer interfaces.

Science.gov (United States)

Jrad, N; Congedo, M; Phlypo, R; Rousseau, S; Flamary, R; Yger, F; Rakotomamonjy, A

2011-10-01

In many machine learning applications, like brain-computer interfaces (BCI), high-dimensional sensor array data are available. Sensor measurements are often highly correlated and signal-to-noise ratio is not homogeneously spread across sensors. Thus, collected data are highly variable and discrimination tasks are challenging. In this work, we focus on sensor weighting as an efficient tool to improve the classification procedure. We present an approach integrating sensor weighting in the classification framework. Sensor weights are considered as hyper-parameters to be learned by a support vector machine (SVM). The resulting sensor weighting SVM (sw-SVM) is designed to satisfy a margin criterion, that is, the generalization error. Experimental studies on two data sets are presented, a P300 data set and an error-related potential (ErrP) data set. For the P300 data set (BCI competition III), for which a large number of trials is available, the sw-SVM proves to perform equivalently with respect to the ensemble SVM strategy that won the competition. For the ErrP data set, for which a small number of trials are available, the sw-SVM shows superior performances as compared to three state-of-the art approaches. Results suggest that the sw-SVM promises to be useful in event-related potentials classification, even with a small number of training trials.

Achieving a hybrid brain-computer interface with tactile selective attention and motor imagery

Science.gov (United States)

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

2014-12-01

Objective. We propose a new hybrid brain-computer interface (BCI) system that integrates two different EEG tasks: tactile selective attention (TSA) using a vibro-tactile stimulator on the left/right finger and motor imagery (MI) of left/right hand movement. Event-related desynchronization (ERD) from the MI task and steady-state somatosensory evoked potential (SSSEP) from the TSA task are retrieved and combined into two hybrid senses. Approach. One hybrid approach is to measure two tasks simultaneously; the features of each task are combined for testing. Another hybrid approach is to measure two tasks consecutively (TSA first and MI next) using only MI features. For comparison with the hybrid approaches, the TSA and MI tasks are measured independently. Main results. Using a total of 16 subject datasets, we analyzed the BCI classification performance for MI, TSA and two hybrid approaches in a comparative manner; we found that the consecutive hybrid approach outperformed the others, yielding about a 10% improvement in classification accuracy relative to MI alone. It is understood that TSA may play a crucial role as a prestimulus in that it helps to generate earlier ERD prior to MI and thus sustains ERD longer and to a stronger degree; this ERD may give more discriminative information than ERD in MI alone. Significance. Overall, our proposed consecutive hybrid approach is very promising for the development of advanced BCI systems.

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...

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...

Computer simulation study of the nematic-vapour interface in the Gay-Berne model

Science.gov (United States)

Rull, Luis F.; Romero-Enrique, José Manuel

2017-06-01

We present computer simulations of the vapour-nematic interface of the Gay-Berne model. We considered situations which correspond to either prolate or oblate molecules. We determine the anchoring of the nematic phase and correlate it with the intermolecular potential parameters. On the other hand, we evaluate the surface tension associated to this interface. We find a corresponding states law for the surface tension dependence on the temperature, valid for both prolate and oblate molecules.

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.

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

Science.gov (United States)

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.

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

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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

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.

A simple interface to computational fluid dynamics programs for building environment simulations

Energy Technology Data Exchange (ETDEWEB)

Broderick, III, C R; Chen, Q [Massachusetts Institute of Technology, Cambridge, MA (United States)

2000-07-01

It is becoming a popular practice for architects and HVAC engineers to simulate airflow in and around buildings by computational fluid dynamics (CFD) methods in order to predict indoor and outdoor environment. However, many CFD programs are crippled by a historically poor and inefficient user interface system, particularly for users with little training in numerical simulation. This investigation endeavors to create a simplified CFD interface (SCI) that allows architects and buildings engineers to use CFD without excessive training. The SCI can be easily integrated into new CFD programs. (author)

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.

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.

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.

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

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 Conceptual Architecture for Adaptive Human-Computer Interface of a PT Operation Platform Based on Context-Awareness

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Qing Xue

2014-01-01

Full Text Available We present a conceptual architecture for adaptive human-computer interface of a PT operation platform based on context-awareness. This architecture will form the basis of design for such an interface. This paper describes components, key technologies, and working principles of the architecture. The critical contents covered context information modeling, processing, relationship establishing between contexts and interface design knowledge by use of adaptive knowledge reasoning, and visualization implementing of adaptive interface with the aid of interface tools technology.

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.

Error-Free Text Typing Performance of an Inductive Intra-Oral Tongue Computer Interface for Severely Disabled Individuals.

Science.gov (United States)

Andreasen Struijk, Lotte N S; Bentsen, Bo; Gaihede, Michael; Lontis, Eugen R

2017-11-01

For severely paralyzed individuals, alternative computer interfaces are becoming increasingly essential for everyday life as social and vocational activities are facilitated by information technology and as the environment becomes more automatic and remotely controllable. Tongue computer interfaces have proven to be desirable by the users partly due to their high degree of aesthetic acceptability, but so far the mature systems have shown a relatively low error-free text typing efficiency. This paper evaluated the intra-oral inductive tongue computer interface (ITCI) in its intended use: Error-free text typing in a generally available text editing system, Word. Individuals with tetraplegia and able bodied individuals used the ITCI for typing using a MATLAB interface and for Word typing for 4 to 5 experimental days, and the results showed an average error-free text typing rate in Word of 11.6 correct characters/min across all participants and of 15.5 correct characters/min for participants familiar with tongue piercings. Improvements in typing rates between the sessions suggest that typing ratescan be improved further through long-term use of the ITCI.

A high speed, selective multi-ADC to computer data transfer interface, for nuclear physics experiments

International Nuclear Information System (INIS)

Arctaedius, T.; Ekstroem, R.E.

1986-08-01

A link connecting up to fifteen Analog to Digital Converters with a computer, through a Direct Memory Access interface, is described. The interface decides which of the connected ADC:s that participate in an event, and transfers the output-data from these to the computer, accompanied with a 2-byte word identifying the participating ADC:s. This data format can be recorded on tape without further transformations, and is easy to unfold at the off-line analysis. Data transfer is accomplished in less than a few microseconds, which is made possible by the use of high speed TTL circuits. (authors)

Computer interfacing

CERN Document Server

Dixey, Graham

1994-01-01

This book explains how computers interact with the world around them and therefore how to make them a useful tool. Topics covered include descriptions of all the components that make up a computer, principles of data exchange, interaction with peripherals, serial communication, input devices, recording methods, computer-controlled motors, and printers.In an informative and straightforward manner, Graham Dixey describes how to turn what might seem an incomprehensible 'black box' PC into a powerful and enjoyable tool that can help you in all areas of your work and leisure. With plenty of handy

Neural Correlates of User-initiated Motor Success and Failure - A Brain-Computer Interface Perspective.

Science.gov (United States)

Yazmir, Boris; Reiner, Miriam

2018-05-15

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

User interfaces for computational science: A domain specific language for OOMMF embedded in Python

Directory of Open Access Journals (Sweden)

Marijan Beg

2017-05-01

Full Text Available Computer simulations are used widely across the engineering and science disciplines, including in the research and development of magnetic devices using computational micromagnetics. In this work, we identify and review different approaches to configuring simulation runs: (i the re-compilation of source code, (ii the use of configuration files, (iii the graphical user interface, and (iv embedding the simulation specification in an existing programming language to express the computational problem. We identify the advantages and disadvantages of different approaches and discuss their implications on effectiveness and reproducibility of computational studies and results. Following on from this, we design and describe a domain specific language for micromagnetics that is embedded in the Python language, and allows users to define the micromagnetic simulations they want to carry out in a flexible way. We have implemented this micromagnetic simulation description language together with a computational backend that executes the simulation task using the Object Oriented MicroMagnetic Framework (OOMMF. We illustrate the use of this Python interface for OOMMF by solving the micromagnetic standard problem 4. All the code is publicly available and is open source.

Facial pressure zones of an oronasal interface for noninvasive ventilation: a computer model analysis

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Luana Souto Barros

2014-12-01

Full Text Available OBJECTIVE: To study the effects of an oronasal interface (OI for noninvasive ventilation, using a three-dimensional (3D computational model with the ability to simulate and evaluate the main pressure zones (PZs of the OI on the human face. METHODS: We used a 3D digital model of the human face, based on a pre-established geometric model. The model simulated soft tissues, skull, and nasal cartilage. The geometric model was obtained by 3D laser scanning and post-processed for use in the model created, with the objective of separating the cushion from the frame. A computer simulation was performed to determine the pressure required in order to create the facial PZs. We obtained descriptive graphical images of the PZs and their intensity. RESULTS: For the graphical analyses of each face-OI model pair and their respective evaluations, we ran 21 simulations. The computer model identified several high-impact PZs in the nasal bridge and paranasal regions. The variation in soft tissue depth had a direct impact on the amount of pressure applied (438-724 cmH2O. CONCLUSIONS: The computer simulation results indicate that, in patients submitted to noninvasive ventilation with an OI, the probability of skin lesion is higher in the nasal bridge and paranasal regions. This methodology could increase the applicability of biomechanical research on noninvasive ventilation interfaces, providing the information needed in order to choose the interface that best minimizes the risk of skin lesion.

An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

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Jinyi Long

2017-01-01

Full Text Available The hybrid brain computer interface (BCI based on motor imagery (MI and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not result in optimal performance. Here, we present an efficient framework to optimize them together by concatenating the features of MI and P300 in a block diagonal form. Then a linear classifier under a dual spectral norm regularizer is applied to the combined features. Under this framework, the hybrid features of MI and P300 can be learned, selected, and combined together directly. Experimental results on the data set of hybrid BCI based on MI and P300 are provided to illustrate competitive performance of the proposed method against other conventional methods. This provides an evidence that the method used here contributes to the discrimination performance of the brain state in hybrid BCI.

A structural approach to constructing perspective efficient and reliable human-computer interfaces

International Nuclear Information System (INIS)

Balint, L.

1989-01-01

The principles of human-computer interface (HCI) realizations are investigated with the aim of getting closer to a general framework and thus, to a more or less solid background of constructing perspective efficient, reliable and cost-effective human-computer interfaces. On the basis of characterizing and classifying the different HCI solutions, the fundamental problems of interface construction are pointed out especially with respect to human error occurrence possibilities. The evolution of HCI realizations is illustrated by summarizing the main properties of past, present and foreseeable future interface generations. HCI modeling is pointed out to be a crucial problem in theoretical and practical investigations. Suggestions concerning HCI structure (hierarchy and modularity), HCI functional dynamics (mapping from input to output information), minimization of human error caused system failures (error-tolerance, error-recovery and error-correcting) as well as cost-effective HCI design and realization methodology (universal and application-oriented vs. application-specific solutions) are presented. The concept of RISC-based and SCAMP-type HCI components is introduced with the aim of having a reduced interaction scheme in communication and a well defined architecture in HCI components' internal structure. HCI efficiency and reliability are dealt with, by taking into account complexity and flexibility. The application of fast computerized prototyping is also briefly investigated as an experimental device of achieving simple, parametrized, invariant HCI models. Finally, a concise outline of an approach of how to construct ideal HCI's is also suggested by emphasizing the open questions and the need of future work related to the proposals, as well. (author). 14 refs, 6 figs

Evaluating a multi-player brain-computer interface game: challenge versus co-experience

NARCIS (Netherlands)

Gürkök, Hayrettin; Volpe, G; Reidsma, Dennis; Poel, Mannes; Camurri, A.; Obbink, Michel; Nijholt, Antinus

2013-01-01

Brain–computer interfaces (BCIs) have started to be considered as game controllers. The low level of control they provide prevents them from providing perfect control but allows the design of challenging games which can be enjoyed by players. Evaluation of enjoyment, or user experience (UX), is

Citation analysis of Computer Standards & Interfaces: Technical or also non-technical focus?

NARCIS (Netherlands)

G. van de Kaa (Geerten); H.J. de Vries (Henk); B. Baskaran (Balakumaran)

2015-01-01

textabstractThis paper analyzes to which extent research published in Computer Standards & Interfaces (CSI) has a technical focus. We find that CSI has been following its scope very closely in the last three years and that the majority of its publications have a technical focus. Articles published

Computer-Vision-Assisted Palm Rehabilitation With Supervised Learning.

Science.gov (United States)

Vamsikrishna, K M; Dogra, Debi Prosad; Desarkar, Maunendra Sankar

2016-05-01

Physical rehabilitation supported by the computer-assisted-interface is gaining popularity among health-care fraternity. In this paper, we have proposed a computer-vision-assisted contactless methodology to facilitate palm and finger rehabilitation. Leap motion controller has been interfaced with a computing device to record parameters describing 3-D movements of the palm of a user undergoing rehabilitation. We have proposed an interface using Unity3D development platform. Our interface is capable of analyzing intermediate steps of rehabilitation without the help of an expert, and it can provide online feedback to the user. Isolated gestures are classified using linear discriminant analysis (DA) and support vector machines (SVM). Finally, a set of discrete hidden Markov models (HMM) have been used to classify gesture sequence performed during rehabilitation. Experimental validation using a large number of samples collected from healthy volunteers reveals that DA and SVM perform similarly while applied on isolated gesture recognition. We have compared the results of HMM-based sequence classification with CRF-based techniques. Our results confirm that both HMM and CRF perform quite similarly when tested on gesture sequences. The proposed system can be used for home-based palm or finger rehabilitation in the absence of experts.

EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

Science.gov (United States)

Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

2016-01-01

Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

Data communications in a parallel active messaging interface of a parallel computer

Science.gov (United States)

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2013-10-29

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the parallel computer including a plurality of compute nodes that execute a parallel application, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a data communications instruction, the instruction characterized by an instruction type, the instruction specifying a transmission of transfer data from the origin endpoint to a target endpoint and transmitting, in accordance with the instruction type, the transfer data from the origin endpoint to the target endpoint.

Effects of muscle fatigue on the usability of a myoelectric human-computer interface.

Science.gov (United States)

Barszap, Alexander G; Skavhaug, Ida-Maria; Joshi, Sanjay S

2016-10-01

Electromyography-based human-computer interface development is an active field of research. However, knowledge on the effects of muscle fatigue for specific devices is limited. We have developed a novel myoelectric human-computer interface in which subjects continuously navigate a cursor to targets by manipulating a single surface electromyography (sEMG) signal. Two-dimensional control is achieved through simultaneous adjustments of power in two frequency bands through a series of dynamic low-level muscle contractions. Here, we investigate the potential effects of muscle fatigue during the use of our interface. In the first session, eight subjects completed 300 cursor-to-target trials without breaks; four using a wrist muscle and four using a head muscle. The wrist subjects returned for a second session in which a static fatiguing exercise took place at regular intervals in-between cursor-to-target trials. In the first session we observed no declines in performance as a function of use, even after the long period of use. In the second session, we observed clear changes in cursor trajectories, paired with a target-specific decrease in hit rates. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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...

A Novel Feature Optimization for Wearable Human-Computer Interfaces Using Surface Electromyography Sensors

Directory of Open Access Journals (Sweden)

Han Sun

2018-03-01

Full Text Available The novel human-computer interface (HCI using bioelectrical signals as input is a valuable tool to improve the lives of people with disabilities. In this paper, surface electromyography (sEMG signals induced by four classes of wrist movements were acquired from four sites on the lower arm with our designed system. Forty-two features were extracted from the time, frequency and time-frequency domains. Optimal channels were determined from single-channel classification performance rank. The optimal-feature selection was according to a modified entropy criteria (EC and Fisher discrimination (FD criteria. The feature selection results were evaluated by four different classifiers, and compared with other conventional feature subsets. In online tests, the wearable system acquired real-time sEMG signals. The selected features and trained classifier model were used to control a telecar through four different paradigms in a designed environment with simple obstacles. Performance was evaluated based on travel time (TT and recognition rate (RR. The results of hardware evaluation verified the feasibility of our acquisition systems, and ensured signal quality. Single-channel analysis results indicated that the channel located on the extensor carpi ulnaris (ECU performed best with mean classification accuracy of 97.45% for all movement’s pairs. Channels placed on ECU and the extensor carpi radialis (ECR were selected according to the accuracy rank. Experimental results showed that the proposed FD method was better than other feature selection methods and single-type features. The combination of FD and random forest (RF performed best in offline analysis, with 96.77% multi-class RR. Online results illustrated that the state-machine paradigm with a 125 ms window had the highest maneuverability and was closest to real-life control. Subjects could accomplish online sessions by three sEMG-based paradigms, with average times of 46.02, 49.06 and 48.08 s

Interface design of VSOP'94 computer code for safety analysis

Energy Technology Data Exchange (ETDEWEB)

Natsir, Khairina, E-mail: yenny@batan.go.id; Andiwijayakusuma, D.; Wahanani, Nursinta Adi [Center for Development of Nuclear Informatics - National Nuclear Energy Agency, PUSPIPTEK, Serpong, Tangerang, Banten (Indonesia); Yazid, Putranto Ilham [Center for Nuclear Technology, Material and Radiometry- National Nuclear Energy Agency, Jl. Tamansari No.71, Bandung 40132 (Indonesia)

2014-09-30

Today, most software applications, also in the nuclear field, come with a graphical user interface. VSOP'94 (Very Superior Old Program), was designed to simplify the process of performing reactor simulation. VSOP is a integrated code system to simulate the life history of a nuclear reactor that is devoted in education and research. One advantage of VSOP program is its ability to calculate the neutron spectrum estimation, fuel cycle, 2-D diffusion, resonance integral, estimation of reactors fuel costs, and integrated thermal hydraulics. VSOP also can be used to comparative studies and simulation of reactor safety. However, existing VSOP is a conventional program, which was developed using Fortran 65 and have several problems in using it, for example, it is only operated on Dec Alpha mainframe platforms and provide text-based output, difficult to use, especially in data preparation and interpretation of results. We develop a GUI-VSOP, which is an interface program to facilitate the preparation of data, run the VSOP code and read the results in a more user friendly way and useable on the Personal 'Computer (PC). Modifications include the development of interfaces on preprocessing, processing and postprocessing. GUI-based interface for preprocessing aims to provide a convenience way in preparing data. Processing interface is intended to provide convenience in configuring input files and libraries and do compiling VSOP code. Postprocessing interface designed to visualized the VSOP output in table and graphic forms. GUI-VSOP expected to be useful to simplify and speed up the process and analysis of safety aspects.

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.

What Do IT-People Know About the (Nordic) History of Computers and User Interfaces?

DEFF Research Database (Denmark)

Jørgensen, Anker Helms

2009-01-01

:  This paper reports a preliminary, empirical exploration of what IT-people know about the history of computers and user interfaces.  The principal motivation for the study is that the younger generations such as students in IT seem to know very little about these topics.  The study employed...... to become the designation or even the icon for the computer.  In other words, one of the key focal points in the area of human-computer interaction: to make the computer as such invisible seems to have been successful...

US Army Weapon Systems Human-Computer Interface (WSHCI) style guide, Version 1

Energy Technology Data Exchange (ETDEWEB)

Avery, L.W.; O`Mara, P.A.; Shepard, A.P.

1996-09-30

A stated goal of the U.S. Army has been the standardization of the human computer interfaces (HCIS) of its system. Some of the tools being used to accomplish this standardization are HCI design guidelines and style guides. Currently, the Army is employing a number of style guides. While these style guides provide good guidance for the command, control, communications, computers, and intelligence (C4I) domain, they do not necessarily represent the more unique requirements of the Army`s real time and near-real time (RT/NRT) weapon systems. The Office of the Director of Information for Command, Control, Communications, and Computers (DISC4), in conjunction with the Weapon Systems Technical Architecture Working Group (WSTAWG), recognized this need as part of their activities to revise the Army Technical Architecture (ATA). To address this need, DISC4 tasked the Pacific Northwest National Laboratory (PNNL) to develop an Army weapon systems unique HCI style guide. This document, the U.S. Army Weapon Systems Human-Computer Interface (WSHCI) Style Guide, represents the first version of that style guide. The purpose of this document is to provide HCI design guidance for RT/NRT Army systems across the weapon systems domains of ground, aviation, missile, and soldier systems. Each domain should customize and extend this guidance by developing their domain-specific style guides, which will be used to guide the development of future systems within their domains.

Computer-based auditory phoneme discrimination training improves speech recognition in noise in experienced adult cochlear implant listeners.

Science.gov (United States)

Schumann, Annette; Serman, Maja; Gefeller, Olaf; Hoppe, Ulrich

2015-03-01

Specific computer-based auditory training may be a useful completion in the rehabilitation process for cochlear implant (CI) listeners to achieve sufficient speech intelligibility. This study evaluated the effectiveness of a computerized, phoneme-discrimination training programme. The study employed a pretest-post-test design; participants were randomly assigned to the training or control group. Over a period of three weeks, the training group was instructed to train in phoneme discrimination via computer, twice a week. Sentence recognition in different noise conditions (moderate to difficult) was tested pre- and post-training, and six months after the training was completed. The control group was tested and retested within one month. Twenty-seven adult CI listeners who had been using cochlear implants for more than two years participated in the programme; 15 adults in the training group, 12 adults in the control group. Besides significant improvements for the trained phoneme-identification task, a generalized training effect was noted via significantly improved sentence recognition in moderate noise. No significant changes were noted in the difficult noise conditions. Improved performance was maintained over an extended period. Phoneme-discrimination training improves experienced CI listeners' speech perception in noise. Additional research is needed to optimize auditory training for individual benefit.

Interfacing of home-made photoacoustic spectrometer to computer

International Nuclear Information System (INIS)

Dhobale, A.R.; Chaturvedi, T.P.; Venkiteswaran, S.; Sastry, M.D.

1996-01-01

This report describes the interfacing of Photo Acoustic Spectrometer (PAS) fabricated in-house to a personal computer. This work was carried out to make a state of the art computer based spectrometer with provision for automatic background correction and also which gives hard copy of the spectrum. This report includes the development of software necessary to acquire data and for further processing of the signal. The monochromator used was modified for obtaining a +5 V pulse for each wavelength position. This pulse was further used for controlling the data acquisition and automatic increment of wavelength. Software program was developed in Quick Basic ver. 4.5 environment for acquisition, storage, display and analysis of the spectrum. The program displays on-line spectrum building up on the monitor. Another program converts the acquired spectrum into a normalized spectrum comparing with carbon spectrum stored already in addition to the S/N ratio improvement. The photo acoustic cell and chopper unit were also modified for improving the performance of the PAS unit. (author). 11 refs., 13 figs., 2 tabs

Quality control of the gamma camera/computer interface

International Nuclear Information System (INIS)

Busemann-Sokole, E.

1983-01-01

Reporting on the conference mentioned, the author indicates that technical inspection of the gamma camera and the attached computer each by themselves is not sufficient. The parts of the interface and the hardware or software can contain sources of error. In order to obtain the best diagnostic image a number of control measurements are recommended dealing with image intensifying, intensifier offset, linearity of transformation, exclusion of 'data drop' or 'bit drop', 2-pulse timing, correct response with different counting rates, and response to triggers (electrocardiogram). The last and most important recommendation is to record in writing particulars of each inspection and control measurement, particulars and solutions of problems and modifications in hardware and software. (Auth.)

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.

New generation of 3D desktop computer interfaces

Science.gov (United States)

Skerjanc, Robert; Pastoor, Siegmund

1997-05-01

Today's computer interfaces use 2-D displays showing windows, icons and menus and support mouse interactions for handling programs and data files. The interface metaphor is that of a writing desk with (partly) overlapping sheets of documents placed on its top. Recent advances in the development of 3-D display technology give the opportunity to take the interface concept a radical stage further by breaking the design limits of the desktop metaphor. The major advantage of the envisioned 'application space' is, that it offers an additional, immediately perceptible dimension to clearly and constantly visualize the structure and current state of interrelations between documents, videos, application programs and networked systems. In this context, we describe the development of a visual operating system (VOS). Under VOS, applications appear as objects in 3-D space. Users can (graphically connect selected objects to enable communication between the respective applications. VOS includes a general concept of visual and object oriented programming for tasks ranging from, e.g., low-level programming up to high-level application configuration. In order to enable practical operation in an office or at home for many hours, the system should be very comfortable to use. Since typical 3-D equipment used, e.g., in virtual-reality applications (head-mounted displays, data gloves) is rather cumbersome and straining, we suggest to use off-head displays and contact-free interaction techniques. In this article, we introduce an autostereoscopic 3-D display and connected video based interaction techniques which allow viewpoint-depending imaging (by head tracking) and visually controlled modification of data objects and links (by gaze tracking, e.g., to pick, 3-D objects just by looking at them).

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.

Data communications in a parallel active messaging interface of a parallel computer

Science.gov (United States)

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2013-11-12

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer composed of compute nodes that execute a parallel application, each compute node including application processors that execute the parallel application and at least one management processor dedicated to gathering information regarding data communications. The PAMI is composed of data communications endpoints, each endpoint composed of a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources. Embodiments function by gathering call site statistics describing data communications resulting from execution of data communications instructions and identifying in dependence upon the call cite statistics a data communications algorithm for use in executing a data communications instruction at a call site in the parallel application.

Visibility Aspects Importance of User Interface Reception in Cloud Computing Applications with Increased Automation

OpenAIRE

Haxhixhemajli, Denis

2012-01-01

Visibility aspects of User Interfaces are important; they deal with the crucial phase of human-computer interaction. They allow users to perform and at the same time hide the complexity of the system. Acceptance of new systems depends on how visibility aspects of the User Interfaces are presented. Human eyes make the first contact with the appearance of any system by so it generates the very beginning of the human – application interaction. In this study it is enforced that visibility aspects...

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

Science.gov (United States)

Papageorgiou, T Dorina; Lisinski, Jonathan M; McHenry, Monica A; White, Jason P; LaConte, Stephen M

2013-08-13

Brain-computer interfaces (BCIs) can convert mental states into signals to drive real-world devices, but it is not known if a given covert task is the same when performed with and without BCI-based control. Using a BCI likely involves additional cognitive processes, such as multitasking, attention, and conflict monitoring. In addition, it is challenging to measure the quality of covert task performance. We used whole-brain classifier-based real-time functional MRI to address these issues, because the method provides both classifier-based maps to examine the neural requirements of BCI and classification accuracy to quantify the quality of task performance. Subjects performed a covert counting task at fast and slow rates to control a visual interface. Compared with the same task when viewing but not controlling the interface, we observed that being in control of a BCI improved task classification of fast and slow counting states. Additional BCI control increased subjects' whole-brain signal-to-noise ratio compared with the absence of control. The neural pattern for control consisted of a positive network comprised of dorsal parietal and frontal regions and the anterior insula of the right hemisphere as well as an expansive negative network of regions. These findings suggest that real-time functional MRI can serve as a platform for exploring information processing and frontoparietal and insula network-based regulation of whole-brain task signal-to-noise ratio.

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

Enrichment of Human-Computer Interaction in Brain-Computer Interfaces via Virtual Environments

Directory of Open Access Journals (Sweden)

Alonso-Valerdi Luz María

2017-01-01

Full Text Available Tridimensional representations stimulate cognitive processes that are the core and foundation of human-computer interaction (HCI. Those cognitive processes take place while a user navigates and explores a virtual environment (VE and are mainly related to spatial memory storage, attention, and perception. VEs have many distinctive features (e.g., involvement, immersion, and presence that can significantly improve HCI in highly demanding and interactive systems such as brain-computer interfaces (BCI. BCI is as a nonmuscular communication channel that attempts to reestablish the interaction between an individual and his/her environment. Although BCI research started in the sixties, this technology is not efficient or reliable yet for everyone at any time. Over the past few years, researchers have argued that main BCI flaws could be associated with HCI issues. The evidence presented thus far shows that VEs can (1 set out working environmental conditions, (2 maximize the efficiency of BCI control panels, (3 implement navigation systems based not only on user intentions but also on user emotions, and (4 regulate user mental state to increase the differentiation between control and noncontrol modalities.

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.

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.

BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics.

Science.gov (United States)

Ayres, Daniel L; Darling, Aaron; Zwickl, Derrick J; Beerli, Peter; Holder, Mark T; Lewis, Paul O; Huelsenbeck, John P; Ronquist, Fredrik; Swofford, David L; Cummings, Michael P; Rambaut, Andrew; Suchard, Marc A

2012-01-01

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.

The Unlock Project: a Python-based framework for practical brain-computer interface communication "app" development.

Science.gov (United States)

Brumberg, Jonathan S; Lorenz, Sean D; Galbraith, Byron V; Guenther, Frank H

2012-01-01

In this paper we present a framework for reducing the development time needed for creating applications for use in non-invasive brain-computer interfaces (BCI). Our framework is primarily focused on facilitating rapid software "app" development akin to current efforts in consumer portable computing (e.g. smart phones and tablets). This is accomplished by handling intermodule communication without direct user or developer implementation, instead relying on a core subsystem for communication of standard, internal data formats. We also provide a library of hardware interfaces for common mobile EEG platforms for immediate use in BCI applications. A use-case example is described in which a user with amyotrophic lateral sclerosis participated in an electroencephalography-based BCI protocol developed using the proposed framework. We show that our software environment is capable of running in real-time with updates occurring 50-60 times per second with limited computational overhead (5 ms system lag) while providing accurate data acquisition and signal analysis.

Archaeologies of touch interfacing with haptics from electricity to computing

CERN Document Server

Parisi, David

2018-01-01

David Parisi offers the first full history of new computing technologies known as haptic interfaces--which use electricity, vibration, and force feedback to stimulate the sense of touch--showing how the efforts of scientists and engineers over the past 300 years have gradually remade and redefined our sense of touch. Archaeologies of Touch offers a timely and provocative engagement with the long history of touch technology that helps us confront and question the power relations underpinning the project of giving touch its own set of technical media.

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.

Fully Online Multicommand Brain-Computer Interface with Visual Neurofeedback Using SSVEP Paradigm

Directory of Open Access Journals (Sweden)

Pablo Martinez

2007-01-01

Full Text Available We propose a new multistage procedure for a real-time brain-machine/computer interface (BCI. The developed system allows a BCI user to navigate a small car (or any other object on the computer screen in real time, in any of the four directions, and to stop it if necessary. Extensive experiments with five young healthy subjects confirmed the high performance of the proposed online BCI system. The modular structure, high speed, and the optimal frequency band characteristics of the BCI platform are features which allow an extension to a substantially higher number of commands in the near future.

Development of a graphical interface computer code for reactor fuel reloading optimization

International Nuclear Information System (INIS)

Do Quang Binh; Nguyen Phuoc Lan; Bui Xuan Huy

2007-01-01

This report represents the results of the project performed in 2007. The aim of this project is to develop a graphical interface computer code that allows refueling engineers to design fuel reloading patterns for research reactor using simulated graphical model of reactor core. Besides, this code can perform refueling optimization calculations based on genetic algorithms as well as simulated annealing. The computer code was verified based on a sample problem, which relies on operational and experimental data of Dalat research reactor. This code can play a significant role in in-core fuel management practice at nuclear research reactor centers and in training. (author)

Implementation of active electrodes on a brain-computer interface and its application as P300 speller

International Nuclear Information System (INIS)

Aguero Rojas, Eliecer

2013-01-01

A brain computer interface has implemented using open hardware called Modular EEG, created by The OpenEEG Project and distributed by the company Olimex Ltd. That hardware is modified to use active electrodes, instead of passive electrodes, for acquiring electroencephalographic signals. The application has been given to the interface has been a speller P300; for which has used the BC12000 open software that has the necessary configuration for the application. P300 speller has used a protocol in each session so that could be standardize the method to different users. Valuing the results with three neuropsychological tests, was within the objectives; however, has not been achieved by the limitation in time of project implementation. A brain computer interface has been used with passive electrodes; implemented in the same way that the BCI with active electrodes; and has worked better than the interface with active electrodes. One of the major advantages that has been observed of passive electrodes on the actives has been the size of the same, because the liabilities are smaller and therefore, easier to place preventing the hair of the user, which increases the noise in the signal. (author) [es

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.

Brain-computer interfaces current trends and applications

CERN Document Server

Azar, Ahmad

2015-01-01

The success of a BCI system depends as much on the system itself as on the user’s ability to produce distinctive EEG activity. BCI systems can be divided into two groups according to the placement of the electrodes used to detect and measure neurons firing in the brain. These groups are: invasive systems, electrodes are inserted directly into the cortex are used for single cell or multi unit recording, and electrocorticography (EcoG), electrodes are placed on the surface of the cortex (or dura); noninvasive systems, they are placed on the scalp and use electroencephalography (EEG) or magnetoencephalography (MEG) to detect neuron activity. The book is basically divided into three parts. The first part of the book covers the basic concepts and overviews of Brain Computer Interface. The second part describes new theoretical developments of BCI systems. The third part covers views on real applications of BCI systems.

Discrimination ability of the Energy score

DEFF Research Database (Denmark)

Pinson, Pierre; Tastu, Julija

as appealing since being proper, we show that its discrimination ability may be limited when focusing on the dependence structure of multivariate probabilistic forecasts. For the case of multivariate Gaussian process, a theoretical upper for such discrimination ability is derived and discussed. This limited...... discrimination ability may eventually get compromised by computational and sampling issues, as dimension increases....

User interface support

Science.gov (United States)

Lewis, Clayton; Wilde, Nick

1989-01-01

Space construction will require heavy investment in the development of a wide variety of user interfaces for the computer-based tools that will be involved at every stage of construction operations. Using today's technology, user interface development is very expensive for two reasons: (1) specialized and scarce programming skills are required to implement the necessary graphical representations and complex control regimes for high-quality interfaces; (2) iteration on prototypes is required to meet user and task requirements, since these are difficult to anticipate with current (and foreseeable) design knowledge. We are attacking this problem by building a user interface development tool based on extensions to the spreadsheet model of computation. The tool provides high-level support for graphical user interfaces and permits dynamic modification of interfaces, without requiring conventional programming concepts and skills.

Two ions coupled to an optical cavity : from an enhanced quantum computer interface towards distributed quantum computing

International Nuclear Information System (INIS)

Casabone, B.

2015-01-01

Distributed quantum computing, an approach to scale up the computational power of quantum computers, requires entanglement between nodes of a quantum network. In our research group, two building blocks of schemes to entangle two ion-based quantum computers using cavity-based quantum interfaces have recently been demonstrated: ion-photon entanglement and ion-photon state mapping. In this thesis work, we extend the first building block in order to entangle two ions located in the same optical cavity. The entanglement generated by this protocol is efficient and heralded, and as it does not rely on the fact that ions interact with the same cavity, our results are a stepping stone towards the efficient generation of entanglement of remote ion-based quantum computers. In the second part of this thesis, we discuss how collective effects can be used to improve the performance of a cavity-based quantum interface. We show that by using two ions in the so-called superradiant state, the coupling strength between the two ions and the optical cavity is effectively increased compared to the single-ion case. As a complementary result, the creation of a state of two ions that exhibits a reduced coupling strength to the optical cavity, i.e., a subradiant state, is shown. Finally, we demonstrate a direct application of the increased coupling strength that the superradiant state exhibits by showing an enhanced version of the ion-photon state mapping process. By using the current setup and a second one that is being assembled, we intend to build a quantum network. The heralded ion-ion entanglement protocol presented in this thesis work will be used to entangle ions located in both setups, an experiment that requires photons generated in both apparatuses to be indistinguishable. Collective effects then can be used to modify the waveform of photons exiting the cavity in order to effect the desired photon indistinguishability. (author) [de

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.

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

Science.gov (United States)

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

2014-12-01

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

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

Science.gov (United States)

Revechkis, Boris; Aflalo, Tyson N S; Kellis, Spencer; Pouratian, Nader; Andersen, Richard A

2014-12-01

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

Optimizing event-related potential based brain-computer interfaces: a systematic evaluation of dynamic stopping methods

Science.gov (United States)

Schreuder, Martijn; Höhne, Johannes; Blankertz, Benjamin; Haufe, Stefan; Dickhaus, Thorsten; Tangermann, Michael

2013-06-01

Objective. In brain-computer interface (BCI) research, systems based on event-related potentials (ERP) are considered particularly successful and robust. This stems in part from the repeated stimulation which counteracts the low signal-to-noise ratio in electroencephalograms. Repeated stimulation leads to an optimization problem, as more repetitions also cost more time. The optimal number of repetitions thus represents a data-dependent trade-off between the stimulation time and the obtained accuracy. Several methods for dealing with this have been proposed as ‘early stopping’, ‘dynamic stopping’ or ‘adaptive stimulation’. Despite their high potential for BCI systems at the patient's bedside, those methods are typically ignored in current BCI literature. The goal of the current study is to assess the benefit of these methods. Approach. This study assesses for the first time the existing methods on a common benchmark of both artificially generated data and real BCI data of 83 BCI sessions, allowing for a direct comparison between these methods in the context of text entry. Main results. The results clearly show the beneficial effect on the online performance of a BCI system, if the trade-off between the number of stimulus repetitions and accuracy is optimized. All assessed methods work very well for data of good subjects, and worse for data of low-performing subjects. Most methods, however, are robust in the sense that they do not reduce the performance below the baseline of a simple no stopping strategy. Significance. Since all methods can be realized as a module between the BCI and an application, minimal changes are needed to include these methods into existing BCI software architectures. Furthermore, the hyperparameters of most methods depend to a large extend on only a single variable—the discriminability of the training data. For the convenience of BCI practitioners, the present study proposes linear regression coefficients for directly estimating

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.

Si Interface Barrier Modification on Memristor for Brain-Inspired Computing

Science.gov (United States)

Wu, Wei; Wu, Huaqiang; Gao, Bin; Qian, He

2017-06-01

Memristor is an emerging technology aimed at implementing neuromorphic computing in hardware system. Resistive random access memory (RRAM) is a kind of memristor with excellent performance, but abrupt switching in the set process influences the efficiency of neuromorphic system. In this study, we present an interface switching memristor device based on TiN/Si/TaOx/TiN stack and CMOS compatible fabrication process to achieve gradually resistive switching both in set and reset processes. The devices show a more than 10 switching window. The related switching mechanism is discussed.

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.

Fragment-based docking: development of the CHARMMing Web user interface as a platform for computer-aided drug design.

Science.gov (United States)

Pevzner, Yuri; Frugier, Emilie; Schalk, Vinushka; Caflisch, Amedeo; Woodcock, H Lee

2014-09-22

Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser. One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing's capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of "re-dockings" with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing's docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening.

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.

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.

Study of signal discrimination for timing measurements

CERN Document Server

Krepelkova, Marta

2017-01-01

The timing detectors of the CMS-TOTEM Precision Proton Spectrometer (CT-PPS) are currently read out using discrete components, separated into three boards; the first board hosts the sensors and the amplifiers, the second one hosts the discriminators and the third is dedicated to the Time to Digital Converter (TDC) and to the interface with the data acquisition system (DAQ). This work proposes a new front-end electronics for the timing detector, with sensors, amplifiers and discriminators integrated on the same board. We simulated an updated version of the amplifier together with a discriminator designed using commercial components. We decided to use an LVDS buffer as a discriminator, because of its cost, availability, speed and lo w power consumption. As a proof of concept, we used the LVDS input of an FPGA to discriminate signals produced by a detector prototype, using a radioactive source.

Computation of the Distribution of the Fiber-Matrix Interface Cracks in the Edge Trimming of CFRP

Science.gov (United States)

Wang, Fu-ji; Zhang, Bo-yu; Ma, Jian-wei; Bi, Guang-jian; Hu, Hai-bo

2018-04-01

Edge trimming is commonly used to bring the CFRP components to right dimension and shape in aerospace industries. However, various forms of undesirable machining damage occur frequently which will significantly decrease the material performance of CFRP. The damage is difficult to predict and control due to the complicated changing laws, causing unsatisfactory machining quality of CFRP components. Since the most of damage has the same essence: the fiber-matrix interface cracks, this study aims to calculate the distribution of them in edge trimming of CFRP, thereby to obtain the effects of the machining parameters, which could be helpful to guide the optimal selection of the machining parameters in engineering. Through the orthogonal cutting experiments, the quantitative relation between the fiber-matrix interface crack depth and the fiber cutting angle, cutting depth as well as cutting speed is established. According to the analysis on material removal process on any location of the workpiece in edge trimming, the instantaneous cutting parameters are calculated, and the formation process of the fiber-matrix interface crack is revealed. Finally, the computational method for the fiber-matrix interface cracks in edge trimming of CFRP is proposed. Upon the computational results, it is found that the fiber orientations of CFRP workpieces is the most significant factor on the fiber-matrix interface cracks, which can not only change the depth of them from micrometers to millimeters, but control the distribution image of them. Other machining parameters, only influence the fiber-matrix interface cracks depth but have little effect on the distribution image.

U.S. Army weapon systems human-computer interface style guide. Version 2

Energy Technology Data Exchange (ETDEWEB)

Avery, L.W.; O`Mara, P.A.; Shepard, A.P.; Donohoo, D.T.

1997-12-31

A stated goal of the US Army has been the standardization of the human computer interfaces (HCIs) of its system. Some of the tools being used to accomplish this standardization are HCI design guidelines and style guides. Currently, the Army is employing a number of HCI design guidance documents. While these style guides provide good guidance for the command, control, communications, computers, and intelligence (C4I) domain, they do not necessarily represent the more unique requirements of the Army`s real time and near-real time (RT/NRT) weapon systems. The Office of the Director of Information for Command, Control, Communications, and Computers (DISC4), in conjunction with the Weapon Systems Technical Architecture Working Group (WSTAWG), recognized this need as part of their activities to revise the Army Technical Architecture (ATA), now termed the Joint Technical Architecture-Army (JTA-A). To address this need, DISC4 tasked the Pacific Northwest National Laboratory (PNNL) to develop an Army weapon systems unique HCI style guide, which resulted in the US Army Weapon Systems Human-Computer Interface (WSHCI) Style Guide Version 1. Based on feedback from the user community, DISC4 further tasked PNNL to revise Version 1 and publish Version 2. The intent was to update some of the research and incorporate some enhancements. This document provides that revision. The purpose of this document is to provide HCI design guidance for the RT/NRT Army system domain across the weapon systems subdomains of ground, aviation, missile, and soldier systems. Each subdomain should customize and extend this guidance by developing their domain-specific style guides, which will be used to guide the development of future systems within their subdomains.

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

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

2015-03-31

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).

Cognitive assessment in Amyotrophic Lateral Sclerosis by means of P300-Brain Computer Interface: a preliminary study.

Science.gov (United States)

Poletti, Barbara; Carelli, Laura; Solca, Federica; Lafronza, Annalisa; Pedroli, Elisa; Faini, Andrea; Zago, Stefano; Ticozzi, Nicola; Meriggi, Paolo; Cipresso, Pietro; Lulé, Dorothée; Ludolph, Albert C; Riva, Giuseppe; Silani, Vincenzo

To investigate the use of P300-based Brain Computer Interface (BCI) technology for the administration of motor-verbal free cognitive tests in Amyotrophic Lateral Sclerosis (ALS). We recruited 15 ALS patients and 15 age- and education-matched healthy subjects. All participants underwent a BCI-based neuropsychological assessment, together with two standard cognitive screening tools (FAB, MoCA), two psychological questionnaires (BDI, STAI-Y) and a usability questionnaire. For patients, clinical and respiratory examinations were also performed, together with a behavioural assessment (FBI). Correlations were observed between standard cognitive and BCI-based neuropsychological assessment, mainly concerning execution times in the ALS group. Moreover, patients provided positive rates concerning the BCI perceived usability and subjective experience. Finally, execution times at the BCI-based neuropsychological assessment were useful to discriminate patients from controls, with patients achieving lower processing speed than controls regarding executive functions. The developed motor-verbal free neuropsychological battery represents an innovative approach, that could provide relevant information for clinical practice and ethical issues. Its use for cognitive evaluation throughout the course of ALS, currently not available by means of standard assessment, must be addressed in further longitudinal validation studies. Further work will be aimed at refining the developed system and enlarging the cognitive spectrum investigated.

Student teaching and research laboratory focusing on brain-computer interface paradigms--A creative environment for computer science students.

Science.gov (United States)

Rutkowski, Tomasz M

2015-08-01

This paper presents an applied concept of a brain-computer interface (BCI) student research laboratory (BCI-LAB) at the Life Science Center of TARA, University of Tsukuba, Japan. Several successful case studies of the student projects are reviewed together with the BCI Research Award 2014 winner case. The BCI-LAB design and project-based teaching philosophy is also explained. Future teaching and research directions summarize the review.

Flexusi Interface Builder For Computer Based Accelerator Monitoring And Control System

CERN Document Server

Kurakin, V G; Kurakin, P V

2004-01-01

We have developed computer code for any desired graphics user interface designing for monitoring and control system at the executable level. This means that operator can build up measurement console consisting of virtual devices before or even during real experiment without recompiling source file. Such functionality results in number of advantages comparing with traditional programming. First of all any risk disappears to introduce bug into source code. Another important thing is the fact the both program developers and operator staff do not interface in developing ultimate product (measurement console). Thus, small team without detailed project can design even very complicated monitoring and control system. For the reason mentioned below, approach suggested is especially helpful for large complexes to be monitored and control, accelerator being among them. The program code consists of several modules, responsible for data acquisition, control and representation. Borland C++ Builder technologies based on VCL...

Quadcopter control in three-dimensional space using a noninvasive motor imagery based brain-computer interface

Science.gov (United States)

LaFleur, Karl; Cassady, Kaitlin; Doud, Alexander; Shades, Kaleb; Rogin, Eitan; He, Bin

2013-01-01

Objective At the balanced intersection of human and machine adaptation is found the optimally functioning brain-computer interface (BCI). In this study, we report a novel experiment of BCI controlling a robotic quadcopter in three-dimensional physical space using noninvasive scalp EEG in human subjects. We then quantify the performance of this system using metrics suitable for asynchronous BCI. Lastly, we examine the impact that operation of a real world device has on subjects’ control with comparison to a two-dimensional virtual cursor task. Approach Five human subjects were trained to modulate their sensorimotor rhythms to control an AR Drone navigating a three-dimensional physical space. Visual feedback was provided via a forward facing camera on the hull of the drone. Individual subjects were able to accurately acquire up to 90.5% of all valid targets presented while travelling at an average straight-line speed of 0.69 m/s. Significance Freely exploring and interacting with the world around us is a crucial element of autonomy that is lost in the context of neurodegenerative disease. Brain-computer interfaces are systems that aim to restore or enhance a user’s ability to interact with the environment via a computer and through the use of only thought. We demonstrate for the first time the ability to control a flying robot in the three-dimensional physical space using noninvasive scalp recorded EEG in humans. Our work indicates the potential of noninvasive EEG based BCI systems to accomplish complex control in three-dimensional physical space. The present study may serve as a framework for the investigation of multidimensional non-invasive brain-computer interface control in a physical environment using telepresence robotics. PMID:23735712

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces

Directory of Open Access Journals (Sweden)

Gorin Andrey A

2008-05-01

Full Text Available Abstract Background Protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the Protein Data Bank (PDB. Results We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1 comprehensively collecting all protein-protein interfaces; (2 clustering similar protein-protein interfaces together; (3 estimating the probability that each cluster is relevant based on a diverse set of properties; and (4 combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the Protein Interface Server (PInS website (see Availability and requirements section. Conclusion Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

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.

Interface models

DEFF Research Database (Denmark)

Ravn, Anders P.; Staunstrup, Jørgen

1994-01-01

This paper proposes a model for specifying interfaces between concurrently executing modules of a computing system. The model does not prescribe a particular type of communication protocol and is aimed at describing interfaces between both software and hardware modules or a combination of the two....... The model describes both functional and timing properties of an 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

A Time-Frequency Approach to Feature Extraction for a Brain-Computer Interface with a Comparative Analysis of Performance Measures

Directory of Open Access Journals (Sweden)

T. M. McGinnity

2005-11-01

Full Text Available The paper presents an investigation into a time-frequency (TF method for extracting features from the electroencephalogram (EEG recorded from subjects performing imagination of left- and right-hand movements. The feature extraction procedure (FEP extracts frequency domain information to form features whilst time-frequency resolution is attained by localising the fast Fourier transformations (FFTs of the signals to specific windows localised in time. All features are extracted at the rate of the signal sampling interval from a main feature extraction (FE window through which all data passes. Subject-specific frequency bands are selected for optimal feature extraction and intraclass variations are reduced by smoothing the spectra for each signal by an interpolation (IP process. The TF features are classified using linear discriminant analysis (LDA. The FE window has potential advantages for the FEP to be applied in an online brain-computer interface (BCI. The approach achieves good performance when quantified by classification accuracy (CA rate, information transfer (IT rate, and mutual information (MI. The information that these performance measures provide about a BCI system is analysed and the importance of this is demonstrated through the results.

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...

Molecular discriminators using single wall carbon nanotubes

International Nuclear Information System (INIS)

Bhattacharyya, Tamoghna; Dasgupta, Anjan Kr; Ray, Nihar Ranjan; Sarkar, Sabyasachi

2012-01-01

The interaction between single wall carbon nanotubes (SWNTs) and amphiphilic molecules has been studied in a solid phase. SWNTs are allowed to interact with different amphiphilic probes (e.g. lipids) in a narrow capillary interface. Contact between strong hydrophobic and amphiphilic interfaces leads to a molecular restructuring of the lipids at the interface. The geometry of the diffusion front and the rate and the extent of diffusion of the interface are dependent on the structure of the lipid at the interface. Lecithin having a linear tail showed greater mobility of the interface as compared to a branched tail lipid like dipalmitoyl phosphatidylcholine, indicating the hydrophobic interaction between single wall carbon nanotube core and the hydrophobic tail of the lipid. Solid phase interactions between SWNT and lipids can thus become a very simple but efficient means of discriminating amphiphilic molecules in general and lipids in particular. (paper)

A novel P300-based brain-computer interface stimulus presentation paradigm: moving beyond rows and columns

Science.gov (United States)

Townsend, G.; LaPallo, B.K.; Boulay, C.B.; Krusienski, D.J.; Frye, G.E.; Hauser, C.K.; Schwartz, N.E.; Vaughan, T.M.; Wolpaw, J.R.; Sellers, E.W.

2010-01-01

Objective An electroencephalographic brain-computer interface (BCI) can provide a non-muscular means of communication for people with amyotrophic lateral sclerosis (ALS) or other neuromuscular disorders. We present a novel P300-based BCI stimulus presentation – the checkerboard paradigm (CBP). CBP performance is compared to that of the standard row/column paradigm (RCP) introduced by Farwell and Donchin (1988). Methods Using an 8×9 matrix of alphanumeric characters and keyboard commands, 18 participants used the CBP and RCP in counter-balanced fashion. With approximately 9 – 12 minutes of calibration data, we used a stepwise linear discriminant analysis for online classification of subsequent data. Results Mean online accuracy was significantly higher for the CBP, 92%, than for the RCP, 77%. Correcting for extra selections due to errors, mean bit rate was also significantly higher for the CBP, 23 bits/min, than for the RCP, 17 bits/min. Moreover, the two paradigms produced significantly different waveforms. Initial tests with three advanced ALS participants produced similar results. Furthermore, these individuals preferred the CBP to the RCP. Conclusions These results suggest that the CBP is markedly superior to the RCP in performance and user acceptability. Significance The CBP has the potential to provide a substantially more effective BCI than the RCP. This is especially important for people with severe neuromuscular disabilities. PMID:20347387

x-y-recording in transmission electron microscopy. A versatile and inexpensive interface to personal computers with application to stereology.

Science.gov (United States)

Rickmann, M; Siklós, L; Joó, F; Wolff, J R

1990-09-01

An interface for IBM XT/AT-compatible computers is described which has been designed to read the actual specimen stage position of electron microscopes. The complete system consists of (i) optical incremental encoders attached to the x- and y-stage drivers of the microscope, (ii) two keypads for operator input, (iii) an interface card fitted to the bus of the personal computer, (iv) a standard configuration IBM XT (or compatible) personal computer optionally equipped with a (v) HP Graphic Language controllable colour plotter. The small size of the encoders and their connection to the stage drivers by simple ribbed belts allows an easy adaptation of the system to most electron microscopes. Operation of the interface card itself is supported by any high-level language available for personal computers. By the modular concept of these languages, the system can be customized to various applications, and no computer expertise is needed for actual operation. The present configuration offers an inexpensive attachment, which covers a wide range of applications from a simple notebook to high-resolution (200-nm) mapping of tissue. Since section coordinates can be processed in real-time, stereological estimations can be derived directly "on microscope". This is exemplified by an application in which particle numbers were determined by the disector method.

Cognitive assessment of executive functions using brain computer interface and eye-tracking

Directory of Open Access Journals (Sweden)

P. Cipresso

2013-03-01

Full Text Available New technologies to enable augmentative and alternative communication in Amyotrophic Lateral Sclerosis (ALS have been recently used in several studies. However, a comprehensive battery for cognitive assessment has not been implemented yet. Brain computer interfaces are innovative systems able to generate a control signal from brain responses conveying messages directly to a computer. Another available technology for communication purposes is the Eye-tracker system, that conveys messages from eye-movement to a computer. In this study we explored the use of these two technologies for the cognitive assessment of executive functions in a healthy population and in a ALS patient, also verifying usability, pleasantness, fatigue, and emotional aspects related to the setting. Our preliminary results may have interesting implications for both clinical practice (the availability of an effective tool for neuropsychological evaluation of ALS patients and ethical issues.

Performance monitoring for brain-computer-interface actions.

Science.gov (United States)

Schurger, Aaron; Gale, Steven; Gozel, Olivia; Blanke, Olaf

2017-02-01

When presented with a difficult perceptual decision, human observers are able to make metacognitive judgements of subjective certainty. Such judgements can be made independently of and prior to any overt response to a sensory stimulus, presumably via internal monitoring. Retrospective judgements about one's own task performance, on the other hand, require first that the subject perform a task and thus could potentially be made based on motor processes, proprioceptive, and other sensory feedback rather than internal monitoring. With this dichotomy in mind, we set out to study performance monitoring using a brain-computer interface (BCI), with which subjects could voluntarily perform an action - moving a cursor on a computer screen - without any movement of the body, and thus without somatosensory feedback. Real-time visual feedback was available to subjects during training, but not during the experiment where the true final position of the cursor was only revealed after the subject had estimated where s/he thought it had ended up after 6s of BCI-based cursor control. During the first half of the experiment subjects based their assessments primarily on the prior probability of the end position of the cursor on previous trials. However, during the second half of the experiment subjects' judgements moved significantly closer to the true end position of the cursor, and away from the prior. This suggests that subjects can monitor task performance when the task is performed without overt movement of the body. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Interface Realisms

DEFF Research Database (Denmark)

Pold, Søren

2005-01-01

This article argues for seeing the interface as an important representational and aesthetic form with implications for postmodern culture and digital aesthetics. The interface emphasizes realism due in part to the desire for transparency in Human-Computer Interaction (HCI) and partly...

Glove-Enabled Computer Operations (GECO): Design and Testing of an Extravehicular Activity Glove Adapted for Human-Computer Interface

Science.gov (United States)

Adams, Richard J.; Olowin, Aaron; Krepkovich, Eileen; Hannaford, Blake; Lindsay, Jack I. C.; Homer, Peter; Patrie, James T.; Sands, O. Scott

2013-01-01

The Glove-Enabled Computer Operations (GECO) system enables an extravehicular activity (EVA) glove to be dual-purposed as a human-computer interface device. This paper describes the design and human participant testing of a right-handed GECO glove in a pressurized glove box. As part of an investigation into the usability of the GECO system for EVA data entry, twenty participants were asked to complete activities including (1) a Simon Says Games in which they attempted to duplicate random sequences of targeted finger strikes and (2) a Text Entry activity in which they used the GECO glove to enter target phrases in two different virtual keyboard modes. In a within-subjects design, both activities were performed both with and without vibrotactile feedback. Participants mean accuracies in correctly generating finger strikes with the pressurized glove were surprisingly high, both with and without the benefit of tactile feedback. Five of the subjects achieved mean accuracies exceeding 99 in both conditions. In Text Entry, tactile feedback provided a statistically significant performance benefit, quantified by characters entered per minute, as well as reduction in error rate. Secondary analyses of responses to a NASA Task Loader Index (TLX) subjective workload assessments reveal a benefit for tactile feedback in GECO glove use for data entry. This first-ever investigation of employment of a pressurized EVA glove for human-computer interface opens up a wide range of future applications, including text chat communications, manipulation of procedureschecklists, cataloguingannotating images, scientific note taking, human-robot interaction, and control of suit andor other EVA systems.

Non-target adjacent stimuli classification improves performance of classical ERP-based brain computer interface

Science.gov (United States)

Ceballos, G. A.; Hernández, L. F.

2015-04-01

Objective. The classical ERP-based speller, or P300 Speller, is one of the most commonly used paradigms in the field of Brain Computer Interfaces (BCI). Several alterations to the visual stimuli presentation system have been developed to avoid unfavorable effects elicited by adjacent stimuli. However, there has been little, if any, regard to useful information contained in responses to adjacent stimuli about spatial location of target symbols. This paper aims to demonstrate that combining the classification of non-target adjacent stimuli with standard classification (target versus non-target) significantly improves classical ERP-based speller efficiency. Approach. Four SWLDA classifiers were trained and combined with the standard classifier: the lower row, upper row, right column and left column classifiers. This new feature extraction procedure and the classification method were carried out on three open databases: the UAM P300 database (Universidad Autonoma Metropolitana, Mexico), BCI competition II (dataset IIb) and BCI competition III (dataset II). Main results. The inclusion of the classification of non-target adjacent stimuli improves target classification in the classical row/column paradigm. A gain in mean single trial classification of 9.6% and an overall improvement of 25% in simulated spelling speed was achieved. Significance. We have provided further evidence that the ERPs produced by adjacent stimuli present discriminable features, which could provide additional information about the spatial location of intended symbols. This work promotes the searching of information on the peripheral stimulation responses to improve the performance of emerging visual ERP-based spellers.

Classification of functional near-infrared spectroscopy signals corresponding to the right- and left-wrist motor imagery for development of a brain-computer interface.

Science.gov (United States)

Naseer, Noman; Hong, Keum-Shik

2013-10-11

This paper presents a study on functional near-infrared spectroscopy (fNIRS) indicating that the hemodynamic responses of the right- and left-wrist motor imageries have distinct patterns that can be classified using a linear classifier for the purpose of developing a brain-computer interface (BCI). Ten healthy participants were instructed to imagine kinesthetically the right- or left-wrist flexion indicated on a computer screen. Signals from the right and left primary motor cortices were acquired simultaneously using a multi-channel continuous-wave fNIRS system. Using two distinct features (the mean and the slope of change in the oxygenated hemoglobin concentration), the linear discriminant analysis classifier was used to classify the right- and left-wrist motor imageries resulting in average classification accuracies of 73.35% and 83.0%, respectively, during the 10s task period. Moreover, when the analysis time was confined to the 2-7s span within the overall 10s task period, the average classification accuracies were improved to 77.56% and 87.28%, respectively. These results demonstrate the feasibility of an fNIRS-based BCI and the enhanced performance of the classifier by removing the initial 2s span and/or the time span after the peak value. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

Science.gov (United States)

Fiorini, Rodolfo A.; Dacquino, Gianfranco

2005-03-01

GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous

Adaptation in P300 braincomputer interfaces: A two-classifier cotraining approach

DEFF Research Database (Denmark)

Panicker, Rajesh C.; Sun, Ying; Puthusserypady, Sadasivan

2010-01-01

A cotraining-based approach is introduced for constructing high-performance classifiers for P300-based braincomputer interfaces (BCIs), which were trained from very little data. It uses two classifiers: Fishers linear discriminant analysis and Bayesian linear discriminant analysis progressively...

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

Interface or Interlace?

DEFF Research Database (Denmark)

Hansen, Lone Koefoed; Wamberg, Jacob

2005-01-01

Departing from an analysis of the computer's indeterminate location between medium and machine, this paper problematises the idea of a clear-cut interface in complex computing, especially Augmented Reality. The idea and pratice of the interface is derived from the medium as a representational...... surface and thus demands the overview of an autonomous consciouness. Instead we introduce the term interlace, a mingling of representational and physical levels, thus describing the computer's ambiguous blending of imaginary and real. The proposition is demonstrated through analysis of different recent...

Communication: A method to compute the transport coefficient of pure fluids diffusing through planar interfaces from equilibrium molecular dynamics simulations.

Science.gov (United States)

Vermorel, Romain; Oulebsir, Fouad; Galliero, Guillaume

2017-09-14

The computation of diffusion coefficients in molecular systems ranks among the most useful applications of equilibrium molecular dynamics simulations. However, when dealing with the problem of fluid diffusion through vanishingly thin interfaces, classical techniques are not applicable. This is because the volume of space in which molecules diffuse is ill-defined. In such conditions, non-equilibrium techniques allow for the computation of transport coefficients per unit interface width, but their weak point lies in their inability to isolate the contribution of the different physical mechanisms prone to impact the flux of permeating molecules. In this work, we propose a simple and accurate method to compute the diffusional transport coefficient of a pure fluid through a planar interface from equilibrium molecular dynamics simulations, in the form of a diffusion coefficient per unit interface width. In order to demonstrate its validity and accuracy, we apply our method to the case study of a dilute gas diffusing through a smoothly repulsive single-layer porous solid. We believe this complementary technique can benefit to the interpretation of the results obtained on single-layer membranes by means of complex non-equilibrium methods.

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...

A Computational Discriminability Analysis on Twin Fingerprints

Science.gov (United States)

Liu, Yu; Srihari, Sargur N.

Sharing similar genetic traits makes the investigation of twins an important study in forensics and biometrics. Fingerprints are one of the most commonly found types of forensic evidence. The similarity between twins’ prints is critical establish to the reliability of fingerprint identification. We present a quantitative analysis of the discriminability of twin fingerprints on a new data set (227 pairs of identical twins and fraternal twins) recently collected from a twin population using both level 1 and level 2 features. Although the patterns of minutiae among twins are more similar than in the general population, the similarity of fingerprints of twins is significantly different from that between genuine prints of the same finger. Twins fingerprints are discriminable with a 1.5%~1.7% higher EER than non-twins. And identical twins can be distinguished by examine fingerprint with a slightly higher error rate than fraternal twins.

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

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

Touch in Computer-Mediated Environments: An Analysis of Online Shoppers' Touch-Interface User Experiences

Science.gov (United States)

Chung, Sorim

2016-01-01

Over the past few years, one of the most fundamental changes in current computer-mediated environments has been input devices, moving from mouse devices to touch interfaces. However, most studies of online retailing have not considered device environments as retail cues that could influence users' shopping behavior. In this research, I examine the…

Monitoring of facial stress during space flight: Optical computer recognition combining discriminative and generative methods

Science.gov (United States)

Dinges, David F.; Venkataraman, Sundara; McGlinchey, Eleanor L.; Metaxas, Dimitris N.

2007-02-01

Astronauts are required to perform mission-critical tasks at a high level of functional capability throughout spaceflight. Stressors can compromise their ability to do so, making early objective detection of neurobehavioral problems in spaceflight a priority. Computer optical approaches offer a completely unobtrusive way to detect distress during critical operations in space flight. A methodology was developed and a study completed to determine whether optical computer recognition algorithms could be used to discriminate facial expressions during stress induced by performance demands. Stress recognition from a facial image sequence is a subject that has not received much attention although it is an important problem for many applications beyond space flight (security, human-computer interaction, etc.). This paper proposes a comprehensive method to detect stress from facial image sequences by using a model-based tracker. The image sequences were captured as subjects underwent a battery of psychological tests under high- and low-stress conditions. A cue integration-based tracking system accurately captured the rigid and non-rigid parameters of different parts of the face (eyebrows, lips). The labeled sequences were used to train the recognition system, which consisted of generative (hidden Markov model) and discriminative (support vector machine) parts that yield results superior to using either approach individually. The current optical algorithm methods performed at a 68% accuracy rate in an experimental study of 60 healthy adults undergoing periods of high-stress versus low-stress performance demands. Accuracy and practical feasibility of the technique is being improved further with automatic multi-resolution selection for the discretization of the mask, and automated face detection and mask initialization algorithms.

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 ...

Optimal design methods for a digital human-computer interface based on human reliability in a nuclear power plant

International Nuclear Information System (INIS)

Jiang, Jianjun; Zhang, Li; Xie, Tian; Wu, Daqing; Li, Min; Wang, Yiqun; Peng, Yuyuan; Peng, Jie; Zhang, Mengjia; Li, Peiyao; Ma, Congmin; Wu, Xing

2017-01-01

Highlights: • A complete optimization process is established for digital human-computer interfaces of Npps. • A quick convergence search method is proposed. • The authors propose an affinity error probability mapping function to test human reliability. - Abstract: This is the second in a series of papers describing the optimal design method for a digital human-computer interface of nuclear power plant (Npp) from three different points based on human reliability. The purpose of this series is to explore different optimization methods from varying perspectives. This present paper mainly discusses the optimal design method for quantity of components of the same factor. In monitoring process, quantity of components has brought heavy burden to operators, thus, human errors are easily triggered. To solve the problem, the authors propose an optimization process, a quick convergence search method and an affinity error probability mapping function. Two balanceable parameter values of the affinity error probability function are obtained by experiments. The experimental results show that the affinity error probability mapping function about human-computer interface has very good sensitivity and stability, and that quick convergence search method for fuzzy segments divided by component quantity has better performance than general algorithm.

Developing Human-Computer Interface Models and Representation Techniques(Dialogue Management as an Integral Part of Software Engineering)

OpenAIRE

Hartson, H. Rex; Hix, Deborah; Kraly, Thomas M.

1987-01-01

The Dialogue Management Project at Virginia Tech is studying the poorly understood problem of human-computer dialogue development. This problem often leads to low usability in human-computer dialogues. The Dialogue Management Project approaches solutions to low usability in interfaces by addressing human-computer dialogue development as an integral and equal part of the total system development process. This project consists of two rather distinct, but dependent, parts. One is development of ...

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 on Track to Home.

Science.gov (United States)

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.

A high-speed, multi-input serial-interfacing system for a computer with simultaneous back-up recording on magnetic tape

International Nuclear Information System (INIS)

Andeweg, A.H.

1983-01-01

A system has been developed that interfaces nuclear-instrument data modules and a multichannel analyser into a computer. The interface converts 4-bit binary-coded decimal (BCD) data into 8-bit packed BCD data, and converts the parallel data into serial data. The data are transmitted up to a distance of 500m at a transfer rate of 153,6kbaud via an RS422 transmission link to a central computer system. One or more multichannel analyser systems can be connected to the system via a routine device. The routing device serves these analysers on a first-come-first-served mode. The data transmitted to the computer system are recorded simultaneously on a digital magnetic-tape drive to provide a back-up facility

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...

Multi parametric card to personal computers interface based in ispLSI1016 circuits

International Nuclear Information System (INIS)

Osorio Deliz, J.F.; Toledo Acosta, R.B.; Arista Romeu, E.

1997-01-01

It is described the design and principal characteristic of the interface circuit for a 16 bit multi parametric add on card for IBM or compatible microcomputer which content two communication channels of direct memory access and bidirectional between the card and the computer, an interrupt controller, a programmable address register, a default add res register of the card, a four channels multiplexer, as well as the decoder logic of the 80C186 and computer. The circuit was designed with two programmable logic devices ispL1016, which allowed drastically to diminish the quantity of utilized components and get a more flexible design in less time better characteristics

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...

General description of discriminating quantum operations

International Nuclear Information System (INIS)

Zhang Ke-Jia; Gao Fei; Qin Su-Juan; Wen Qiao-Yan; Zhu Ping; Guo Fen-Zhuo

2011-01-01

The discrimination of quantum operations plays a key role in quantum information and computation. Unlike discriminating quantum states, it has some special properties which can be carried out in practice. In this paper, we provide a general description of discriminating quantum operations. Concretely speaking, we describe the distinguishability between quantum operations using a measure called operator fidelity. It is shown that, employing the theory of operator fidelity, we can not only verify some previous results to discriminate unitary operations, but also exhibit a more general discrimination condition. We further apply our results to analysing the security of some quantum cryptographic protocols and discuss the realization of our method using well-developed quantum algorithms. (general)

Effect of police mobile computer terminal interface design on officer driving distraction.

Science.gov (United States)

Zahabi, Maryam; Kaber, David

2018-02-01

Several crash reports have identified in-vehicle distraction to be a primary cause of emergency vehicle crashes especially in law enforcement. Furthermore, studies have found that mobile computer terminals (MCTs) are the most frequently used in-vehicle technology for police officers. Twenty police officers participated in a driving simulator-based assessment of visual behavior, performance, workload and situation awareness with current and enhanced MCT interface designs. In general, results revealed MCT use while driving to decrease officer visual attention to the roadway, but usability improvements can reduce the level of visual distraction and secondary-task completion time. Results also suggest that use of MCTs while driving significantly reduces perceived level of driving environment awareness for police officers and increases cognitive workload. These findings may be useful for MCT manufacturers in improving interface designs to increase police officer and civilian safety. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational and experimental analyses of the wave propagation through a bar structure including liquid-solid interface

Energy Technology Data Exchange (ETDEWEB)

Park, Sang Jin [UST Graduate School, Daejeon (Korea, Republic of); Rhee, Hui Nam [Division of Mechanical and Aerospace Engineering, Sunchon National University, Sunchon (Korea, Republic of); Yoon, Doo Byung; Park, Jin Ho [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-08-15

In this research, we study the propagation of longitudinal and transverse waves through a metal rod including a liquid layer using computational and experimental analyses. The propagation characteristics of longitudinal and transverse waves obtained by the computational and experimental analyses were consistent with the wave propagation theory for both cases, that is, the homogeneous metal rod and the metal rod including a liquid layer. The fluid-structure interaction modeling technique developed for the computational wave propagation analysis in this research can be applied to the more complex structures including solid-liquid interfaces.

Subject-based feature extraction by using fisher WPD-CSP in brain-computer interfaces.

Science.gov (United States)

Yang, Banghua; Li, Huarong; Wang, Qian; Zhang, Yunyuan

2016-06-01

Feature extraction of electroencephalogram (EEG) plays a vital role in brain-computer interfaces (BCIs). In recent years, common spatial pattern (CSP) has been proven to be an effective feature extraction method. However, the traditional CSP has disadvantages of requiring a lot of input channels and the lack of frequency information. In order to remedy the defects of CSP, wavelet packet decomposition (WPD) and CSP are combined to extract effective features. But WPD-CSP method considers less about extracting specific features that are fitted for the specific subject. So a subject-based feature extraction method using fisher WPD-CSP is proposed in this paper. The idea of proposed method is to adapt fisher WPD-CSP to each subject separately. It mainly includes the following six steps: (1) original EEG signals from all channels are decomposed into a series of sub-bands using WPD; (2) average power values of obtained sub-bands are computed; (3) the specified sub-bands with larger values of fisher distance according to average power are selected for that particular subject; (4) each selected sub-band is reconstructed to be regarded as a new EEG channel; (5) all new EEG channels are used as input of the CSP and a six-dimensional feature vector is obtained by the CSP. The subject-based feature extraction model is so formed; (6) the probabilistic neural network (PNN) is used as the classifier and the classification accuracy is obtained. Data from six subjects are processed by the subject-based fisher WPD-CSP, the non-subject-based fisher WPD-CSP and WPD-CSP, respectively. Compared with non-subject-based fisher WPD-CSP and WPD-CSP, the results show that the proposed method yields better performance (sensitivity: 88.7±0.9%, and specificity: 91±1%) and the classification accuracy from subject-based fisher WPD-CSP is increased by 6-12% and 14%, respectively. The proposed subject-based fisher WPD-CSP method can not only remedy disadvantages of CSP by WPD but also discriminate

Computational design of selective peptides to discriminate between similar PDZ domains in an oncogenic pathway.

Science.gov (United States)

Zheng, Fan; Jewell, Heather; Fitzpatrick, Jeremy; Zhang, Jian; Mierke, Dale F; Grigoryan, Gevorg

2015-01-30

Reagents that target protein-protein interactions to rewire signaling are of great relevance in biological research. Computational protein design may offer a means of creating such reagents on demand, but methods for encoding targeting selectivity are sorely needed. This is especially challenging when targeting interactions with ubiquitous recognition modules--for example, PDZ domains, which bind C-terminal sequences of partner proteins. Here we consider the problem of designing selective PDZ inhibitor peptides in the context of an oncogenic signaling pathway, in which two PDZ domains (NHERF-2 PDZ2-N2P2 and MAGI-3 PDZ6-M3P6) compete for a receptor C-terminus to differentially modulate oncogenic activities. Because N2P2 has been shown to increase tumorigenicity and M3P6 to decreases it, we sought to design peptides that inhibit N2P2 without affecting M3P6. We developed a structure-based computational design framework that models peptide flexibility in binding yet is efficient enough to rapidly analyze tradeoffs between affinity and selectivity. Designed peptides showed low-micromolar inhibition constants for N2P2 and no detectable M3P6 binding. Peptides designed for reverse discrimination bound M3P6 tighter than N2P2, further testing our technology. Experimental and computational analysis of selectivity determinants revealed significant indirect energetic coupling in the binding site. Successful discrimination between N2P2 and M3P6, despite their overlapping binding preferences, is highly encouraging for computational approaches to selective PDZ targeting, especially because design relied on a homology model of M3P6. Still, we demonstrate specific deficiencies of structural modeling that must be addressed to enable truly robust design. The presented framework is general and can be applied in many scenarios to engineer selective targeting. Copyright © 2014 Elsevier Ltd. All rights reserved.

Inkjet color-printer control interface

Science.gov (United States)

Kistler, R.; Kriegler, F. J.; Marshall, R. E.

1977-01-01

Special purpose interface permits computer-driven control of inkjet printers. Inkjet printers are answer to problem of high-speed peripheral output devices for computer systems. Control interface was developed to provide high-resolution color-classification maps quickly and economically from multispectral data.

[The P300-based brain-computer interface: presentation of the complex "flash + movement" stimuli].

Science.gov (United States)

Ganin, I P; Kaplan, A Ia

2014-01-01

The P300 based brain-computer interface requires the detection of P300 wave of brain event-related potentials. Most of its users learn the BCI control in several minutes and after the short classifier training they can type a text on the computer screen or assemble an image of separate fragments in simple BCI-based video games. Nevertheless, insufficient attractiveness for users and conservative stimuli organization in this BCI may restrict its integration into real information processes control. At the same time initial movement of object (motion-onset stimuli) may be an independent factor that induces P300 wave. In current work we checked the hypothesis that complex "flash + movement" stimuli together with drastic and compact stimuli organization on the computer screen may be much more attractive for user while operating in P300 BCI. In 20 subjects research we showed the effectiveness of our interface. Both accuracy and P300 amplitude were higher for flashing stimuli and complex "flash + movement" stimuli compared to motion-onset stimuli. N200 amplitude was maximal for flashing stimuli, while for "flash + movement" stimuli and motion-onset stimuli it was only a half of it. Similar BCI with complex stimuli may be embedded into compact control systems requiring high level of user attention under impact of negative external effects obstructing the BCI control.

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...

A computer interface for processing multi-parameter data of multiple event types

International Nuclear Information System (INIS)

Katayama, I.; Ogata, H.

1980-01-01

A logic circuit called a 'Raw Data Processor (RDP)' which functions as an interface between ADCs and the PDP-11 computer has been developed at RCNP, Osaka University for general use. It enables data processing simultaneously for numbers of events of various types up to 16, and an arbitrary combination of ADCs of any number up to 14 can be assigned to each event type by means of a pinboard matrix. The details of the RDP and its application are described. (orig.)

Interface control scheme for computer high-speed interface unit

Science.gov (United States)

Ballard, B. K.

1975-01-01

Control scheme is general and performs for multiplexed and dedicated channels as well as for data-bus interfaces. Control comprises two 64-pin, dual in-line packages, each of which holds custom large-scale integrated array built with silicon-on-sapphire complementary metal-oxide semiconductor technology.

EEG Negativity in Fixations Used for Gaze-Based Control: Toward Converting Intentions into Actions with an Eye-Brain-Computer Interface

Science.gov (United States)

Shishkin, Sergei L.; Nuzhdin, Yuri O.; Svirin, Evgeny P.; Trofimov, Alexander G.; Fedorova, Anastasia A.; Kozyrskiy, Bogdan L.; Velichkovsky, Boris M.

2016-01-01

We usually look at an object when we are going to manipulate it. Thus, eye tracking can be used to communicate intended actions. An effective human-machine interface, however, should be able to differentiate intentional and spontaneous eye movements. We report an electroencephalogram (EEG) marker that differentiates gaze fixations used for control from spontaneous fixations involved in visual exploration. Eight healthy participants played a game with their eye movements only. Their gaze-synchronized EEG data (fixation-related potentials, FRPs) were collected during game's control-on and control-off conditions. A slow negative wave with a maximum in the parietooccipital region was present in each participant's averaged FRPs in the control-on conditions and was absent or had much lower amplitude in the control-off condition. This wave was similar but not identical to stimulus-preceding negativity, a slow negative wave that can be observed during feedback expectation. Classification of intentional vs. spontaneous fixations was based on amplitude features from 13 EEG channels using 300 ms length segments free from electrooculogram contamination (200–500 ms relative to the fixation onset). For the first fixations in the fixation triplets required to make moves in the game, classified against control-off data, a committee of greedy classifiers provided 0.90 ± 0.07 specificity and 0.38 ± 0.14 sensitivity. Similar (slightly lower) results were obtained for the shrinkage Linear Discriminate Analysis (LDA) classifier. The second and third fixations in the triplets were classified at lower rate. We expect that, with improved feature sets and classifiers, a hybrid dwell-based Eye-Brain-Computer Interface (EBCI) can be built using the FRP difference between the intended and spontaneous fixations. If this direction of BCI development will be successful, such a multimodal interface may improve the fluency of interaction and can possibly become the basis for a new input device

Sources of EEG activity most relevant to performance of brain-computer interface based on motor imagery

Czech Academy of Sciences Publication Activity Database

Frolov, A.; Húsek, Dušan; Bobrov, P.; Korshakov, A.V.; Chernikova, L.; Konovalov, R.; Mokienko, O.

2012-01-01

Roč. 22, č. 1 (2012), s. 21-37 ISSN 1210-0552 R&D Projects: GA ČR GAP202/10/0262 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070 Program:ED Institutional research plan: CEZ:AV0Z10300504 Keywords : brain-computer interface * independent component analysis * pattern classification * motor imagery * inverse problem * fMRI * EEG Subject RIV: IN - Informatics, Computer Science Impact factor: 0.362, year: 2012

An efficient rhythmic component expression and weighting synthesis strategy for classifying motor imagery EEG in a brain computer interface

Science.gov (United States)

Wang, Tao; He, Bin

2004-03-01

The recognition of mental states during motor imagery tasks is crucial for EEG-based brain computer interface research. We have developed a new algorithm by means of frequency decomposition and weighting synthesis strategy for recognizing imagined right- and left-hand movements. A frequency range from 5 to 25 Hz was divided into 20 band bins for each trial, and the corresponding envelopes of filtered EEG signals for each trial were extracted as a measure of instantaneous power at each frequency band. The dimensionality of the feature space was reduced from 200 (corresponding to 2 s) to 3 by down-sampling of envelopes of the feature signals, and subsequently applying principal component analysis. The linear discriminate analysis algorithm was then used to classify the features, due to its generalization capability. Each frequency band bin was weighted by a function determined according to the classification accuracy during the training process. The present classification algorithm was applied to a dataset of nine human subjects, and achieved a success rate of classification of 90% in training and 77% in testing. The present promising results suggest that the present classification algorithm can be used in initiating a general-purpose mental state recognition based on motor imagery tasks.

Exploring combinations of auditory and visual stimuli for gaze-independent brain-computer interfaces.

Directory of Open Access Journals (Sweden)

Xingwei An

Full Text Available For Brain-Computer Interface (BCI systems that are designed for users with severe impairments of the oculomotor system, an appropriate mode of presenting stimuli to the user is crucial. To investigate whether multi-sensory integration can be exploited in the gaze-independent event-related potentials (ERP speller and to enhance BCI performance, we designed a visual-auditory speller. We investigate the possibility to enhance stimulus presentation by combining visual and auditory stimuli within gaze-independent spellers. In this study with N = 15 healthy users, two different ways of combining the two sensory modalities are proposed: simultaneous redundant streams (Combined-Speller and interleaved independent streams (Parallel-Speller. Unimodal stimuli were applied as control conditions. The workload, ERP components, classification accuracy and resulting spelling speed were analyzed for each condition. The Combined-speller showed a lower workload than uni-modal paradigms, without the sacrifice of spelling performance. Besides, shorter latencies, lower amplitudes, as well as a shift of the temporal and spatial distribution of discriminative information were observed for Combined-speller. These results are important and are inspirations for future studies to search the reason for these differences. For the more innovative and demanding Parallel-Speller, where the auditory and visual domains are independent from each other, a proof of concept was obtained: fifteen users could spell online with a mean accuracy of 87.7% (chance level <3% showing a competitive average speed of 1.65 symbols per minute. The fact that it requires only one selection period per symbol makes it a good candidate for a fast communication channel. It brings a new insight into the true multisensory stimuli paradigms. Novel approaches for combining two sensory modalities were designed here, which are valuable for the development of ERP-based BCI paradigms.

A proposed parameterization of interface discontinuity factors depending on neighborhood for pin-by-pin diffusion computations for LWR

International Nuclear Information System (INIS)

Herrero, Jose Javier; Garcia-Herranz, Nuria; Ahnert, Carol

2011-01-01

There exists an interest in performing full core pin-by-pin computations for present nuclear reactors. In such type of problems the use of a transport approximation like the diffusion equation requires the introduction of correction parameters. Interface discontinuity factors can improve the diffusion solution to nearly reproduce a transport solution. Nevertheless, calculating accurate pin-by-pin IDF requires the knowledge of the heterogeneous neutron flux distribution, which depends on the boundary conditions of the pin-cell as well as the local variables along the nuclear reactor operation. As a consequence, it is impractical to compute them for each possible configuration. An alternative to generate accurate pin-by-pin interface discontinuity factors is to calculate reference values using zero-net-current boundary conditions and to synthesize afterwards their dependencies on the main neighborhood variables. In such way the factors can be accurately computed during fine-mesh diffusion calculations by correcting the reference values as a function of the actual environment of the pin-cell in the core. In this paper we propose a parameterization of the pin-by-pin interface discontinuity factors allowing the implementation of a cross sections library able to treat the neighborhood effect. First results are presented for typical PWR configurations. (author)

A proposed parameterization of interface discontinuity factors depending on neighborhood for pin-by-pin diffusion computations for LWR

Energy Technology Data Exchange (ETDEWEB)

Herrero, Jose Javier; Garcia-Herranz, Nuria; Ahnert, Carol, E-mail: herrero@din.upm.es, E-mail: nuria@din.upm.es, E-mail: carol@din.upm.es [Departamento de Ingenieria Nuclear, Universidad Politecnica de Madrid (Spain)

2011-07-01

There exists an interest in performing full core pin-by-pin computations for present nuclear reactors. In such type of problems the use of a transport approximation like the diffusion equation requires the introduction of correction parameters. Interface discontinuity factors can improve the diffusion solution to nearly reproduce a transport solution. Nevertheless, calculating accurate pin-by-pin IDF requires the knowledge of the heterogeneous neutron flux distribution, which depends on the boundary conditions of the pin-cell as well as the local variables along the nuclear reactor operation. As a consequence, it is impractical to compute them for each possible configuration. An alternative to generate accurate pin-by-pin interface discontinuity factors is to calculate reference values using zero-net-current boundary conditions and to synthesize afterwards their dependencies on the main neighborhood variables. In such way the factors can be accurately computed during fine-mesh diffusion calculations by correcting the reference values as a function of the actual environment of the pin-cell in the core. In this paper we propose a parameterization of the pin-by-pin interface discontinuity factors allowing the implementation of a cross sections library able to treat the neighborhood effect. First results are presented for typical PWR configurations. (author)

From discrimination to internalized mental illness stigma: The mediating roles of anticipated discrimination and anticipated stigma.

Science.gov (United States)

Quinn, Diane M; Williams, Michelle K; Weisz, Bradley M

2015-06-01

Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future and how anticipation of stigma in turn predicts greater stigma internalization. Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Correlational analyses indicated that more experiences of discrimination due to one's mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Experiences of discrimination over one's lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. (c) 2015 APA, all rights reserved).

SSVEP and ANN based optimal speller design for Brain Computer Interface

Directory of Open Access Journals (Sweden)

Irshad Ahmad Ansari

2015-07-01

Full Text Available This work put forwards an optimal BCI (Brain Computer Interface speller design based on Steady State Visual Evoked Potentials (SSVEP and Artificial Neural Network (ANN in order to help the people with severe motor impairments. This work is carried out to enhance the accuracy and communication rate of  BCI system. To optimize the BCI system, the work has been divided into two steps: First, designing of an encoding technique to choose characters from the speller interface and the second is the development and implementation of feature extraction algorithm to acquire optimal features, which is used to train the BCI system for classification using neural network. Optimization of speller interface is focused on representation of character matrix and its designing parameters. Then again, a lot of deliberations made in order to optimize selection of features and user’s time window. Optimized system works nearly the same with the new user and gives character per minute (CPM of 13 ± 2 with an average accuracy of 94.5% by choosing first two harmonics of power spectral density as the feature vectors and using the 2 second time window for each selection. Optimized BCI performs better with experienced users with an average accuracy of 95.1%. Such a good accuracy has not been reported before in account of fair enough CPM.DOI: 10.15181/csat.v2i2.1059

Photonic integrated circuit as a picosecond pulse timing discriminator.

Science.gov (United States)

Lowery, Arthur James; Zhuang, Leimeng

2016-04-18

We report the first experimental demonstration of a compact on-chip optical pulse timing discriminator that is able to provide an output voltage proportional to the relative timing of two 60-ps input pulses on separate paths. The output voltage is intrinsically low-pass-filtered, so the discriminator forms an interface between high-speed optics and low-speed electronics. Potential applications include timing synchronization of multiple pulse trains as a precursor for optical time-division multiplexing, and compact rangefinders with millimeter dimensions.

Advances in Human-Computer Interaction: Graphics and Animation Components for Interface Design

Science.gov (United States)

Cipolla Ficarra, Francisco V.; Nicol, Emma; Cipolla-Ficarra, Miguel; Richardson, Lucy

We present an analysis of communicability methodology in graphics and animation components for interface design, called CAN (Communicability, Acceptability and Novelty). This methodology has been under development between 2005 and 2010, obtaining excellent results in cultural heritage, education and microcomputing contexts. In studies where there is a bi-directional interrelation between ergonomics, usability, user-centered design, software quality and the human-computer interaction. We also present the heuristic results about iconography and layout design in blogs and websites of the following countries: Spain, Italy, Portugal and France.

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

OpenAIRE

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

2011-01-01

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 in May–June 2010 in Asilomar, California. We assessed respondents’ opinions about a number of topics. First, we investigated preferences for terminology and definitions relating to BCIs. Second, w...

An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information.

Science.gov (United States)

Kumar, Shiu; Sharma, Alok; Tsunoda, Tatsuhiko

2017-12-28

Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks. CSP features are extracted from multiple overlapping sub-bands. An additional sub-band has been introduced that cover the wide frequency band (7-30 Hz) and two different types of features are extracted using CSP and common spatio-spectral pattern techniques, respectively. Mutual information is then computed from the extracted features of each of these bands and the top filter banks are selected for further processing. Linear discriminant analysis is applied to the features extracted from each of the filter banks. The scores are fused together, and classification is done using support vector machine. The proposed method is evaluated using BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, and it outperformed all other competing methods achieving the lowest misclassification rate and the highest kappa coefficient on all three datasets. Introducing a wide sub-band and using mutual information for selecting the most discriminative sub-bands, the proposed method shows improvement in motor imagery EEG signal classification.

Sequenced subjective accents for brain-computer interfaces

Science.gov (United States)

Vlek, R. J.; Schaefer, R. S.; Gielen, C. C. A. M.; Farquhar, J. D. R.; Desain, P.

2011-06-01

Subjective accenting is a cognitive process in which identical auditory pulses at an isochronous rate turn into the percept of an accenting pattern. This process can be voluntarily controlled, making it a candidate for communication from human user to machine in a brain-computer interface (BCI) system. In this study we investigated whether subjective accenting is a feasible paradigm for BCI and how its time-structured nature can be exploited for optimal decoding from non-invasive EEG data. Ten subjects perceived and imagined different metric patterns (two-, three- and four-beat) superimposed on a steady metronome. With an offline classification paradigm, we classified imagined accented from non-accented beats on a single trial (0.5 s) level with an average accuracy of 60.4% over all subjects. We show that decoding of imagined accents is also possible with a classifier trained on perception data. Cyclic patterns of accents and non-accents were successfully decoded with a sequence classification algorithm. Classification performances were compared by means of bit rate. Performance in the best scenario translates into an average bit rate of 4.4 bits min-1 over subjects, which makes subjective accenting a promising paradigm for an online auditory BCI.

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.

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...

A distributed, graphical user interface based, computer control system for atomic physics experiments.

Science.gov (United States)

Keshet, Aviv; Ketterle, Wolfgang

2013-01-01

Atomic physics experiments often require a complex sequence of precisely timed computer controlled events. This paper describes a distributed graphical user interface-based control system designed with such experiments in mind, which makes use of off-the-shelf output hardware from National Instruments. The software makes use of a client-server separation between a user interface for sequence design and a set of output hardware servers. Output hardware servers are designed to use standard National Instruments output cards, but the client-server nature should allow this to be extended to other output hardware. Output sequences running on multiple servers and output cards can be synchronized using a shared clock. By using a field programmable gate array-generated variable frequency clock, redundant buffers can be dramatically shortened, and a time resolution of 100 ns achieved over effectively arbitrary sequence lengths.

A distributed, graphical user interface based, computer control system for atomic physics experiments

Science.gov (United States)

Keshet, Aviv; Ketterle, Wolfgang

2013-01-01

Atomic physics experiments often require a complex sequence of precisely timed computer controlled events. This paper describes a distributed graphical user interface-based control system designed with such experiments in mind, which makes use of off-the-shelf output hardware from National Instruments. The software makes use of a client-server separation between a user interface for sequence design and a set of output hardware servers. Output hardware servers are designed to use standard National Instruments output cards, but the client-server nature should allow this to be extended to other output hardware. Output sequences running on multiple servers and output cards can be synchronized using a shared clock. By using a field programmable gate array-generated variable frequency clock, redundant buffers can be dramatically shortened, and a time resolution of 100 ns achieved over effectively arbitrary sequence lengths.

Acid chat: gestural interface design

OpenAIRE

Gökhan, Ali Oytun; Gokhan, Ali Oytun

2005-01-01

AcidChat is an experimental design project that aims to create an innovative computer software interface for Internet chat software using today's well known technologies; Adobe Photoshop, Macromedia Freehand and digital photography. The aim of the project is to create new understandings of interface and it's usage, by adding new conceptions to chat based interfaces which creates a totally new look at the computer software and application. One of the key features is to add a gestural approach ...

An efficient ERP-based brain-computer interface using random set presentation and face familiarity.

Directory of Open Access Journals (Sweden)

Seul-Ki Yeom

Full Text Available Event-related potential (ERP-based P300 spellers are commonly used in the field of brain-computer interfaces as an alternative channel of communication for people with severe neuro-muscular diseases. This study introduces a novel P300 based brain-computer interface (BCI stimulus paradigm using a random set presentation pattern and exploiting the effects of face familiarity. The effect of face familiarity is widely studied in the cognitive neurosciences and has recently been addressed for the purpose of BCI. In this study we compare P300-based BCI performances of a conventional row-column (RC-based paradigm with our approach that combines a random set presentation paradigm with (non- self-face stimuli. Our experimental results indicate stronger deflections of the ERPs in response to face stimuli, which are further enhanced when using the self-face images, and thereby improving P300-based spelling performance. This lead to a significant reduction of stimulus sequences required for correct character classification. These findings demonstrate a promising new approach for improving the speed and thus fluency of BCI-enhanced communication with the widely used P300-based BCI setup.

Fencing data transfers in a parallel active messaging interface of a parallel computer

Science.gov (United States)

Blocksome, Michael A.; Mamidala, Amith R.

2015-06-02

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task; the compute nodes coupled for data communications through the PAMI and through data communications resources including at least one segment of shared random access memory; including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers through a segment of shared memory; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

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.

Analysis of User Interaction with a Brain-Computer Interface Based on Steady-State Visually Evoked Potentials: Case Study of a Game.

Science.gov (United States)

Leite, Harlei Miguel de Arruda; de Carvalho, Sarah Negreiros; Costa, Thiago Bulhões da Silva; Attux, Romis; Hornung, Heiko Horst; Arantes, Dalton Soares

2018-01-01

This paper presents a systematic analysis of a game controlled by a Brain-Computer Interface (BCI) based on Steady-State Visually Evoked Potentials (SSVEP). The objective is to understand BCI systems from the Human-Computer Interface (HCI) point of view, by observing how the users interact with the game and evaluating how the interface elements influence the system performance. The interactions of 30 volunteers with our computer game, named "Get Coins," through a BCI based on SSVEP, have generated a database of brain signals and the corresponding responses to a questionnaire about various perceptual parameters, such as visual stimulation, acoustic feedback, background music, visual contrast, and visual fatigue. Each one of the volunteers played one match using the keyboard and four matches using the BCI, for comparison. In all matches using the BCI, the volunteers achieved the goals of the game. Eight of them achieved a perfect score in at least one of the four matches, showing the feasibility of the direct communication between the brain and the computer. Despite this successful experiment, adaptations and improvements should be implemented to make this innovative technology accessible to the end user.

A Development of Lightweight Grid Interface

International Nuclear Information System (INIS)

Iwai, G; Kawai, Y; Sasaki, T; Watase, Y

2011-01-01

In order to help a rapid development of Grid/Cloud aware applications, we have developed API to abstract the distributed computing infrastructures based on SAGA (A Simple API for Grid Applications). SAGA, which is standardized in the OGF (Open Grid Forum), defines API specifications to access distributed computing infrastructures, such as Grid, Cloud and local computing resources. The Universal Grid API (UGAPI), which is a set of command line interfaces (CLI) and APIs, aims to offer simpler API to combine several SAGA interfaces with richer functionalities. These CLIs of the UGAPI offer typical functionalities required by end users for job management and file access to the different distributed computing infrastructures as well as local computing resources. We have also built a web interface for the particle therapy simulation and demonstrated the large scale calculation using the different infrastructures at the same time. In this paper, we would like to present how the web interface based on UGAPI and SAGA achieve more efficient utilization of computing resources over the different infrastructures with technical details and practical experiences.

Initial constructs for patient-centered outcome measures to evaluate brain-computer interfaces.

Science.gov (United States)

Andresen, Elena M; Fried-Oken, Melanie; Peters, Betts; Patrick, Donald L

2016-10-01

The authors describe preliminary work toward the creation of patient-centered outcome (PCO) measures to evaluate brain-computer interface (BCI) as an assistive technology (AT) for individuals with severe speech and physical impairments (SSPI). In Phase 1, 591 items from 15 existing measures were mapped to the International Classification of Functioning, Disability and Health (ICF). In Phase 2, qualitative interviews were conducted with eight people with SSPI and seven caregivers. Resulting text data were coded in an iterative analysis. Most items (79%) were mapped to the ICF environmental domain; over half (53%) were mapped to more than one domain. The ICF framework was well suited for mapping items related to body functions and structures, but less so for items in other areas, including personal factors. Two constructs emerged from qualitative data: quality of life (QOL) and AT. Component domains and themes were identified for each. Preliminary constructs, domains and themes were generated for future PCO measures relevant to BCI. Existing instruments are sufficient for initial items but do not adequately match the values of people with SSPI and their caregivers. Field methods for interviewing people with SSPI were successful, and support the inclusion of these individuals in PCO research. Implications for Rehabilitation Adapted interview methods allow people with severe speech and physical impairments to participate in patient-centered outcomes research. Patient-centered outcome measures are needed to evaluate the clinical implementation of brain-computer interface as an assistive technology.

Interactive displays natural human-interface technologies

CERN Document Server

Bhowmik, Achintya K

2014-01-01

One of the first books to provide an in-depth discussion of the technologies, applications and trends in the rapidly emerging field of interactive displays (touch, gesture & voice) The book will cover the technologies, applications and trends in the field of interactive displays, namely interfaces based on touch, gesture and voice and those using a combination of these technologies. The book will be split into 4 main parts with each being dedicated to a specific user interface. Part 1 ''Touch Interfaces'' will provide a review of the currently deployed touch-screen technologies and applications. It will also cover the recent developments towards achieving thinner, lightweight and cost-reduced touch screen panels in the future via integration of touch functionalities. Part 2 ''Gesture Interfaces'' will examine techniques and applications in stereoscopic 3D computer vision, structured-light 3D computer vision and time-of-flight 3D computer vision in gesture interfaces. Part 3 ''Voice Interfaces'' will revie...

Designing end-user interfaces

CERN Document Server

Heaton, N

1988-01-01

Designing End-User Interfaces: State of the Art Report focuses on the field of human/computer interaction (HCI) that reviews the design of end-user interfaces.This compilation is divided into two parts. Part I examines specific aspects of the problem in HCI that range from basic definitions of the problem, evaluation of how to look at the problem domain, and fundamental work aimed at introducing human factors into all aspects of the design cycle. Part II consists of six main topics-definition of the problem, psychological and social factors, principles of interface design, computer intelligenc

Non-Discriminating Arguments and Their Uses

DEFF Research Database (Denmark)

Christiansen, Henning; Gallagher, John Patrick

2009-01-01

We present a technique for identifying predicate arguments that play no role in determining the control flow of a logic program with respect to goals satisfying given mode and sharing restrictions.  We call such arguments non-discriminating arguments. We show that such arguments can be detected...... by an automatic analysis. Following this, we define a transformation procedure, called discriminator slicing, that removes the non-discriminating arguments, resulting in a program whose computation trees are isomorphic to those of the original program.  Finally, we show how the results of the original program can...... be reconstructed from trace of the transformed program with the original arguments.   Thus the overall result is a two-stage execution of a program, which can be applied usefully in several contexts;  we describe a case study in optimising computations in the probabilistic logic program language PRISM, and discuss...

Molecular Computational Investigation of Electron Transfer Kinetics across Cytochrome-Iron Oxide Interfaces

International Nuclear Information System (INIS)

Kerisit, Sebastien N.; Rosso, Kevin M.; Dupuis, Michel; Valiev, Marat

2007-01-01

The interface between electron transfer proteins such as cytochromes and solid phase mineral oxides is central to the activity of dissimilatory-metal reducing bacteria. A combination of potential-based molecular dynamics simulations and ab initio electronic structure calculations are used in the framework of Marcus' electron transfer theory to compute elementary electron transfer rates from a well-defined cytochrome model, namely the small tetraheme cytochrome (STC) from Shewanella oneidensis, to surfaces of the iron oxide mineral hematite (a-Fe2O3). Room temperature molecular dynamics simulations show that an isolated STC molecule favors surface attachment via direct contact of hemes I and IV at the poles of the elongated axis, with electron transfer distances as small as 9 Angstroms. The cytochrome remains attached to the mineral surface in the presence of water and shows limited surface diffusion at the interface. Ab initio electronic coupling matrix element (VAB) calculations of configurations excised from the molecular dynamics simulations reveal VAB values ranging from 1 to 20 cm-1, consistent with nonadiabaticity. Using these results, together with experimental data on the redox potential of hematite and hemes in relevant cytochromes and calculations of the reorganization energy from cluster models, we estimate the rate of electron transfer across this model interface to range from 1 to 1000 s-1 for the most exothermic driving force considered in this work, and from 0.01 to 20 s-1 for the most endothermic. This fairly large range of electron transfer rates highlights the sensitivity of the rate upon the electronic coupling matrix element, which is in turn dependent on the fluctuations of the heme configuration at the interface. We characterize this dependence using an idealized bis-imidazole heme to compute from first principles the VAB variation due to porphyrin ring orientation, electron transfer distance, and mineral surface termination. The electronic

The mind-writing pupil : A human-computer interface based on decoding of covert attention through pupillometry

NARCIS (Netherlands)

Mathôt, Sebastiaan; Melmi, Jean Baptiste; Van Der Linden, Lotje; Van Der Stigchel, Stefan

2016-01-01

We present a new human-computer interface that is based on decoding of attention through pupillometry. Our method builds on the recent finding that covert visual attention affects the pupillary light response: Your pupil constricts when you covertly (without looking at it) attend to a bright,

Portable non-invasive brain-computer interface: challenges and opportunities of optical modalities

Science.gov (United States)

Scholl, Clara A.; Hendrickson, Scott M.; Swett, Bruce A.; Fitch, Michael J.; Walter, Erich C.; McLoughlin, Michael P.; Chevillet, Mark A.; Blodgett, David W.; Hwang, Grace M.

2017-05-01

The development of portable non-invasive brain computer interface technologies with higher spatio-temporal resolution has been motivated by the tremendous success seen with implanted devices. This talk will discuss efforts to overcome several major obstacles to viability including approaches that promise to improve spatial and temporal resolution. Optical approaches in particular will be highlighted and the potential benefits of both Blood-Oxygen Level Dependent (BOLD) and Fast Optical Signal (FOS) will be discussed. Early-stage research into the correlations between neural activity and FOS will be explored.

From Discrimination to Internalized Mental Illness Stigma: The Mediating Roles of Anticipated Discrimination and Anticipated Stigma

Science.gov (United States)

Quinn, Diane M.; Williams, Michelle K.; Weisz, Bradley M.

2015-01-01

Objective Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future, and how anticipation of stigma, in turn predicts greater stigma internalization. Method Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Results Correlational analyses indicated that more experiences of discrimination due to one’s mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Conclusion and Implications for Practice Experiences of discrimination over the lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. PMID:25844910

Adaptive learning with covariate shift-detection for motor imagery-based brain–computer interface

OpenAIRE

Raza, H; Cecotti, H; Li, Y; Prasad, G

2015-01-01

A common assumption in traditional supervised learning is the similar probability distribution of data between the training phase and the testing/operating phase. When transitioning from the training to testing phase, a shift in the probability distribution of input data is known as a covariate shift. Covariate shifts commonly arise in a wide range of real-world systems such as electroencephalogram-based brain–computer interfaces (BCIs). In such systems, there is a necessity for continuous mo...

Multiple computer-based methods of measuring joint space width can discriminate between treatment arms in the COBRA trial -- Update of an ongoing OMERACT project.

Science.gov (United States)

Sharp, John T; Angwin, Jane; Boers, Maarten; Duryea, Jeff; Finckh, Axel; Hall, James R; Kauffman, Joost A; Landewé, Robert; Langs, Georg; Lukas, Cédric; Moens, H J Bernelot; Peloschek, Philipp; Strand, C Vibeke; van der Heijde, Désirée

2009-08-01

Previously reported data on 5 computer-based programs for measurement of joint space width focusing on discriminating ability and reproducibility are updated, showing new data. Four of 5 different programs for measuring joint space width were more discriminating than observer scoring for change in narrowing in the 12 months interval. Three of 4 programs were more discriminating than observer scoring for the 0-18 month interval. The program that failed to discriminate in the 0-12 month interval was not the same program that failed in the 0-18 month interval. The committee agreed at an interim meeting in November 2007 that an important goal for computer-based measurement programs is a 90% success rate in making measurements of joint pairs in followup studies. This means that the same joint must be measured in images of both timepoints in order to assess change over time in serial radiographs. None of the programs met this 90% threshold, but 3 programs achieved 85%-90% success rate. Intraclass correlation coefficients for assessing change in joint space width in individual joints were 0.98 or 0.99 for 4 programs. The smallest detectable change was < 0.2 mm for 4 of the 5 programs, representing 29%-36% of the change within the 99th percentile of measurements.

Adaptive user interfaces

CERN Document Server

1990-01-01

This book describes techniques for designing and building adaptive user interfaces developed in the large AID project undertaken by the contributors.Key Features* Describes one of the few large-scale adaptive interface projects in the world* Outlines the principles of adaptivity in human-computer interaction

Interdisciplinary research and education at the biology-engineering-computer science interface: a perspective.

Science.gov (United States)

Tadmor, Brigitta; Tidor, Bruce

2005-09-01

Progress in the life sciences, including genome sequencing and high-throughput experimentation, offers an opportunity for understanding biology and medicine from a systems perspective. This 'new view', which complements the more traditional component-based approach, involves the integration of biological research with approaches from engineering disciplines and computer science. The result is more than a new set of technologies. Rather, it promises a fundamental reconceptualization of the life sciences based on the development of quantitative and predictive models to describe crucial processes. To achieve this change, learning communities are being formed at the interface of the life sciences, engineering and computer science. Through these communities, research and education will be integrated across disciplines and the challenges associated with multidisciplinary team-based science will be addressed.

Examining sensory ability, feature matching and assessment-based adaptation for a brain-computer interface using the steady-state visually evoked potential.

Science.gov (United States)

Brumberg, Jonathan S; Nguyen, Anh; Pitt, Kevin M; Lorenz, Sean D

2018-01-31

We investigated how overt visual attention and oculomotor control influence successful use of a visual feedback brain-computer interface (BCI) for accessing augmentative and alternative communication (AAC) devices in a heterogeneous population of individuals with profound neuromotor impairments. BCIs are often tested within a single patient population limiting generalization of results. This study focuses on examining individual sensory abilities with an eye toward possible interface adaptations to improve device performance. Five individuals with a range of neuromotor disorders participated in four-choice BCI control task involving the steady state visually evoked potential. The BCI graphical interface was designed to simulate a commercial AAC device to examine whether an integrated device could be used successfully by individuals with neuromotor impairment. All participants were able to interact with the BCI and highest performance was found for participants able to employ an overt visual attention strategy. For participants with visual deficits to due to impaired oculomotor control, effective performance increased after accounting for mismatches between the graphical layout and participant visual capabilities. As BCIs are translated from research environments to clinical applications, the assessment of BCI-related skills will help facilitate proper device selection and provide individuals who use BCI the greatest likelihood of immediate and long term communicative success. Overall, our results indicate that adaptations can be an effective strategy to reduce barriers and increase access to BCI technology. These efforts should be directed by comprehensive assessments for matching individuals to the most appropriate device to support their complex communication needs. Implications for Rehabilitation Brain computer interfaces using the steady state visually evoked potential can be integrated with an augmentative and alternative communication device to provide access

Computer simulation of biomolecule–biomaterial interactions at surfaces and interfaces

International Nuclear Information System (INIS)

Wang, Qun; Wang, Meng-hao; Lu, Xiong; Wang, Ke-feng; Zhang, Xing-dong; Liu, Yaling; Zhang, Hong-ping

2015-01-01

Biomaterial surfaces and interfaces are intrinsically complicated systems because they involve biomolecules, implanted biomaterials, and complex biological environments. It is difficult to understand the interaction mechanism between biomaterials and biomolecules through conventional experimental methods. Computer simulation is an effective way to study the interaction mechanism at the atomic and molecular levels. In this review, we summarized the recent studies on the interaction behaviors of biomolecules with three types of the most widely used biomaterials: hydroxyapatite (HA), titanium oxide (TiO 2 ), and graphene(G)/graphene oxide(GO). The effects of crystal forms, crystallographic planes, surface defects, doping atoms, and water environments on biomolecules adsorption are discussed in detail. This review provides valuable theoretical guidance for biomaterial designing and surface modification. (topical review)

Recursive N-way partial least squares for brain-computer interface.

Directory of Open Access Journals (Sweden)

Andrey Eliseyev

Full Text Available In the article tensor-input/tensor-output blockwise Recursive N-way Partial Least Squares (RNPLS regression is considered. It combines the multi-way tensors decomposition with a consecutive calculation scheme and allows blockwise treatment of tensor data arrays with huge dimensions, as well as the adaptive modeling of time-dependent processes with tensor variables. In the article the numerical study of the algorithm is undertaken. The RNPLS algorithm demonstrates fast and stable convergence of regression coefficients. Applied to Brain Computer Interface system calibration, the algorithm provides an efficient adjustment of the decoding model. Combining the online adaptation with easy interpretation of results, the method can be effectively applied in a variety of multi-modal neural activity flow modeling tasks.

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.

Development traumatic brain injury computer user interface for disaster area in Indonesia supported by emergency broadband access network.

Science.gov (United States)

Sutiono, Agung Budi; Suwa, Hirohiko; Ohta, Toshizumi; Arifin, Muh Zafrullah; Kitamura, Yohei; Yoshida, Kazunari; Merdika, Daduk; Qiantori, Andri; Iskandar

2012-12-01

Disasters bring consequences of negative impacts on the environment and human life. One of the common cause of critical condition is traumatic brain injury (TBI), namely, epidural (EDH) and subdural hematoma (SDH), due to downfall hard things during earthquake. We proposed and analyzed the user response, namely neurosurgeon, general doctor/surgeon and nurse when they interacted with TBI computer interface. The communication systems was supported by TBI web based applications using emergency broadband access network with tethered balloon and simulated in the field trial to evaluate the coverage area. The interface consisted of demography data and multi tabs for anamnesis, treatment, follow up and teleconference interfaces. The interface allows neurosurgeon, surgeon/general doctors and nurses to entry the EDH and SDH patient's data during referring them on the emergency simulation and evaluated based on time needs and their understanding. The average time needed was obtained after simulated by Lenovo T500 notebook using mouse; 8-10 min for neurosurgeons, 12-15 min for surgeons/general doctors and 15-19 min for nurses. By using Think Pad X201 Tablet, the time needed for entry data was 5-7 min for neurosurgeon, 7-10 min for surgeons/general doctors and 12-16 min for nurses. We observed that the time difference was depending on the computer type and user literacy qualification as well as their understanding on traumatic brain injury, particularly for the nurses. In conclusion, there are five data classification for simply TBI GUI, namely, 1) demography, 2) specific anamnesis for EDH and SDH, 3) treatment action and medicine of TBI, 4) follow up data display and 5) teleneurosurgery for streaming video consultation. The type of computer, particularly tablet PC was more convenient and faster for entry data, compare to that computer mouse touched pad. Emergency broadband access network using tethered balloon is possible to be employed to cover the communications systems in

Interfaces for a simple local network

International Nuclear Information System (INIS)

Nekhanevich, Eh.L.; Yasenev, M.V.

1988-01-01

A system of communication and interfaces for a simple local network of computers is described. The data on technical parameters, fields of application and operation features of the interfaces developed are presented. The data indispensable for the development of software are given. The experience in operation of the subsystem of software for remote terminal computers which makes use of the above interfaces is briefly presented. 7 refs.; 3 figs

Benchmarking Brain-Computer Interfaces Outside the Laboratory: The Cybathlon 2016

Directory of Open Access Journals (Sweden)

Domen Novak

2018-01-01

Full Text Available This paper presents a new approach to benchmarking brain-computer interfaces (BCIs outside the lab. A computer game was created that mimics a real-world application of assistive BCIs, with the main outcome metric being the time needed to complete the game. This approach was used at the Cybathlon 2016, a competition for people with disabilities who use assistive technology to achieve tasks. The paper summarizes the technical challenges of BCIs, describes the design of the benchmarking game, then describes the rules for acceptable hardware, software and inclusion of human pilots in the BCI competition at the Cybathlon. The 11 participating teams, their approaches, and their results at the Cybathlon are presented. Though the benchmarking procedure has some limitations (for instance, we were unable to identify any factors that clearly contribute to BCI performance, it can be successfully used to analyze BCI performance in realistic, less structured conditions. In the future, the parameters of the benchmarking game could be modified to better mimic different applications (e.g., the need to use some commands more frequently than others. Furthermore, the Cybathlon has the potential to showcase such devices to the general public.

Towards psychologically adaptive brain-computer interfaces

Science.gov (United States)

Myrden, A.; Chau, T.

2016-12-01

Objective. Brain-computer interface (BCI) performance is sensitive to short-term changes in psychological states such as fatigue, frustration, and attention. This paper explores the design of a BCI that can adapt to these short-term changes. Approach. Eleven able-bodied individuals participated in a study during which they used a mental task-based EEG-BCI to play a simple maze navigation game while self-reporting their perceived levels of fatigue, frustration, and attention. In an offline analysis, a regression algorithm was trained to predict changes in these states, yielding Pearson correlation coefficients in excess of 0.45 between the self-reported and predicted states. Two means of fusing the resultant mental state predictions with mental task classification were investigated. First, single-trial mental state predictions were used to predict correct classification by the BCI during each trial. Second, an adaptive BCI was designed that retrained a new classifier for each testing sample using only those training samples for which predicted mental state was similar to that predicted for the current testing sample. Main results. Mental state-based prediction of BCI reliability exceeded chance levels. The adaptive BCI exhibited significant, but practically modest, increases in classification accuracy for five of 11 participants and no significant difference for the remaining six despite a smaller average training set size. Significance. Collectively, these findings indicate that adaptation to psychological state may allow the design of more accurate BCIs.

Through the Interface - a human activity approach to user interfaces

DEFF Research Database (Denmark)

Bødker, Susanne

In providing a theoretical framework for understanding human- computer interaction as well as design of user interfaces, this book combines elements of anthropology, psychology, cognitive science, software engineering, and computer science. The framework examines the everyday work practices of us...

Neurons Forming Optic Glomeruli Compute Figure-Ground Discriminations in Drosophila

OpenAIRE

Aptekar, JW; Keles, MF; Lu, PM; Zolotova, NM; Frye, MA

2015-01-01

Many animals rely on visual figure–ground discrimination to aid in navigation, and to draw attention to salient features like conspecifics or predators. Even figures that are similar in pattern and luminance to the visual surroundings can be distinguished by the optical disparity generated by their relative motion against the ground, and yet the neural mechanisms underlying these visual discriminations are not well understood. We show in flies that a diverse array of figure–ground stimuli con...

A Review of Hybrid Brain-Computer Interface Systems

Directory of Open Access Journals (Sweden)

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.

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

NARCIS (Netherlands)

Horschig, J.M.; Oosterheert, W.; Oostenveld, R.; Jensen, O.

2015-01-01

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

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.…

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.

Vibrotactile Feedback for Brain-Computer Interface Operation

Directory of Open Access Journals (Sweden)

Febo Cincotti

2007-01-01

Full Text Available 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 (including 3 with spinal cord injury, we compared vibrotactile and visual feedback, addressing: (I the feasibility of subjects' training to master their EEG rhythms using tactile feedback; (II the compatibility of this form of feedback in presence of a visual distracter; (III the performance in presence of a complex visual task on the same (visual or different (tactile sensory channel. The stimulation protocol we developed supports a general usage of the tactors; preliminary experimentations. All studies indicated that the vibrotactile channel can function as a valuable feedback modality with reliability comparable to the classical visual feedback. Advantages of using a vibrotactile feedback emerged when the visual channel was highly loaded by a complex task. In all experiments, vibrotactile feedback felt, after some training, more natural for both controls and SCI users.

Ethical aspects of brain computer interfaces: a scoping review.

Science.gov (United States)

Burwell, Sasha; Sample, Matthew; Racine, Eric

2017-11-09

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., communication). The unprecedented direct connection created by BCI between human brains and computer hardware raises various ethical, social, and legal challenges that merit further examination and discussion. To identify and characterize the key issues associated with BCI use, we performed a scoping review of biomedical ethics literature, analyzing the ethics concerns cited across multiple disciplines, including philosophy and medicine. Based on this investigation, we report that BCI research and its potential translation to therapeutic intervention generate significant ethical, legal, and social concerns, notably with regards to personhood, stigma, autonomy, privacy, research ethics, safety, responsibility, and justice. Our review of the literature determined, furthermore, that while these issues have been enumerated extensively, few concrete recommendations have been expressed. We conclude that future research should focus on remedying a lack of practical solutions to the ethical challenges of BCI, alongside the collection of empirical data on the perspectives of the public, BCI users, and BCI researchers.

CAMAC to GPIB interface

International Nuclear Information System (INIS)

Naivar, F.J.

1978-01-01

A CAMAC module developed at the Los Alamos Scientific Laboratory allows any device conforming to the GPIB standard to be connected to a CAMAC system. This module incorporates a microprocessor to control up to 14 GPIB-compatible instruments using a restricted set of CAMAC F-N-A commands. The marriage of a device-independent bus (IEEE Standard 488-1975) to a computer-independent bus (IEEE Standard 583-1975) provides a general method for interfacing a system of programmable instruments to any computer. This module is being used to interface a variety of interactive devices on a control console to a control computer

Atomistic calculations of interface elastic properties in noncoherent metallic bilayers

International Nuclear Information System (INIS)

Mi Changwen; Jun, Sukky; Kouris, Demitris A.; Kim, Sung Youb

2008-01-01

The paper describes theoretical and computational studies associated with the interface elastic properties of noncoherent metallic bicrystals. Analytical forms of interface energy, interface stresses, and interface elastic constants are derived in terms of interatomic potential functions. Embedded-atom method potentials are then incorporated into the model to compute these excess thermodynamics variables, using energy minimization in a parallel computing environment. The proposed model is validated by calculating surface thermodynamic variables and comparing them with preexisting data. Next, the interface elastic properties of several fcc-fcc bicrystals are computed. The excess energies and stresses of interfaces are smaller than those on free surfaces of the same crystal orientations. In addition, no negative values of interface stresses are observed. Current results can be applied to various heterogeneous materials where interfaces assume a prominent role in the systems' mechanical behavior

Joint Time-Frequency-Space Classification of EEG in a Brain-Computer Interface Application

Directory of Open Access Journals (Sweden)

Molina Gary N Garcia

2003-01-01

Full Text Available Brain-computer interface is a growing field of interest in human-computer interaction with diverse applications ranging from medicine to entertainment. In this paper, we present a system which allows for classification of mental tasks based on a joint time-frequency-space decorrelation, in which mental tasks are measured via electroencephalogram (EEG signals. The efficiency of this approach was evaluated by means of real-time experimentations on two subjects performing three different mental tasks. To do so, a number of protocols for visualization, as well as training with and without feedback, were also developed. Obtained results show that it is possible to obtain good classification of simple mental tasks, in view of command and control, after a relatively small amount of training, with accuracies around 80%, and in real time.

A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential

DEFF Research Database (Denmark)

Mohebbi, Ali; Engelsholm, Signe K.D.; Puthusserypady, Sadasivan

2015-01-01

In this pilot study, a novel and minimalistic Brain Computer Interface (BCI) based wheelchair control application was developed. The system was based on pseudorandom code modulated Visual Evoked Potentials (c-VEPs). The visual stimuli in the scheme were generated based on the Gold code...

Using real-time fMRI brain-computer interfacing to treat eating disorders.

Science.gov (United States)

Sokunbi, Moses O

2018-05-15

Real-time functional magnetic resonance imaging based brain-computer interfacing (fMRI neurofeedback) has shown encouraging outcomes in the treatment of psychiatric and behavioural disorders. However, its use in the treatment of eating disorders is very limited. Here, we give a brief overview of how to design and implement fMRI neurofeedback intervention for the treatment of eating disorders, considering the basic and essential components. We also attempt to develop potential adaptations of fMRI neurofeedback intervention for the treatment of anorexia nervosa, bulimia nervosa and binge eating disorder. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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...

Touch in Computer-Mediated Environments: An Analysis of Online Shoppers’ Touch-Interface User Experiences

OpenAIRE

Chung, Sorim

2016-01-01

Over the past few years, one of the most fundamental changes in current computer-mediated environments has been input devices, moving from mouse devices to touch interfaces. However, most studies of online retailing have not considered device environments as retail cues that could influence users’ shopping behavior. In this research, I examine the underlying mechanisms between input device environments and shoppers’ decision-making processes. In particular, I investigate the impact of input d...

Microcomputer interfacing and applications

CERN Document Server

Mustafa, M A

1990-01-01

This is the applications guide to interfacing microcomputers. It offers practical non-mathematical solutions to interfacing problems in many applications including data acquisition and control. Emphasis is given to the definition of the objectives of the interface, then comparing possible solutions and producing the best interface for every situation. Dr Mustafa A Mustafa is a senior designer of control equipment and has written many technical articles and papers on the subject of computers and their application to control engineering.

Computer interfacing of the unified systems for personnel supervising in nuclear units

International Nuclear Information System (INIS)

Staicu, M.

1997-01-01

The dosimetric supervising of the personnel working in nuclear units is based on the information supplied by: 1) the dosimetric data obtained by the method of thermoluminescence; 2) the dosimetric data obtained by the method of photo dosimetry: 3) the records from medical periodic control. To create a unified system of supervising the following elements were combined: a) an Automatic System of TLD Reading and Data Processing (SACDTL). The data from this system are transmitted 'on line' to the computer; b) the measuring line of the optical density of exposed dosimetric films. The interface achieved within the general ensemble SACDTL could be adapted to this line of measurement. The transmission of the data from the measurement line to the computer is made 'on line'; c) the medical surveillance data for each person transmitted 'off line' to the database computer. The unified system resulting from the unification of the three supervising systems will achieve the following general functions: - registering of the personnel working in the nuclear field; - recording the dosimetric data; - processing and presentation of the data; - issuing of measurement bulletins. Thus, by means of unified database, dosimetric intercomparison and correlative studies can be undertaken. (author)

Gaze-and-brain-controlled interfaces for human-computer and human-robot interaction

Directory of Open Access Journals (Sweden)

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

An Architectural Experience for Interface Design

Science.gov (United States)

Gong, Susan P.

2016-01-01

The problem of human-computer interface design was brought to the foreground with the emergence of the personal computer, the increasing complexity of electronic systems, and the need to accommodate the human operator in these systems. With each new technological generation discovering the interface design problems of its own technologies, initial…

Dimensionality reduction based on distance preservation to local mean for symmetric positive definite matrices and its application in brain-computer interfaces

Science.gov (United States)

Davoudi, Alireza; Shiry Ghidary, Saeed; Sadatnejad, Khadijeh

2017-06-01

Objective. In this paper, we propose a nonlinear dimensionality reduction algorithm for the manifold of symmetric positive definite (SPD) matrices that considers the geometry of SPD matrices and provides a low-dimensional representation of the manifold with high class discrimination in a supervised or unsupervised manner. Approach. The proposed algorithm tries to preserve the local structure of the data by preserving distances to local means (DPLM) and also provides an implicit projection matrix. DPLM is linear in terms of the number of training samples. Main results. We performed several experiments on the multi-class dataset IIa from BCI competition IV and two other datasets from BCI competition III including datasets IIIa and IVa. The results show that our approach as dimensionality reduction technique—leads to superior results in comparison with other competitors in the related literature because of its robustness against outliers and the way it preserves the local geometry of the data. Significance. The experiments confirm that the combination of DPLM with filter geodesic minimum distance to mean as the classifier leads to superior performance compared with the state of the art on brain-computer interface competition IV dataset IIa. Also the statistical analysis shows that our dimensionality reduction method performs significantly better than its competitors.

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.

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.

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.

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.

A cell-phone-based brain-computer interface for communication in daily life

Science.gov (United States)

Wang, Yu-Te; Wang, Yijun; Jung, Tzyy-Ping

2011-04-01

Moving a brain-computer interface (BCI) system from a laboratory demonstration to real-life applications still poses severe challenges to the BCI community. This study aims to integrate a mobile and wireless electroencephalogram (EEG) system and a signal-processing platform based on a cell phone into a truly wearable and wireless online BCI. Its practicality and implications in a routine BCI are demonstrated through the realization and testing of a steady-state visual evoked potential (SSVEP)-based BCI. This study implemented and tested online signal processing methods in both time and frequency domains for detecting SSVEPs. The results of this study showed that the performance of the proposed cell-phone-based platform was comparable, in terms of the information transfer rate, with other BCI systems using bulky commercial EEG systems and personal computers. To the best of our knowledge, this study is the first to demonstrate a truly portable, cost-effective and miniature cell-phone-based platform for online BCIs.

Classification effects of real and imaginary movement selective attention tasks on a P300-based brain-computer interface

Science.gov (United States)

Salvaris, Mathew; Sepulveda, Francisco

2010-10-01

Brain-computer interfaces (BCIs) rely on various electroencephalography methodologies that allow the user to convey their desired control to the machine. Common approaches include the use of event-related potentials (ERPs) such as the P300 and modulation of the beta and mu rhythms. All of these methods have their benefits and drawbacks. In this paper, three different selective attention tasks were tested in conjunction with a P300-based protocol (i.e. the standard counting of target stimuli as well as the conduction of real and imaginary movements in sync with the target stimuli). The three tasks were performed by a total of 10 participants, with the majority (7 out of 10) of the participants having never before participated in imaginary movement BCI experiments. Channels and methods used were optimized for the P300 ERP and no sensory-motor rhythms were explicitly used. The classifier used was a simple Fisher's linear discriminant. Results were encouraging, showing that on average the imaginary movement achieved a P300 versus No-P300 classification accuracy of 84.53%. In comparison, mental counting, the standard selective attention task used in previous studies, achieved 78.9% and real movement 90.3%. Furthermore, multiple trial classification results were recorded and compared, with real movement reaching 99.5% accuracy after four trials (12.8 s), imaginary movement reaching 99.5% accuracy after five trials (16 s) and counting reaching 98.2% accuracy after ten trials (32 s).

Diffuse-Interface Methods in Fluid Mechanics

Science.gov (United States)

Anderson, D. M.; McFadden, G. B.; Wheeler, A. A.

1997-01-01

The authors review the development of diffuse-interface models of hydrodynamics and their application to a wide variety of interfacial phenomena. The authors discuss the issues involved in formulating diffuse-interface models for single-component and binary fluids. Recent applications and computations using these models are discussed in each case. Further, the authors address issues including sharp-interface analyses that relate these models to the classical free-boundary problem, related computational approaches to describe interfacial phenomena, and related approaches describing fully-miscible fluids.

Decoding of intended saccade direction in an oculomotor brain-computer interface

Science.gov (United States)

Jia, Nan; Brincat, Scott L.; Salazar-Gómez, Andrés F.; Panko, Mikhail; Guenther, Frank H.; Miller, Earl K.

2017-08-01

Objective. To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from the hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we aimed to demonstrate the feasibility of a BCI utilizing the oculomotor system. Approach. We developed a chronic intracortical BCI in monkeys to decode intended saccadic eye movement direction using activity from multiple frontal cortical areas. Main results. Intended saccade direction could be decoded in real time with high accuracy, particularly at contralateral locations. Accurate decoding was evident even at the beginning of the BCI session; no extensive BCI experience was necessary. High-frequency (80-500 Hz) local field potential magnitude provided the best performance, even over spiking activity, thus simplifying future BCI applications. Most of the information came from the frontal and supplementary eye fields, with relatively little contribution from dorsolateral prefrontal cortex. Significance. Our results support the feasibility of high-accuracy intracortical oculomotor BCIs that require little or no practice to operate and may be ideally suited for ‘point and click’ computer operation as used in most current AAC systems.

Virtual microscopy: merging of computer mediated communication and intuitive interfacing

Science.gov (United States)

de Ridder, Huib; de Ridder-Sluiter, Johanna G.; Kluin, Philip M.; Christiaans, Henri H. C. M.

2009-02-01

Ubiquitous computing (or Ambient Intelligence) is an upcoming technology that is usually associated with futuristic smart environments in which information is available anytime anywhere and with which humans can interact in a natural, multimodal way. However spectacular the corresponding scenarios may be, it is equally challenging to consider how this technology may enhance existing situations. This is illustrated by a case study from the Dutch medical field: central quality reviewing for pathology in child oncology. The main goal of the review is to assess the quality of the diagnosis based on patient material. The sharing of knowledge in social face-to-face interaction during such meeting is an important advantage. At the same time there is the disadvantage that the experts from the seven Dutch academic medical centers have to travel to the review meeting and that the required logistics to collect and bring patient material and data to the meeting is cumbersome and time-consuming. This paper focuses on how this time-consuming, nonefficient way of reviewing can be replaced by a virtual collaboration system by merging technology supporting Computer Mediated Collaboration and intuitive interfacing. This requires insight in the preferred way of communication and collaboration as well as knowledge about preferred interaction style with a virtual shared workspace.

Optocoupled line receiver input discriminates against narrow noise pulses

CERN Document Server

Napier, T M

1977-01-01

Describes a simple optocoupled interface which connects a data line to the receiving end of a data link that features pulse length discrimination to enhance noise pulse rejection. A rugged red LED, D /sub 1/, can bypass any reasonable fault currents to protect the relatively fragile optocoupler input diode. (0 refs).

Credit scoring analysis using kernel discriminant

Science.gov (United States)

Widiharih, T.; Mukid, M. A.; Mustafid

2018-05-01

Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

Distributed computing system with dual independent communications paths between computers and employing split tokens

Science.gov (United States)

Rasmussen, Robert D. (Inventor); Manning, Robert M. (Inventor); Lewis, Blair F. (Inventor); Bolotin, Gary S. (Inventor); Ward, Richard S. (Inventor)

1990-01-01

This is a distributed computing system providing flexible fault tolerance; ease of software design and concurrency specification; and dynamic balance of the loads. The system comprises a plurality of computers each having a first input/output interface and a second input/output interface for interfacing to communications networks each second input/output interface including a bypass for bypassing the associated computer. A global communications network interconnects the first input/output interfaces for providing each computer the ability to broadcast messages simultaneously to the remainder of the computers. A meshwork communications network interconnects the second input/output interfaces providing each computer with the ability to establish a communications link with another of the computers bypassing the remainder of computers. Each computer is controlled by a resident copy of a common operating system. Communications between respective ones of computers is by means of split tokens each having a moving first portion which is sent from computer to computer and a resident second portion which is disposed in the memory of at least one of computer and wherein the location of the second portion is part of the first portion. The split tokens represent both functions to be executed by the computers and data to be employed in the execution of the functions. The first input/output interfaces each include logic for detecting a collision between messages and for terminating the broadcasting of a message whereby collisions between messages are detected and avoided.

Programmable neural processing on a smartdust for brain-computer interfaces.

Science.gov (United States)

Yuwen Sun; Shimeng Huang; Oresko, Joseph J; Cheng, Allen C

2010-10-01

Brain-computer interfaces (BCIs) offer tremendous promise for improving the quality of life for disabled individuals. BCIs use spike sorting to identify the source of each neural firing. To date, spike sorting has been performed by either using off-chip analysis, which requires a wired connection penetrating the skull to a bulky external power/processing unit, or via custom application-specific integrated circuits that lack the programmability to perform different algorithms and upgrades. In this research, we propose and test the feasibility of performing on-chip, real-time spike sorting on a programmable smartdust, including feature extraction, classification, compression, and wireless transmission. A detailed power/performance tradeoff analysis using DVFS is presented. Our experimental results show that the execution time and power density meet the requirements to perform real-time spike sorting and wireless transmission on a single neural channel.

Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: three-class classification of rest, right-, and left-hand motor execution.

Science.gov (United States)

Trakoolwilaiwan, Thanawin; Behboodi, Bahareh; Lee, Jaeseok; Kim, Kyungsoo; Choi, Ji-Woong

2018-01-01

The aim of this work is to develop an effective brain-computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification are desired. Previous studies have mainly extracted features from the signal manually, but proper features need to be selected carefully. To avoid performance degradation caused by manual feature selection, we applied convolutional neural networks (CNNs) as the automatic feature extractor and classifier for fNIRS-based BCI. In this study, the hemodynamic responses evoked by performing rest, right-, and left-hand motor execution tasks were measured on eight healthy subjects to compare performances. Our CNN-based method provided improvements in classification accuracy over conventional methods employing the most commonly used features of mean, peak, slope, variance, kurtosis, and skewness, classified by support vector machine (SVM) and artificial neural network (ANN). Specifically, up to 6.49% and 3.33% improvement in classification accuracy was achieved by CNN compared with SVM and ANN, respectively.

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

Tactile and bone-conduction auditory brain computer interface for vision and hearing impaired users.

Science.gov (United States)

Rutkowski, Tomasz M; Mori, Hiromu

2015-04-15

The paper presents a report on the recently developed BCI alternative for users suffering from impaired vision (lack of focus or eye-movements) or from the so-called "ear-blocking-syndrome" (limited hearing). We report on our recent studies of the extents to which vibrotactile stimuli delivered to the head of a user can serve as a platform for a brain computer interface (BCI) paradigm. In the proposed tactile and bone-conduction auditory BCI novel multiple head positions are used to evoke combined somatosensory and auditory (via the bone conduction effect) P300 brain responses, in order to define a multimodal tactile and bone-conduction auditory brain computer interface (tbcaBCI). In order to further remove EEG interferences and to improve P300 response classification synchrosqueezing transform (SST) is applied. SST outperforms the classical time-frequency analysis methods of the non-linear and non-stationary signals such as EEG. The proposed method is also computationally more effective comparing to the empirical mode decomposition. The SST filtering allows for online EEG preprocessing application which is essential in the case of BCI. Experimental results with healthy BCI-naive users performing online tbcaBCI, validate the paradigm, while the feasibility of the concept is illuminated through information transfer rate case studies. We present a comparison of the proposed SST-based preprocessing method, combined with a logistic regression (LR) classifier, together with classical preprocessing and LDA-based classification BCI techniques. The proposed tbcaBCI paradigm together with data-driven preprocessing methods are a step forward in robust BCI applications research. Copyright © 2014 Elsevier B.V. All rights reserved.

XML Interfaces to the Internet of Things

NARCIS (Netherlands)

S. Pemberton (Steven); C Foster

2015-01-01

htmlabstractThe internet of things is predicated on tiny, cheap, lower power computers being embedded in devices everywhere. However such tiny devices by definition have very little memory and computing power available to support user interfaces or extended servers, and so the user interface

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.

Concept of software interface for BCI systems

Science.gov (United States)

Svejda, Jaromir; Zak, Roman; Jasek, Roman

2016-06-01

Brain Computer Interface (BCI) technology is intended to control external system by brain activity. One of main part of such system is software interface, which carries about clear communication between brain and either computer or additional devices connected to computer. This paper is organized as follows. Firstly, current knowledge about human brain is briefly summarized to points out its complexity. Secondly, there is described a concept of BCI system, which is then used to build an architecture of proposed software interface. Finally, there are mentioned disadvantages of sensing technology discovered during sensing part of our research.

Discriminative Transfer Learning for General Image Restoration

KAUST Repository

Xiao, Lei; Heide, Felix; Heidrich, Wolfgang; Schö lkopf, Bernhard; Hirsch, Michael

2018-01-01

Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

Discriminative Transfer Learning for General Image Restoration

KAUST Repository

Xiao, Lei

2018-04-30

Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

A New Human-Machine Interfaces of Computer-based Procedure System to Reduce the Team Errors in Nuclear Power Plants

International Nuclear Information System (INIS)

Kim, Sa Kil; Sim, Joo Hyun; Lee, Hyun Chul

2016-01-01

In this study, we identify the emerging types of team errors, especially, in digitalized control room of nuclear power plants such as the APR-1400 main control room of Korea. Most works in nuclear industry are to be performed by a team of more than two persons. Even though the individual errors can be detected and recovered by the qualified others and/or the well trained team, it is rather seldom that the errors by team could be easily detected and properly recovered by the team itself. Note that the team is defined as two or more people who are appropriately interacting with each other, and the team is a dependent aggregate, which accomplishes a valuable goal. Organizational errors sometimes increase the likelihood of operator errors through the active failure pathway and, at the same time, enhance the possibility of adverse outcomes through defensive weaknesses. We incorporate the crew resource management as a representative approach to deal with the team factors of the human errors. We suggest a set of crew resource management training procedures under the unsafe environments where human errors can have devastating effects. We are on the way to develop alternative interfaces against team error in a condition of using a computer-based procedure system in a digitalized main control room. The computer-based procedure system is a representative feature of digitalized control room. In this study, we will propose new interfaces of computer-based procedure system to reduce feasible team errors. We are on the way of effectiveness test to validate whether the new interface can reduce team errors during operating with a computer-based procedure system in a digitalized control room

A New Human-Machine Interfaces of Computer-based Procedure System to Reduce the Team Errors in Nuclear Power Plants

Energy Technology Data Exchange (ETDEWEB)

Kim, Sa Kil; Sim, Joo Hyun; Lee, Hyun Chul [Korea Atomic Research Institute, Daejeon (Korea, Republic of)

2016-10-15

In this study, we identify the emerging types of team errors, especially, in digitalized control room of nuclear power plants such as the APR-1400 main control room of Korea. Most works in nuclear industry are to be performed by a team of more than two persons. Even though the individual errors can be detected and recovered by the qualified others and/or the well trained team, it is rather seldom that the errors by team could be easily detected and properly recovered by the team itself. Note that the team is defined as two or more people who are appropriately interacting with each other, and the team is a dependent aggregate, which accomplishes a valuable goal. Organizational errors sometimes increase the likelihood of operator errors through the active failure pathway and, at the same time, enhance the possibility of adverse outcomes through defensive weaknesses. We incorporate the crew resource management as a representative approach to deal with the team factors of the human errors. We suggest a set of crew resource management training procedures under the unsafe environments where human errors can have devastating effects. We are on the way to develop alternative interfaces against team error in a condition of using a computer-based procedure system in a digitalized main control room. The computer-based procedure system is a representative feature of digitalized control room. In this study, we will propose new interfaces of computer-based procedure system to reduce feasible team errors. We are on the way of effectiveness test to validate whether the new interface can reduce team errors during operating with a computer-based procedure system in a digitalized control room.

WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

Directory of Open Access Journals (Sweden)

Parichit Sharma

Full Text Available The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture

WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

Science.gov (United States)

Sharma, Parichit; Mantri, Shrikant S

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design

A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update.

Science.gov (United States)

Lotte, F; Bougrain, L; Cichocki, A; Clerc, M; Congedo, M; Rakotomamonjy, A; Yger, F

2018-06-01

Most current electroencephalography (EEG)-based brain-computer interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately ten years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs. We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs. We synthesize these studies in order to present such algorithms, to report how they were used for BCIs, what were the outcomes, and to identify their pros and cons. We found that the recently designed classification algorithms for EEG-based BCIs can be divided into four main categories: adaptive classifiers, matrix and tensor classifiers, transfer learning and deep learning, plus a few other miscellaneous classifiers. Among these, adaptive classifiers were demonstrated to be generally superior to static ones, even with unsupervised adaptation. Transfer learning can also prove useful although the benefits of transfer learning remain unpredictable. Riemannian geometry-based methods have reached state-of-the-art performances on multiple BCI problems and deserve to be explored more thoroughly, along with tensor-based methods. Shrinkage linear discriminant analysis and random forests also appear particularly useful for small training samples settings. On the other hand, deep learning methods have not yet shown convincing improvement over state-of-the-art BCI methods. This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges to further advance EEG classification in BCI.

A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

Science.gov (United States)

Lotte, F.; Bougrain, L.; Cichocki, A.; Clerc, M.; Congedo, M.; Rakotomamonjy, A.; Yger, F.

2018-06-01

Objective. Most current electroencephalography (EEG)-based brain–computer interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately ten years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs. Approach. We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs. We synthesize these studies in order to present such algorithms, to report how they were used for BCIs, what were the outcomes, and to identify their pros and cons. Main results. We found that the recently designed classification algorithms for EEG-based BCIs can be divided into four main categories: adaptive classifiers, matrix and tensor classifiers, transfer learning and deep learning, plus a few other miscellaneous classifiers. Among these, adaptive classifiers were demonstrated to be generally superior to static ones, even with unsupervised adaptation. Transfer learning can also prove useful although the benefits of transfer learning remain unpredictable. Riemannian geometry-based methods have reached state-of-the-art performances on multiple BCI problems and deserve to be explored more thoroughly, along with tensor-based methods. Shrinkage linear discriminant analysis and random forests also appear particularly useful for small training samples settings. On the other hand, deep learning methods have not yet shown convincing improvement over state-of-the-art BCI methods. Significance. This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges

The use of the computer code PE2D in the electrostatic modelling of an electron beam generator vacuum diode interface

International Nuclear Information System (INIS)

Biddlecombe, C.S.; Edwards, C.B.; Shaw, M.J.

1981-10-01

The computer code PE2D has been used to optimise the design of a compact, 500kV, low inductance vacuum diode interface assembly for SPRITE, a sophisticated electron beam pumped exciplex laser system under construction at RAL. Electrostatic modelling of various dielectric interfaces has been achieved in cylindrical symmetry under conditions not amenable to more traditional methods of electrostatic field plotting. (author)

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

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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.

An online hybrid brain-computer interface combining multiple physiological signals for webpage browse.

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Long Chen; Zhongpeng Wang; Feng He; Jiajia Yang; Hongzhi Qi; Peng Zhou; Baikun Wan; Dong Ming

2015-08-01

The hybrid brain computer interface (hBCI) could provide higher information transfer rate than did the classical BCIs. It included more than one brain-computer or human-machine interact paradigms, such as the combination of the P300 and SSVEP paradigms. Research firstly constructed independent subsystems of three different paradigms and tested each of them with online experiments. Then we constructed a serial hybrid BCI system which combined these paradigms to achieve the functions of typing letters, moving and clicking cursor, and switching among them for the purpose of browsing webpages. Five subjects were involved in this study. They all successfully realized these functions in the online tests. The subjects could achieve an accuracy above 90% after training, which met the requirement in operating the system efficiently. The results demonstrated that it was an efficient system capable of robustness, which provided an approach for the clinic application.

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

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Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

2017-06-01

Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the

CAMAC serial highway interface for the LSI-11

International Nuclear Information System (INIS)

Lau, N.H.

1980-01-01

A CAMAC Serial Highway Interface has been designed for the Local Control and Instrumentation System of the Mirror Fusion Test Facility. There are over 50 distinguishable systems in the facility, each of which consists of the LSI-11 computer, fiber optic communication links, and the CAMAC system. The LSI-11 computer includes a 32k memory, serial modem interface and the CAMAC Serial Highway Interface

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

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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.

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...

Endpoint-based parallel data processing in a parallel active messaging interface of a parallel computer

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Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.

2014-08-12

Endpoint-based parallel data processing in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective operation through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.

Universal quantum interfaces

International Nuclear Information System (INIS)

Lloyd, Seth; Landahl, Andrew J.; Slotine, Jean-Jacques E.

2004-01-01

To observe or control a quantum system, one must interact with it via an interface. This article exhibits simple universal quantum interfaces--quantum input/output ports consisting of a single two-state system or quantum bit that interacts with the system to be observed or controlled. It is shown that under very general conditions the ability to observe and control the quantum bit on its own implies the ability to observe and control the system itself. The interface can also be used as a quantum communication channel, and multiple quantum systems can be connected by interfaces to become an efficient universal quantum computer. Experimental realizations are proposed, and implications for controllability, observability, and quantum information processing are explored

Combinatorial Nano-Bio Interfaces.

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Cai, Pingqiang; Zhang, Xiaoqian; Wang, Ming; Wu, Yun-Long; Chen, Xiaodong

2018-06-08

Nano-bio interfaces are emerging from the convergence of engineered nanomaterials and biological entities. Despite rapid growth, clinical translation of biomedical nanomaterials is heavily compromised by the lack of comprehensive understanding of biophysicochemical interactions at nano-bio interfaces. In the past decade, a few investigations have adopted a combinatorial approach toward decoding nano-bio interfaces. Combinatorial nano-bio interfaces comprise the design of nanocombinatorial libraries and high-throughput bioevaluation. In this Perspective, we address challenges in combinatorial nano-bio interfaces and call for multiparametric nanocombinatorics (composition, morphology, mechanics, surface chemistry), multiscale bioevaluation (biomolecules, organelles, cells, tissues/organs), and the recruitment of computational modeling and artificial intelligence. Leveraging combinatorial nano-bio interfaces will shed light on precision nanomedicine and its potential applications.

The Identification, Implementation, and Evaluation of Critical User Interface Design Features of Computer-Assisted Instruction Programs in Mathematics for Students with Learning Disabilities

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Seo, You-Jin; Woo, Honguk

2010-01-01

Critical user interface design features of computer-assisted instruction programs in mathematics for students with learning disabilities and corresponding implementation guidelines were identified in this study. Based on the identified features and guidelines, a multimedia computer-assisted instruction program, "Math Explorer", which delivers…

TCP/IP Interface for the Satellite Orbit Analysis Program (SOAP)

Science.gov (United States)

Carnright, Robert; Stodden, David; Coggi, John

2009-01-01

The Transmission Control Protocol/ Internet protocol (TCP/IP) interface for the Satellite Orbit Analysis Program (SOAP) provides the means for the software to establish real-time interfaces with other software. Such interfaces can operate between two programs, either on the same computer or on different computers joined by a network. The SOAP TCP/IP module employs a client/server interface where SOAP is the server and other applications can be clients. Real-time interfaces between software offer a number of advantages over embedding all of the common functionality within a single program. One advantage is that they allow each program to divide the computation labor between processors or computers running the separate applications. Secondly, each program can be allowed to provide its own expertise domain with other programs able to use this expertise.

To Determine the Percentage of Copper in a Brass Screw Using a Computer Interface with a Colorimeter.

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Horgan, Joan; Hedge, Robyn

1997-01-01

Year 11 students investigated the real-world problem of whether screws are really brass. It allowed them to use the colorimeter and computer interface in a way that was easily understood and models normal practice in testing laboratories. Screws were dissolved in nitric acid and their absorbance of red light was compared with a standard curve.…

Brain Computer Interface for Micro-controller Driven Robot Based on Emotiv Sensors

Directory of Open Access Journals (Sweden)

Parth Gargava

2017-08-01

Full Text Available 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 navigation of the robot. This prototype works on features learning and classification centric techniques using support vector machine. The suggested pipeline, ensures successful navigation of a robot in four directions in real time with accuracy of 93 percent.

The Rise of the Graphical User Interface.

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Edwards, Alastair D. N.

1996-01-01

Discusses the history of the graphical user interface (GUI) and the growing realization that adaptations must be made to it lest its visual nature discriminate against nonsighted or sight-impaired users. One of the most popular commercially developed adaptations is to develop sounds that signal the location of icons or menus to mouse users.…

Computational parametric study of a Richtmyer-Meshkov instability for an inclined interface.

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McFarland, Jacob A; Greenough, Jeffrey A; Ranjan, Devesh

2011-08-01

A computational study of the Richtmyer-Meshkov instability for an inclined interface is presented. The study covers experiments to be performed in the Texas A&M University inclined shock tube facility. Incident shock wave Mach numbers from 1.2 to 2.5, inclination angles from 30° to 60°, and gas pair Atwood numbers of ∼0.67 and ∼0.95 are used in this parametric study containing 15 unique combinations of these parameters. Qualitative results are examined through a time series of density plots for multiple combinations of these parameters, and the qualitative effects of each of the parameters are discussed. Pressure, density, and vorticity fields are presented in animations available online to supplement the discussion of the qualitative results. These density plots show the evolution of two main regions in the flow field: a mixing region containing driver and test gas that is dominated by large vortical structures, and a more homogeneous region of unmixed fluid which can separate away from the mixing region in some cases. The interface mixing width is determined for various combinations of the parameters listed at the beginning of the Abstract. A scaling method for the mixing width is proposed using the interface geometry and wave velocities calculated using one-dimensional gas dynamic equations. This model uses the transmitted wave velocity for the characteristic velocity and an initial offset time based on the travel time of strong reflected waves. It is compared to an adapted Richtmyer impulsive model scaling and shown to scale the initial mixing width growth rate more effectively for fixed Atwood number.

User interface issues in supporting human-computer integrated scheduling

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Cooper, Lynne P.; Biefeld, Eric W.

1991-01-01

The topics are presented in view graph form and include the following: characteristics of Operations Mission Planner (OMP) schedule domain; OMP architecture; definition of a schedule; user interface dimensions; functional distribution; types of users; interpreting user interaction; dynamic overlays; reactive scheduling; and transitioning the interface.

Brain computer interface learning for systems based on electrocorticography and intracortical microelectrode arrays.

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Hiremath, Shivayogi V; Chen, Weidong; Wang, Wei; Foldes, Stephen; Yang, Ying; Tyler-Kabara, Elizabeth C; Collinger, Jennifer L; Boninger, Michael L

2015-01-01

A brain-computer interface (BCI) system transforms neural activity into control signals for external devices in real time. A BCI user needs to learn to generate specific cortical activity patterns to control external devices effectively. We call this process BCI learning, and it often requires significant effort and time. Therefore, it is important to study this process and develop novel and efficient approaches to accelerate BCI learning. This article reviews major approaches that have been used for BCI learning, including computer-assisted learning, co-adaptive learning, operant conditioning, and sensory feedback. We focus on BCIs based on electrocorticography and intracortical microelectrode arrays for restoring motor function. This article also explores the possibility of brain modulation techniques in promoting BCI learning, such as electrical cortical stimulation, transcranial magnetic stimulation, and optogenetics. Furthermore, as proposed by recent BCI studies, we suggest that BCI learning is in many ways analogous to motor and cognitive skill learning, and therefore skill learning should be a useful metaphor to model BCI learning.

Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

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Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

2015-11-01

One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Graphical User Interface: Crisis, Danger, and Opportunity.

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Boyd, L. H.; And Others

1990-01-01

This article describes differences between the graphical user interface and traditional character-based interface systems, identifies potential problems posed by graphic computing environments for blind computer users, and describes some programs and strategies that are being developed to provide access to those environments. (Author/JDD)

[Research of controlling of smart home system based on P300 brain-computer interface].

Science.gov (United States)

Wang, Jinjia; Yang, Chengjie

2014-08-01

Using electroencephalogram (EEG) signal to control external devices has always been the research focus in the field of brain-computer interface (BCI). This is especially significant for those disabilities who have lost capacity of movements. In this paper, the P300-based BCI and the microcontroller-based wireless radio frequency (RF) technology are utilized to design a smart home control system, which can be used to control household appliances, lighting system, and security devices directly. Experiment results showed that the system was simple, reliable and easy to be populirised.

Computational analysis of acoustic transmission through periodically perforated interfaces

Directory of Open Access Journals (Sweden)

Rohan E.

2009-06-01

Full Text Available The objective of the paper is to demonstrate the homogenization approach applied to modelling the acoustic transmission on perforated interfaces embedded in the acoustic fluid. We assume a layer, with periodically perforated obstacles, separating two half-spaces filled with the fluid. The homogenization method provides limit transmission conditions which can be prescribed at the homogenized surface representing the "limit" interface. The conditions describe relationship between jump of the acoustic pressures and the transversal acoustic velocity, on introducing the "in-layer pressure" which describes wave propagation in the tangent directions with respect to the interface.This approach may serve as a relevant tool for optimal design of devices aimed at attenuation of the acoustic waves, such as the engine exhaust mufflers or other structures fitted with sieves and grillages. We present numerical examples of wave propagation in a muffler-like structure illustrating viability of the approach when complex 3D geometries of the interface perforation are considered.

Whatever works: a systematic user-centered training protocol to optimize brain-computer interfacing individually.

Directory of Open Access Journals (Sweden)

Elisabeth V C Friedrich

Full Text Available This study implemented a systematic user-centered training protocol for a 4-class brain-computer interface (BCI. The goal was to optimize the BCI individually in order to achieve high performance within few sessions for all users. Eight able-bodied volunteers, who were initially naïve to the use of a BCI, participated in 10 sessions over a period of about 5 weeks. In an initial screening session, users were asked to perform the following seven mental tasks while multi-channel EEG was recorded: mental rotation, word association, auditory imagery, mental subtraction, spatial navigation, motor imagery of the left hand and motor imagery of both feet. Out of these seven mental tasks, the best 4-class combination as well as most reactive frequency band (between 8-30 Hz was selected individually for online control. Classification was based on common spatial patterns and Fisher's linear discriminant analysis. The number and time of classifier updates varied individually. Selection speed was increased by reducing trial length. To minimize differences in brain activity between sessions with and without feedback, sham feedback was provided in the screening and calibration runs in which usually no real-time feedback is shown. Selected task combinations and frequency ranges differed between users. The tasks that were included in the 4-class combination most often were (1 motor imagery of the left hand (2, one brain-teaser task (word association or mental subtraction (3, mental rotation task and (4 one more dynamic imagery task (auditory imagery, spatial navigation, imagery of the feet. Participants achieved mean performances over sessions of 44-84% and peak performances in single-sessions of 58-93% in this user-centered 4-class BCI protocol. This protocol is highly adjustable to individual users and thus could increase the percentage of users who can gain and maintain BCI control. A high priority for future work is to examine this protocol with severely

Impact of familiarity on information complexity in human-computer interfaces

Directory of Open Access Journals (Sweden)

Bakaev Maxim

2016-01-01

Full Text Available A quantitative measure of information complexity remains very much desirable in HCI field, since it may aid in optimization of user interfaces, especially in human-computer systems for controlling complex objects. Our paper is dedicated to exploration of subjective (subject-depended aspect of the complexity, conceptualized as information familiarity. Although research of familiarity in human cognition and behaviour is done in several fields, the accepted models in HCI, such as Human Processor or Hick-Hyman’s law do not generally consider this issue. In our experimental study the subjects performed search and selection of digits and letters, whose familiarity was conceptualized as frequency of occurrence in numbers and texts. The analysis showed significant effect of information familiarity on selection time and throughput in regression models, although the R2 values were somehow low. Still, we hope that our results might aid in quantification of information complexity and its further application for optimizing interaction in human-machine systems.

P300 brain computer interface: current challenges and emerging trends

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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

COMPUTER CONTROL OF BEHAVIORAL EXPERIMENTS.

Science.gov (United States)

SIEGEL, LOUIS

THE LINC COMPUTER PROVIDES A PARTICULAR SCHEDULE OF REINFORCEMENT FOR BEHAVIORAL EXPERIMENTS BY EXECUTING A SEQUENCE OF COMPUTER OPERATIONS IN CONJUNCTION WITH A SPECIALLY DESIGNED INTERFACE. THE INTERFACE IS THE MEANS OF COMMUNICATION BETWEEN THE EXPERIMENTAL CHAMBER AND THE COMPUTER. THE PROGRAM AND INTERFACE OF AN EXPERIMENT INVOLVING A PIGEON…

Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain-computer interface

Science.gov (United States)

LaFleur, Karl; Cassady, Kaitlin; Doud, Alexander; Shades, Kaleb; Rogin, Eitan; He, Bin

2013-08-01

Objective. At the balanced intersection of human and machine adaptation is found the optimally functioning brain-computer interface (BCI). In this study, we report a novel experiment of BCI controlling a robotic quadcopter in three-dimensional (3D) physical space using noninvasive scalp electroencephalogram (EEG) in human subjects. We then quantify the performance of this system using metrics suitable for asynchronous BCI. Lastly, we examine the impact that the operation of a real world device has on subjects' control in comparison to a 2D virtual cursor task. Approach. Five human subjects were trained to modulate their sensorimotor rhythms to control an AR Drone navigating a 3D physical space. Visual feedback was provided via a forward facing camera on the hull of the drone. Main results. Individual subjects were able to accurately acquire up to 90.5% of all valid targets presented while travelling at an average straight-line speed of 0.69 m s-1. Significance. Freely exploring and interacting with the world around us is a crucial element of autonomy that is lost in the context of neurodegenerative disease. Brain-computer interfaces are systems that aim to restore or enhance a user's ability to interact with the environment via a computer and through the use of only thought. We demonstrate for the first time the ability to control a flying robot in 3D physical space using noninvasive scalp recorded EEG in humans. Our work indicates the potential of noninvasive EEG-based BCI systems for accomplish complex control in 3D physical space. The present study may serve as a framework for the investigation of multidimensional noninvasive BCI control in a physical environment using telepresence robotics.

WRAP module 1 DMS/PCS interface definition document

International Nuclear Information System (INIS)

Weidert, J.R.

1994-01-01

This document has been developed to define the computer software interfaces between Waste Receiving ampersand Processing Module 1 (WRAP 1) computer systems. The interfaces include those data interfaces which exist between the Plant Control System (PCS) and Data Management System (DMS), between the DMS and Non-Destructive Assay (NDA) equipment, and between the DMS and Boxed Waste Assay System (BWAS) equipment. In addition to the data interfaces between the various WRAP computer systems; there are also a number of control functions between WRAP 1 equipment. These control function interfaces have been specified in WRAP Construction specification 13462 and the associated equipment specifications. The PCS vendor has been listed in the equipment specifications as the responsible party for establishing the final control system interface between the PCS and Non-Destructive Examination (NDE) Equipment, the PCS and Non-Destructive Assay (NDA) Equipment, and the PCS and BWAS equipment. The primary interface requirements between these systems are addressed in Specification Sections 13462, 13532, 13533, 13026, 13537, and 13538. Additional requirements may be found in other specification sections such as the Automatic Stacker Retriever System (AS/RS) Technical Specification 14520 and the WRAP 1 Data Management System Software Requirements Specification

Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

OpenAIRE

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 spec...

An Eulerian method for computation of multimaterial impact with ENO shock-capturing and sharp interfaces

CERN Document Server

Udaykumar, H S; Belk, D M; Vanden, K J

2003-01-01

A technique is presented for the numerical simulation of high-speed multimaterial impact. Of particular interest is the interaction of solid impactors with targets. The computations are performed on a fixed Cartesian mesh by casting the equations governing material deformation in Eulerian conservation law form. The advantage of the Eulerian setting is the disconnection of the mesh from the boundary deformation allowing for large distortions of the interfaces. Eigenvalue analysis reveals that the system of equations is hyperbolic for the range of materials and impact velocities of interest. High-order accurate ENO shock-capturing schemes are used along with interface tracking techniques to evolve sharp immersed boundaries. The numerical technique is designed to tackle the following physical phenomena encountered during impact: (1) high velocities of impact leading to large deformations of the impactor as well as targets; (2) nonlinear wave-propagation and the development of shocks in the materials; (3) modelin...

An optimal range of information quantity on computer-based procedure interface design in the advanced main control room

International Nuclear Information System (INIS)

Hsieh Minchih; Chiu Mingchuan; Hwang Sheueling

2015-01-01

The quantification of information in the interface design is a critical issue. Too much information on an interface can confuse a user while executing a task, and too little information may result in poor user performance. This study focused on the quantification of visible information on computer-based procedures (CBPs). Levels of information quantity and task complexity were considered in this experiment. Simulated CBPs were developed to consist of three levels: high (at least 10 events, i.e. 3.32 bits), medium (4–8 events, i.e. 2–3 bits), and low information quantity (1 or 2 events, i.e. 0 or 1 bits). Task complexity comprised two levels: complex tasks and simple tasks. The dependent variables include operation time, secondary task performance, and mental workload. Results suggested that medium information quantity of five to eight events has a remarkable advantage in supporting operator performance under both simple and complex tasks. This research not only suggested the appropriate range of information quantity on the CBP interface, but also complemented certain deficient results of previous CBP interface design studies. Additionally, based on results obtained by this study, the quantification of information on the CBP interface should be considered to ensure safe operation of nuclear power plants. (author)

Playful Interfaces : Introduction and History

NARCIS (Netherlands)

Nijholt, Anton; Nijholt, A.

2014-01-01

In this short survey we have some historical notes about human-computer interface development with an emphasis on interface technology that has allowed us to design playful interactions with applications. The applications do not necessarily have to be entertainment applications. We can have playful

Some computer graphical user interfaces in radiation therapy.

Science.gov (United States)

Chow, James C L

2016-03-28

In this review, five graphical user interfaces (GUIs) used in radiation therapy practices and researches are introduced. They are: (1) the treatment time calculator, superficial X-ray treatment time calculator (SUPCALC) used in the superficial X-ray radiation therapy; (2) the monitor unit calculator, electron monitor unit calculator (EMUC) used in the electron radiation therapy; (3) the multileaf collimator machine file creator, sliding window intensity modulated radiotherapy (SWIMRT) used in generating fluence map for research and quality assurance in intensity modulated radiation therapy; (4) the treatment planning system, DOSCTP used in the calculation of 3D dose distribution using Monte Carlo simulation; and (5) the monitor unit calculator, photon beam monitor unit calculator (PMUC) used in photon beam radiation therapy. One common issue of these GUIs is that all user-friendly interfaces are linked to complex formulas and algorithms based on various theories, which do not have to be understood and noted by the user. In that case, user only needs to input the required information with help from graphical elements in order to produce desired results. SUPCALC is a superficial radiation treatment time calculator using the GUI technique to provide a convenient way for radiation therapist to calculate the treatment time, and keep a record for the skin cancer patient. EMUC is an electron monitor unit calculator for electron radiation therapy. Instead of doing hand calculation according to pre-determined dosimetric tables, clinical user needs only to input the required drawing of electron field in computer graphical file format, prescription dose, and beam parameters to EMUC to calculate the required monitor unit for the electron beam treatment. EMUC is based on a semi-experimental theory of sector-integration algorithm. SWIMRT is a multileaf collimator machine file creator to generate a fluence map produced by a medical linear accelerator. This machine file controls

USING OLFACTORY DISPLAYS AS A NONTRADITIONAL INTERFACE IN HUMAN COMPUTER INTERACTION

Directory of Open Access Journals (Sweden)

Alper Efe

2017-07-01

Full Text Available Smell has its limitations and disadvantages as a display medium, but it also has its strengths and many have recognized its potential. At present, in communications and virtual technologies, smell is either forgotten or improperly stimulated, because non controlled odorants present in the physical space surrounding the user. Nonetheless a controlled presentation of olfactory information can give advantages in various application fields. Therefore, two enabling technologies, electronic noses and especially olfactory displays are reviewed. Scenarios of usage are discussed together with relevant psycho-physiological issues. End-to-end systems including olfactory interfaces are quantitatively characterised under many respects. Recent works done by the authors on field are reported. The article will touch briefly on the control of scent emissions; an important factor to consider when building scented computer systems. As a sample application SUBSMELL system investigated. A look at areas of human computer interaction where olfaction output may prove useful will be presented. The article will finish with some brief conclusions and discuss some shortcomings and gaps of the topic. In particular, the addition of olfactory cues to a virtual environment increased the user's sense of presence and memory of the environment. Also, this article discusses the educational aspect of the subsmell systems.

Cybathlon experiences of the Graz BCI racing team Mirage91 in the brain-computer interface discipline.

Science.gov (United States)

Statthaler, Karina; Schwarz, Andreas; Steyrl, David; Kobler, Reinmar; Höller, Maria Katharina; Brandstetter, Julia; Hehenberger, Lea; Bigga, Marvin; Müller-Putz, Gernot

2017-12-28

In this work, we share our experiences made at the world-wide first CYBATHLON, an event organized by the Eidgenössische Technische Hochschule Zürich (ETH Zürich), which took place in Zurich in October 2016. It is a championship for severely motor impaired people using assistive prototype devices to compete against each other. Our team, the Graz BCI Racing Team MIRAGE91 from Graz University of Technology, participated in the discipline "Brain-Computer Interface Race". A brain-computer interface (BCI) is a device facilitating control of applications via the user's thoughts. Prominent applications include assistive technology such as wheelchairs, neuroprostheses or communication devices. In the CYBATHLON BCI Race, pilots compete in a BCI-controlled computer game. We report on setting up our team, the BCI customization to our pilot including long term training and the final BCI system. Furthermore, we describe CYBATHLON participation and analyze our CYBATHLON result. We found that our pilot was compliant over the whole time and that we could significantly reduce the average runtime between start and finish from initially 178 s to 143 s. After the release of the final championship specifications with shorter track length, the average runtime converged to 120 s. We successfully participated in the qualification race at CYBATHLON 2016, but performed notably worse than during training, with a runtime of 196 s. We speculate that shifts in the features, due to the nonstationarities in the electroencephalogram (EEG), but also arousal are possible reasons for the unexpected result. Potential counteracting measures are discussed. The CYBATHLON 2016 was a great opportunity for our student team. We consolidated our theoretical knowledge and turned it into practice, allowing our pilot to play a computer game. However, further research is required to make BCI technology invariant to non-task related changes of the EEG.

Discrimination strategies for inequivalent classes of multipartite entangled states

International Nuclear Information System (INIS)

Niekamp, Soenke; Kleinmann, Matthias; Guehne, Otfried

2010-01-01

How can one discriminate different inequivalent classes of multiparticle entanglement experimentally? We present an approach for the discrimination of an experimentally prepared state from the equivalence class of another state. We consider two possible measures for the discrimination strength of an observable. The first measure is based on the difference of expectation values, the second on the relative entropy of the probability distributions of the measurement outcomes. The interpretation of these measures and their usefulness for experiments with limited resources are discussed. In the case of graph states, the stabilizer formalism is employed to compute these quantities and to find sets of observables that result in the most decisive discrimination.

Feature Extraction on Brain Computer Interfaces using Discrete Dyadic Wavelet Transform: Preliminary Results

International Nuclear Information System (INIS)

Gareis, I; Gentiletti, G; Acevedo, R; Rufiner, L

2011-01-01

The purpose of this work is to evaluate different feature extraction alternatives to detect the event related evoked potential signal on brain computer interfaces, trying to minimize the time employed and the classification error, in terms of sensibility and specificity of the method, looking for alternatives to coherent averaging. In this context the results obtained performing the feature extraction using discrete dyadic wavelet transform using different mother wavelets are presented. For the classification a single layer perceptron was used. The results obtained with and without the wavelet decomposition were compared; showing an improvement on the classification rate, the specificity and the sensibility for the feature vectors obtained using some mother wavelets.

Quantitative aspects of directly coupled supercritical fluid extraction-capillary gas chromatography with a conventional split/splitless injector as interface

OpenAIRE

Lou, X.W.; Janssen, J.G.M.; Cramers, C.A.

1993-01-01

The quant. aspects of online supercrit. fluid extn.-capillary gas chromatog. (SFE-GC) with a split/splitless injector as interface were studied. Special attention was paid to the discrimination behavior and the reproducibility of the split/splitless interface. A simple exptl. set-up is proposed that allows accurate quantitation in online SFE-split GC. The results obtained in online SFE-GC compare favorably with those from conventional GC with split injection. Discrimination is absent when wor...

Pulse discrimination of scintillator detector with artificial neural network

International Nuclear Information System (INIS)

Chen Man; Cai Yuerong; Yang Chaowen

2006-01-01

The features of signal for scintillator detectors are analyzed. According to the difference in the fraction of slow and fast scintillation for different particles, three intrinsic parameters (signal amplitude, integration of signal during rinsing, integration of frequency spectrum of signals in middle frequencies) of signals are defined. The artificial neural network method for pulse discrimination of scintillator detector is studied. The signals with different shapes under real condition are simulated with computer, and discriminated by the method. Results of discrimination are gotten and discussed. (authors)

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.

Principles of Motor Recovery in Post-Stroke Patients using Hand Exoskeleton Controlled by the Brain-Computer Interface Based on Motor Imagery

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Biryukova, E. V.; Bobrov, P.; Mokienko, O.; Alexandrov, A.V.

2017-01-01

Roč. 27, č. 1 (2017), s. 107-137 ISSN 1210-0552 Grant - others:Russian Ministry of Education and Science(RU) RFMEFI60715X0128 Institutional support: RVO:67985807 Keywords : brain computer interface * motor imagery * post-stroke and post-traumatic patients * arm and hand exoskeleton * proportional derivative controller * motor synergy * clinical application Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.394, year: 2016

Task-induced frequency modulation features for brain-computer interfacing.

Science.gov (United States)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects' intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects' intents with an accuracy comparable to task-induced amplitude modulation. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Task-induced frequency modulation features for brain-computer interfacing

Science.gov (United States)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Objective. Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects’ intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects’ intents with an accuracy comparable to task-induced amplitude modulation. Approach. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. Main results. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Significance. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

A Novel Multilayer Correlation Maximization Model for Improving CCA-Based Frequency Recognition in SSVEP Brain-Computer Interface.

Science.gov (United States)

Jiao, Yong; Zhang, Yu; Wang, Yu; Wang, Bei; Jin, Jing; Wang, Xingyu

2018-05-01

Multiset canonical correlation analysis (MsetCCA) has been successfully applied to optimize the reference signals by extracting common features from multiple sets of electroencephalogram (EEG) for steady-state visual evoked potential (SSVEP) recognition in brain-computer interface application. To avoid extracting the possible noise components as common features, this study proposes a sophisticated extension of MsetCCA, called multilayer correlation maximization (MCM) model for further improving SSVEP recognition accuracy. MCM combines advantages of both CCA and MsetCCA by carrying out three layers of correlation maximization processes. The first layer is to extract the stimulus frequency-related information in using CCA between EEG samples and sine-cosine reference signals. The second layer is to learn reference signals by extracting the common features with MsetCCA. The third layer is to re-optimize the reference signals set in using CCA with sine-cosine reference signals again. Experimental study is implemented to validate effectiveness of the proposed MCM model in comparison with the standard CCA and MsetCCA algorithms. Superior performance of MCM demonstrates its promising potential for the development of an improved SSVEP-based brain-computer interface.

How discriminating are discriminative instruments?

Science.gov (United States)

Hankins, Matthew

2008-05-27

The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

How discriminating are discriminative instruments?

Directory of Open Access Journals (Sweden)

Hankins Matthew

2008-05-01

Full Text Available Abstract The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL. The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness, but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

THE USE OF A COMPLEX “BRAIN-COMPUTER INTERFACE AND EXO-SKELETON” AND MOVEMENT IMAGINATION TECHNIQUE FOR POST-STROKE REHABILITATION

Directory of Open Access Journals (Sweden)

S. V. Kotov

2015-01-01

Full Text Available Background: Efficacy of physical exercise and movement imagination for restoration of motor dysfunction after a stroke is seen as proven. However, the use of movement imagination is complicated by impossibility of objective and subjective control over  the exercise, as well as by the absence of their motor support. The brain-computer interface based on electroencephalography is a technique that enables a feedback during movement imagination.Materials and methods: We assessed 10 patients (6 men and 4 women aged from 30 to 66 years (mean age, 47 ± 7.7 years with an ischemic (n = 9 and hemorrhagic (n = 1 stroke during the last 2 months to 4 years. Online recognition of movement imagination was done by a classifier with a brain computer interface. An exo-skeleton supported passive movements in a paretic hand managed by the brain-computer interface. During 2 weeks the patients had 10 sessions of 45–90 minute duration each. For control, we used data from 5 stroke patients who, in addition to their standard treatment, underwent an imitation of rehabilitation procedures without movement imagination and feedback. To assess efficacy of treatment, we used a modified Ashworth scale, Fugl-Meyer scale, test for evaluation of hand functions ARAT, British scale for assessment of muscle force MRC-SS. Level of everyday activity and working ability was measured with a modified Rankin scale and Bartel index. Cognitive functions were assessed with Schulte tables.Results: Online recognition of movement imagination according to desynchronization of μ rhythm was registered in 50–75% of patients. All patients reported a subjective improvement of motor functions and working ability. Positive results for at least one parameter were observed in all patients; however, there were no significant difference between the parameters before and after rehabilitation procedures, excluding cognitive functions (degree of warming-up, p < 0.02.Conclusion: In post stroke patients

South African sign language human-computer interface in the context of the national accessibility portal

CSIR Research Space (South Africa)

Olivrin, GJ

2006-02-01

Full Text Available example, between a deaf person who can sign and an able person or a person with a different disability who cannot sign). METHODOLOGY A signing avatar is set up to work together with a chatterbot. The chatterbot is a natural language dialogue interface... are then offered in sign language as the replies are interpreted by a signing avatar, a living character that can reproduce human-like gestures and expressions. To make South African Sign Language (SASL) available digitally, computational models of the language...

TMS communications software. Volume 2: Bus interface unit

Science.gov (United States)

Gregor, P. J.

1979-01-01

A data bus communication system to support the space shuttle's Trend Monitoring System (TMS) and to provide a basis for evaluation of the bus concept is described. Installation of the system included developing both hardware and software interfaces between the bus and the specific TMS computers and terminals. The software written for the microprocessor-based bus interface units is described. The software implements both the general bus communications protocol and also the specific interface protocols for the TMS computers and terminals.

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 subject-independent pattern-based Brain-Computer Interface