A practical, intuitive brain-computer interface for communicating 'yes' or 'no' by listening.
OBJECTIVE
Previous work has shown that it is possible to build an EEG-based binary brain-computer interface system (BCI) driven purely by shifts of attention to auditory stimuli. However, previous studies used abrupt, abstract stimuli that are often perceived as harsh and unpleasant, and whose lack of inherent meaning may make the interface unintuitive and difficult for beginners. We aimed to establish whether we could transition to a system based on more natural, intuitive stimuli (spoken words 'yes' and 'no') without loss of performance, and whether the system could be used by people in the locked-in state.


METHODS
We performed a counterbalanced, interleaved within-subject comparison between an auditory streaming BCI that used beep stimuli, and one that used word stimuli. Fourteen healthy volunteers performed two sessions each, on separate days. We also collected preliminary data from two subjects with advanced amyotrophic lateral sclerosis (ALS), who used the word-based system to answer a set of simple yes-no questions.


RESULTS
The N1, N2 and P3 event-related potentials elicited by words varied more between subjects than those elicited by beeps. However, the difference between responses to attended and unattended stimuli was more consistent with words than beeps. Healthy subjects' performance with word stimuli (mean 77% ± 3.3 s.e.) was slightly but not significantly better than their performance with beep stimuli (mean 73% ± 2.8 s.e.). The two subjects with ALS used the word-based BCI to answer questions with a level of accuracy similar to that of the healthy subjects.


CONCLUSIONS
Since performance using word stimuli was at least as good as performance using beeps, we recommend that auditory streaming BCI systems be built with word stimuli to make the system more pleasant and intuitive. Our preliminary data show that word-based streaming BCI is a promising tool for communication by people who are locked in.
Wadsworth Center, New York State Department of Health , Albany, NY, USA. Helen Hayes Hospital, West Haverstraw, NY, USA.
N Jeremy
NJ
Hill
Erin
E
Ricci
Sameah
S
Haider
Lynn M
LM
McCane
Susan
S
Heckman
Jonathan R
JR
Wolpaw
Theresa M
TM
Vaughan
D000328:Adult; D000368:Aged; D000465:Algorithms; D001307:Auditory Perception; D062207:Brain-Computer Interfaces; D003143:Communication Devices for People with Disabilities; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005260:Female; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D008875:Middle Aged; D011782:Quadriplegia / Q000503:physiopathology* / Q000534:rehabilitation*; D016896:Treatment Outcome; D014584:User-Computer Interface