brain-computer interface

Reaction Time Predicts Brain-Computer Interface Aptitude

Reaction Time Predicts Brain-Computer Interface Aptitude
Author(s)3: Sam Darvishi, Alireza Gharabaghi, Michael C. Ridding, Derek Abbott, Mathias Baumert
Reaction Time Predicts Brain-Computer Interface Aptitude 780 600 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

     There is evidence that 15–30% of the general population cannot effectively operate brain–computer interfaces (BCIs). Thus the BCI performance predictors are critically required to pre-screen participants. Current neurophysiological and…

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A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification

A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification
Author(s)3: Hamza Baali, Aida Khorshidtalab, Mostefa Mesbah, Momoh J. E. Salami
A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification 780 436 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain–computer interface (BCI). This method uses a signal-dependent orthogonal transform, referred to as…

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