EEG correlates of P300-based brain-computer interface (BCI) performance in people with amyotrophic lateral sclerosis.

TitleEEG correlates of P300-based brain-computer interface (BCI) performance in people with amyotrophic lateral sclerosis.
Publication TypeJournal Article
Year of Publication2012
AuthorsMak, JN, McFarland, DJ, Vaughan, TM, McCane, LM, Tsui, PZ, Zeitlin, DJ, Sellers, EW, Wolpaw, JR
JournalJournal of neural engineering
Volume9
Pagination026014
Date Published04/2012
ISSN1741-2552
KeywordsUser-Computer Interface
Abstract

The purpose of this study was to identify electroencephalography (EEG) features that correlate with P300-based brain-computer interface (P300 BCI) performance in people with amyotrophic lateral sclerosis (ALS). Twenty people with ALS used a P300 BCI spelling application in copy-spelling mode. Three types of EEG features were found to be good predictors of P300 BCI performance: (1) the root-mean-square amplitude and (2) the negative peak amplitude of the event-related potential to target stimuli (target ERP) at Fz, Cz, P3, Pz, and P4; and (3) EEG theta frequency (4.5-8 Hz) power at Fz, Cz, P3, Pz, P4, PO7, PO8 and Oz. A statistical prediction model that used a subset of these features accounted for >60% of the variance in copy-spelling performance (p < 0.001, mean R(2)?= 0.6175). The correlations reflected between-subject, rather than within-subject, effects. The results enhance understanding of performance differences among P300 BCI users. The predictors found in this study might help in: (1) identifying suitable candidates for long-term P300 BCI operation; (2) assessing performance online. Further work on within-subject effects needs to be done to establish whether P300 BCI user performance could be improved by optimizing one or more of these EEG features.

URLhttp://www.ncbi.nlm.nih.gov/pubmed/22350501
DOI10.1088/1741-2560/9/2/026014

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