A comprehensive survey of brain interface technology designs

Mason, SG; Bashashati, A; Fatourechi, M; Navarro, KF; Birch, GE

A comprehensive survey of brain interface technology designs

Mason, SG Bashashati, A Fatourechi, M Navarro, KF Birch, GE

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Publication Type:: Journal Article
Citation:: Annals of Biomedical Engineering, 2007, 35 (2), pp. 137 - 169
Issue Date:: 2007-02-01

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Field	Value	Language
dc.contributor.author	Mason, SG	en_US
dc.contributor.author	Bashashati, A	en_US
dc.contributor.author	Fatourechi, M	en_US
dc.contributor.author	Navarro, KF	en_US
dc.contributor.author	Birch, GE	en_US
dc.date.available	2006-07-28	en_US
dc.date.issued	2007-02-01	en_US
dc.identifier.citation	Annals of Biomedical Engineering, 2007, 35 (2), pp. 137 - 169	en_US
dc.identifier.issn	0090-6964	en_US
dc.identifier.uri	http://hdl.handle.net/10453/4221
dc.description.abstract	In this work we present the first comprehensive survey of Brain Interface (BI) technology designs published prior to January 2006. Detailed results from this survey, which was based on the Brain Interface Design Framework proposed by Mason and Birch, are presented and discussed to address the following research questions: (1) which BI technologies are directly comparable, (2) what technology designs exist, (3) which application areas (users, activities and environments) have been targeted in these designs, (4) which design approaches have received little or no research and are possible opportunities for new technology, and (5) how well are designs reported. The results of this work demonstrate that meta-analysis of high-level BI design attributes is possible and informative. The survey also produced a valuable, historical cross-reference where BI technology designers can identify what types of technology have been proposed and by whom. © 2006 Biomedical Engineering Society.	en_US
dc.relation.ispartof	Annals of Biomedical Engineering	en_US
dc.relation.isbasedon	10.1007/s10439-006-9170-0	en_US
dc.subject.classification	Biomedical Engineering	en_US
dc.subject.mesh	Brain	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Electroencephalography	en_US
dc.subject.mesh	Equipment Design	en_US
dc.subject.mesh	Equipment Failure Analysis	en_US
dc.subject.mesh	Biotechnology	en_US
dc.subject.mesh	Evoked Potentials	en_US
dc.subject.mesh	Signal Processing, Computer-Assisted	en_US
dc.subject.mesh	Software	en_US
dc.subject.mesh	Software Design	en_US
dc.subject.mesh	User-Computer Interface	en_US
dc.subject.mesh	Technology Assessment, Biomedical	en_US
dc.title	A comprehensive survey of brain interface technology designs	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	35	en_US
utslib.for	0903 Biomedical Engineering	en_US
utslib.for	09 Engineering	en_US
utslib.for	11 Medical and Health Sciences	en_US
dc.location.activity	ISI:000243471200001	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	35	en_US

Abstract:

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

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http://hdl.handle.net/10453/4221