Detecting Microstate Transition in Human Brain via Eigenspace of Spatiotemporal Graph

In this letter, a novel approach for detecting the transition of electroencephalography (EEG) microstates of the human brain has been proposed. We have considered the EEG electrodes as nodes of a graph and the correlation between the electrodes' signals as the edge weights. Then, using spectral...

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Veröffentlicht in:	IEEE sensors letters 2023-05, Vol.7 (5), p.1-4
Hauptverfasser:	Dev, Raghav, Kumar, Sandeep, Gandhi, Tapan Kumar
Format:	Artikel
Sprache:	eng
Schlagworte:	Brain Correlation Datasets Electrodes Electroencephalography electroencepholography (EEG) microstates graph signal processing Heuristic algorithms human brain invariant spaces Laplace equations Sensor signal processing Signal processing algorithms Spatiotemporal phenomena Spectrum analysis
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