Blind testing of quasi brain deaths based on analysis of EEG energy

Authors:
Wei Zhou;Gang Liu;Qiwei Shi;Shilei Cui;Yina Zhou;Huili Zhu;Rubin Wang;Jianting Cao
Affiliations:
Saitama Institute of Technology, Fukaya-shi, Saitama, Japan;Saitama Institute of Technology, Fukaya-shi, Saitama, Japan;Saitama Institute of Technology, Fukaya-shi, Saitama, Japan;Huadong Hospital Affiliated, Fudan University, Shanghai, China;Huadong Hospital Affiliated, Fudan University, Shanghai, China;Huadong Hospital Affiliated, Fudan University, Shanghai, China;East China University of Science and Technology, Shanghai, China;Saitama Institute of Technology, Fukaya-shi, Saitama, Japan
Venue:
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Year:
2011

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Abstract

This paper presents a power spectral pattern analysis method for quasi-brain-death EEG based on Empirical Mode Decomposition (EMD) under the condition of unknowing the clinical symptoms of patients. EMD method is a time-frequency analysis method for analyzing the nonlinear and non-stationary data. In this paper,we decompose a single-channel recorded EEG data into a number of components with different frequencies, we calculate the power spectral or energy of the decomposed components in a suitable frequency band. Based on the EEG power spectral analysis, the patients are classified into two categories: existence of the brain activities or absence of the brain activities. The experimental results illustrate the effectiveness of our proposed method.