Characterization of cerebral infarction in multiple channel EEG recordings based on quantifications of time-frequency representation

Authors:
Li Zhang;Chuanhong He;Wei He
Affiliations:
State Key Laboratory of Power Transmission Equipment & System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing, China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing, China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing, China
Venue:
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Year:
2010

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Abstract

In this paper, a method for characterizing cerebral infarction (CI) utilizing spontaneous electroencephalogram (EEG) is described. We obtained the time-frequency representations (TFRs) of EEG signals recorded from both normal subjects and CI patients. The corresponding characteristics were depicted by relative frequency band energy (RFBE) and Shannon entropy (SE) of TFR. Comparing with the normal subjects, the CI patients had some changes in EEG as follows: (1) delta and theta rhythms were attenuated while beta and gamma rhythms were enhanced, and the changes of delta and beta were more significant, (2) alpha was also blocked with eyes open, however the blocking action was less evident, (3) SE increase was pronounced. Consequently, the quantitative EEG methods are promising tools to provide helpful and sensitive information for the detection and diagnose of CI.