A dictionary learning approach for spatio-temporal characterization of absence seizures.

Journal: Physiological measurement

Published Date: Nov 4, 2019

Abstract

OBJECTIVE: This research explores absence seizures using data recorded from different layers of somatosensory cortex of four genetic absence epilepsy rats from Strasbourg (GAERS). Localizing the active layers of somatosensory cortex (spatial analysis) and investigating the dynamics of recorded seizures (temporal analysis) are the main goals of this research.

Authors

S Akhavan

University Grenoble Alpes, Grenoble INP, CNRS, GIPSA-lab, Grenoble, France. CIPCE, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.
R Phlypo
H Soltanian-Zadeh
M Kamarei
C Jutten

Keywords

Electrophysiological Phenomena Humans Machine Learning Models, Neurological Seizures Spatio-Temporal Analysis

External Resources

View on PubMed Access via DOI PubMed (31569077)

A dictionary learning approach for spatio-temporal characterization of absence seizures.

Abstract

Authors

Keywords

External Resources

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