alexa A P300-based brain-computer interface: initial tests by ALS patients.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Health & Medical Informatics

Author(s): Sellers EW, Donchin E, Sellers EW, Donchin E, Sellers EW, Donchin E, Sellers EW, Donchin E

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Abstract OBJECTIVE: The current study evaluates the effectiveness of a brain-computer interface (BCI) system that operates by detecting a P300 elicited by one of four randomly presented stimuli (i.e. YES, NO, PASS, END). METHODS: Two groups of participants were tested. The first group included three amyotrophic lateral sclerosis (ALS) patients that varied in degree of disability, but all retained the ability to communicate; the second group included three non-ALS controls. Each participant participated in ten experimental sessions during a period of approximately 6 weeks. During each run the participant's task was to attend to one stimulus and disregard the other three. Stimuli were presented auditorily, visually, or in both modes. RESULTS: Two of the 3 ALS patient's classification rates were equal to those achieved by the non-ALS participants. Waveform morphology varied as a function of the presentation mode, but not in a similar pattern for each participant. CONCLUSIONS: The event-related potentials elicited by the target stimuli could be discriminated from the non-target stimuli for the non-ALS and the ALS groups. Future studies will begin to examine online classification. SIGNIFICANCE: The results of offline classification suggest that a P300-based BCI can serve as a non-muscular communication device in both ALS, and non-ALS control groups. This article was published in Clin Neurophysiol and referenced in Journal of Health & Medical Informatics

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