Online classification of imagined speech using functional near-infrared spectroscopy signals
Alborz Rezazadeh Sereshkeh, Rozhin Yousefi, Andrew T Wong, Tom Chau

TL;DR
This study introduces an online fNIRS-based BCI that enables users to answer yes/no questions by imagining speech, achieving high accuracy and demonstrating the potential for more intuitive communication interfaces.
Contribution
First online fNIRS 3-class imagined speech BCI that allows direct yes/no responses, showing promising accuracy and neural activation patterns.
Findings
9 out of 12 participants performed above chance
Average online 3-class accuracy was 64.1%
Channels in left temporal cortex provided most discriminative info
Abstract
Most brain-computer interfaces (BCIs) based on functional near-infrared spectroscopy (fNIRS) require that users perform mental tasks such as motor imagery, mental arithmetic, or music imagery to convey a message or to answer simple yes or no questions. These cognitive tasks usually have no direct association with the communicative intent, which makes them difficult for users to perform. In this paper, a 3-class intuitive BCI is presented which enables users to directly answer yes or no questions by covertly rehearsing the word 'yes' or 'no' for 15 s. The BCI also admits an equivalent duration of unconstrained rest which constitutes the third discernable task. Twelve participants each completed one offline block and six online blocks over the course of 2 sessions. The mean value of the change in oxygenated hemoglobin concentration during a trial was calculated for each channel and used…
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