Treffer: User-centered design in brain―computer interfaces—A case study

Title:
User-centered design in brain―computer interfaces—A case study
Source:
Brain - computer interfacingArtificial intelligence in medicine (Print). 59(2):71-80
Publisher Information:
Amsterdam: Elsevier, 2013.
Publication Year:
2013
Physical Description:
print, 44 ref
Original Material:
INIST-CNRS
Subject Terms:
Cognition, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Systèmes informatiques et systèmes répartis. Interface utilisateur, Computer systems and distributed systems. User interface, Intelligence artificielle, Artificial intelligence, Sciences biologiques et medicales, Biological and medical sciences, Sciences biologiques fondamentales et appliquees. Psychologie, Fundamental and applied biological sciences. Psychology, Psychologie. Psychophysiologie, Psychology. Psychophysiology, Perception, Audition, Sciences medicales, Medical sciences, Techniques d'exploration et de diagnostic (generalites), Investigative techniques, diagnostic techniques (general aspects), Electrodiagnostic. Enregistrement des activités électriques, Electrodiagnosis. Electric activity recording, Système nerveux, Nervous system, Psychologie. Psychanalyse. Psychiatrie, Psychology. Psychoanalysis. Psychiatry, Accident cérébrovasculaire, Stroke, Accidente cerebrovascular, Analyse discriminante, Discriminant analysis, Análisis discriminante, Analyse donnée, Data analysis, Análisis datos, Application médicale, Medical application, Aplicación medical, Assistance utilisateur, User assistance, Asistencia usuario, Audition, Hearing, Audición, Besoin de l'utilisateur, User need, Necesidad usuario, Cerveau, Brain, Cerebro, Charge travail, Workload, Carga trabajo, Cognition, Cognición, Comportement utilisateur, User behavior, Comportamiento usuario, Etude expérimentale, Experimental study, Estudio experimental, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Interface utilisateur, User interface, Interfase usuario, Mémoire de travail, Working memory, Memoria trabajo, Mémoire à court terme, Short-term memory, Memoria a corto plazo, Potentiel évoqué cognitif, Event evoked potential, Potencial evocado cognitivo, Potentiel évoqué, Evoked potential, Potencial evocado, Préconditionnement, Preconditioning, Precondicionamiento, Théorie cognitive, Cognitive theory, Teoría cognitiva, Assistive technology, Auditory evoked potentials, Brain―computer interface, Event-related potentials, Linear discriminant analysis, Locked-in syndrome, Traumatic brain injury, User-centered design
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Machine Learning Lab, Berlin Institute of Technology, Marchsstrasse 23, 10587 Berlin, Germany
Neuroelectrical Imaging and Brain―Computer Interface Lab, Fondazione Santa Lucia, Via Ardeatina 306, 00142 Rome, Italy
Department of Psychology, University of Rome Sapienza', Via dei Marsi 78, 00183 Rome, Italy
School of Computing Science, University of Glasgow, G12 8QQ Glasgow, Scotland, United Kingdom
BrainLinks-BrainTools Excellence Cluster, University of Freiburg, Albertstrasse 23, 79104 Freiburg, Germany
ISSN:
0933-3657
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Psychology. Ethology

Scanning and diagnostic techniques (generalities)

FRANCIS
Accession Number:
edscal.27953664
Database:
PASCAL Archive

Weitere Informationen

Objective: The array of available brain―computer interface (BCI) paradigms has continued to grow, and so has the corresponding set of machine learning methods which are at the core of BCI systems. The latter have evolved to provide more robust data analysis solutions, and as a consequence the proportion of healthy BCI users who can use a BCI successfully is growing. With this development the chances have increased that the needs and abilities of specific patients, the end-users, can be covered by an existing BCI approach. However, most end-users who have experienced the use of a BCI system at all have encountered a single paradigm only. This paradigm is typically the one that is being tested in the study that the end-user happens to be enrolled in, along with other end-users. Though this corresponds to the preferred study arrangement for basic research, it does not ensure that the end-user experiences a working BCI. In this study, a different approach was taken; that of a user-centered design. It is the prevailing process in traditional assistive technology. Given an individual user with a particular clinical profile, several available BCI approaches are tested and ― if necessary ― adapted to him/her until a suitable BCI system is found. Methods: Described is the case of a 48-year-old woman who suffered from an ischemic brain stem stroke, leading to a severe motor- and communication deficit. She was enrolled in studies with two different BCI systems before a suitable system was found. The first was an auditory event-related potential (ERP) paradigm and the second a visual ERP paradigm, both of which are established in literature. Results: The auditory paradigm did not work successfully, despite favorable preconditions. The visual paradigm worked flawlessly, as found over several sessions. This discrepancy in performance can possibly be explained by the user's clinical deficit in several key neuropsychological indicators, such as attention and working memory. While the auditory paradigm relies on both categories, the visual paradigm could be used with lower cognitive workload. Besides attention and working memory, several other neurophysiological and -psychological indicators ― and the role they play in the BCIs at hand ― are discussed. Conclusion: The user's performance on the first BCI paradigm would typically have excluded her from further ERP-based BCI studies. However, this study clearly shows that, with the numerous paradigms now at our disposal, the pursuit for a functioning BCI system should not be stopped after an initial failed attempt.