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Time- and frequency-resolved covariance analysis for detection and characterization of seizures from intracraneal EEG recordings
[article]
2020
arXiv
pre-print
The amount of power in different frequency bands of the electroencephalogram (EEG) carries information about the behavioral state of a subject. Hence, neurologists treating epileptic patients monitor the temporal evolution of the different bands. We propose a covariance-based method to detect and characterize epileptic seizures operating on the band-filtered EEG signal. The algorithm is unsupervised, and performs a principal component analysis of intra-cranial EEG recordings, detecting
arXiv:1902.11236v2
fatcat:2rhdcb4x2vdcnn5tmrqwqo6ibe