Title |
Performance assessment in brain-computer interface-based augmentative and alternative communication
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Published in |
BioMedical Engineering OnLine, May 2013
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DOI | 10.1186/1475-925x-12-43 |
Pubmed ID | |
Authors |
David E Thompson, Stefanie Blain-Moraes, Jane E Huggins |
Abstract |
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. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 4% |
France | 1 | <1% |
Italy | 1 | <1% |
Germany | 1 | <1% |
United Kingdom | 1 | <1% |
Brazil | 1 | <1% |
Belgium | 1 | <1% |
Iran, Islamic Republic of | 1 | <1% |
Unknown | 129 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 31 | 22% |
Student > Master | 24 | 17% |
Researcher | 16 | 11% |
Student > Bachelor | 14 | 10% |
Student > Doctoral Student | 9 | 6% |
Other | 24 | 17% |
Unknown | 23 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 50 | 35% |
Computer Science | 21 | 15% |
Neuroscience | 9 | 6% |
Agricultural and Biological Sciences | 7 | 5% |
Medicine and Dentistry | 7 | 5% |
Other | 18 | 13% |
Unknown | 29 | 21% |