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

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 dev...

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Detalles Bibliográficos
Autores principales: Thompson, David E, Blain-Moraes, Stefanie, Huggins, Jane E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3662584/
https://www.ncbi.nlm.nih.gov/pubmed/23680020
http://dx.doi.org/10.1186/1475-925X-12-43
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author Thompson, David E
Blain-Moraes, Stefanie
Huggins, Jane E
author_facet Thompson, David E
Blain-Moraes, Stefanie
Huggins, Jane E
author_sort Thompson, David E
collection PubMed
description 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.
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spelling pubmed-36625842013-06-05 Performance assessment in brain-computer interface-based augmentative and alternative communication Thompson, David E Blain-Moraes, Stefanie Huggins, Jane E Biomed Eng Online Review 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. BioMed Central 2013-05-16 /pmc/articles/PMC3662584/ /pubmed/23680020 http://dx.doi.org/10.1186/1475-925X-12-43 Text en Copyright © 2013 Thompson et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Thompson, David E
Blain-Moraes, Stefanie
Huggins, Jane E
Performance assessment in brain-computer interface-based augmentative and alternative communication
title Performance assessment in brain-computer interface-based augmentative and alternative communication
title_full Performance assessment in brain-computer interface-based augmentative and alternative communication
title_fullStr Performance assessment in brain-computer interface-based augmentative and alternative communication
title_full_unstemmed Performance assessment in brain-computer interface-based augmentative and alternative communication
title_short Performance assessment in brain-computer interface-based augmentative and alternative communication
title_sort performance assessment in brain-computer interface-based augmentative and alternative communication
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3662584/
https://www.ncbi.nlm.nih.gov/pubmed/23680020
http://dx.doi.org/10.1186/1475-925X-12-43
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