I²RiMA achieves up to 82.78% balanced accuracy in cross-subject EEG stress detection by mapping frequency-specific covariances to the SPD tangent space, aggregating spectral clusters, and applying intra-inter temporal attention.
Stress-induced effects in resting eeg spectra predict the performance of ssvep-based bci.IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(8):1771–1780, 2020
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I\textsuperscript{2}RiMA: Spectral Riemannian Representation with Temporal Attention for Mental Stress Detection based on EEG Signals
I²RiMA achieves up to 82.78% balanced accuracy in cross-subject EEG stress detection by mapping frequency-specific covariances to the SPD tangent space, aggregating spectral clusters, and applying intra-inter temporal attention.