Fusion of Deep Features from 2D-DOST of fNIRS Signals for Subject-Independent Classification of Motor Execution Tasks
Pouya Khani,
Vahid Solouk,
Hashem Kalbkhani
et al.
Abstract:Functional near-infrared spectroscopy (fNIRS) is a low-cost and noninvasive method to measure the hemodynamic responses of cortical brain activities and has received great attention in brain-computer interface (BCI) applications. In this paper, we present a method based on deep learning and the time-frequency map (TFM) of fNIRS signals to classify the three motor execution tasks including right-hand tapping, left-hand tapping, and foot tapping. To simultaneously obtain the TFM and consider the correlation amon… Show more
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