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Wavelet and Region-Specific EEG Signal Analysis for Studying Post-Stroke Rehabilitation

Shatakshi Singh,Bablu Tiwari,Dimple Dawar,M. Kaur,J. Pandian,Rajeshwar Sahonta,C. S. Kumar,M. Mahadevappa

Published 2021 in Annual International Conference of the IEEE Engineering in Medicine and Biology Society

ABSTRACT

Post-stroke monitoring is a crucial step for properly studying the progress of stroke patients. The rehabilitation process consists of exercise regimes that help in constantly engaging the affected part of the brain leading to faster recovery. The work here studies the effectiveness of the rehabilitation regime by investigating several parameters that can play important role in observing the immediate effect of the exercises. Various parameters from different wavelet coefficients were extracted for monitoring rehabilitation for up to 90 days. Energy and waveform length show maximum variation when monitoring pre and post-exercise changes. The parameters were correlated with clinical(FMA) score. Centroid Index gave high correlation value for beta band (r = -0.559). Alpha band on the other hand showed a good correlation with all the extracted fe atures, maximum being -0.6988 with energy. So for monitoring post-stroke rehabilitation alpha and beta bands should be focused. Region-specific analyses were also done to monitor changes in different parts of the brain.

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