Current Trends in Hardware and Software for Brain-Computer Interfaces (BCIs).

TitleCurrent Trends in Hardware and Software for Brain-Computer Interfaces (BCIs).
Publication TypeJournal Article
Year of Publication2011
AuthorsBrunner, P, Bianchi, L, Guger, C, Cincotti, F, Schalk, G
JournalJ Neural Eng
Volume8
Issue2
Pagination025001
Date Published04/2011
ISSN1741-2552
KeywordsBiofeedback, Psychology, Brain, Brain Mapping, Electroencephalography, Equipment Design, Equipment Failure Analysis, Humans, Man-Machine Systems, Software, User-Computer Interface
Abstract 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.
URLhttp://www.ncbi.nlm.nih.gov/pubmed/21436536
DOI10.1088/1741-2560/8/2/025001
Alternate JournalJ Neural Eng
PubMed ID21436536
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