Spectral representation of EEG data using learned graphs with application to motor imagery decoding

• Published in: Biomedical signal processing and control Vol. 87; p. 105537
• Main Authors: Miri, Maliheh, Abootalebi, Vahid, Saeedi-Sourck, Hamid, Van De Ville, Dimitri, Behjat, Hamid
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2024
• Subjects: Annan data- och informationsvetenskap; Computer and Information Science; Computer and Information Sciences; Data- och informationsvetenskap (Datateknik); EEG; Fukunaga–Koontz transform; Graph learning; Graph signal processing; Motor imagery decoding; Natural Sciences; Naturvetenskap; Other Computer and Information Science; Motor imagery decoding; Graph learning; Fukunaga–Koontz transform; Graph signal processing; EEG

Electroencephalography (EEG) data entail a complex spatiotemporal structure that reflects ongoing organization of brain activity. Characterization of the spatial patterns is an indispensable step in numerous EEG processing pipelines. We present a novel method for transforming EEG data into a spectra...