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Performance assessment in brain-computer interface-based augmentative and alternative communication

dc.contributor.authorThompson, David E
dc.contributor.authorBlain-Moraes, Stefanie
dc.contributor.authorHuggins, Jane E
dc.date.accessioned2015-10-18T18:01:17Z
dc.date.available2015-10-18T18:01:17Z
dc.date.issued2013-05-16
dc.identifier.citationBioMedical Engineering OnLine. 2013 May 16;12(1):43
dc.identifier.urihttps://hdl.handle.net/2027.42/115465en_US
dc.description.abstractAbstract A large number of incommensurable metrics are currently used to report the performance of brain-computer interfaces (BCI) used for augmentative and alterative communication (AAC). The lack of standard metrics precludes the comparison of different BCI-based AAC systems, hindering rapid growth and development of this technology. This paper presents a review of the metrics that have been used to report performance of BCIs used for AAC from January 2005 to January 2012. We distinguish between Level 1 metrics used to report performance at the output of the BCI Control Module, which translates brain signals into logical control output, and Level 2 metrics at the Selection Enhancement Module, which translates logical control to semantic control. We recommend that: (1) the commensurate metrics Mutual Information or Information Transfer Rate (ITR) be used to report Level 1 BCI performance, as these metrics represent information throughput, which is of interest in BCIs for AAC; 2) the BCI-Utility metric be used to report Level 2 BCI performance, as it is capable of handling all current methods of improving BCI performance; (3) these metrics should be supplemented by information specific to each unique BCI configuration; and (4) studies involving Selection Enhancement Modules should report performance at both Level 1 and Level 2 in the BCI system. Following these recommendations will enable efficient comparison between both BCI Control and Selection Enhancement Modules, accelerating research and development of BCI-based AAC systems.
dc.titlePerformance assessment in brain-computer interface-based augmentative and alternative communication
dc.typeArticleen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/115465/1/12938_2012_Article_658.pdf
dc.identifier.doi10.1186/1475-925X-12-43en_US
dc.language.rfc3066en
dc.rights.holderThompson et al.; licensee BioMed Central Ltd.
dc.date.updated2015-10-18T18:01:19Z
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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