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Multiscale permutation entropy analysis of electroencephalogram

Yao Wen-Po Liu Tie-Bing Dai Jia-Fei Wang Jun

Multiscale permutation entropy analysis of electroencephalogram

Yao Wen-Po, Liu Tie-Bing, Dai Jia-Fei, Wang Jun
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  • Received Date:  08 October 2013
  • Accepted Date:  21 December 2013
  • Published Online:  05 April 2014

Multiscale permutation entropy analysis of electroencephalogram

  • 1. Nanjing General Hospital of Nanjing Military Command, Nanjing 210002, China;
  • 2. Image Processing and Image Communications Key Lab., Nanjing Univ. of Posts & Telecomm., Nanjing 210003, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant Nos. 61271082, 61201029, 61102094), and the Natural Science Foundation of Jiangsu Province, China (Grant Nos. BK2011759, BK2011565).

Abstract: We carried out a detailed analysis and a comparison between normal and epileptic electroencephalogram (EEG) based on multiscale permutation entropy. The relationship between multiscale permutation entropy values of EEG and age, and the effect of scale factor on multiscale permutation entropy value were also discussed. By analyzing normal and epileptic EEG based on multiscale permutation entropy, we found that, at the same age, multiscale permutation entropy value of the normal group’s EEG is higher than that of the epileptic group by an average of 0.19, about 7.9%. In addition, for people of age 3 to 35, their multiscale permutation entropies are clearly maximum. When scale factor is smaller than 15, the value of their entropy would reduce no matter whether the age increases or decreases. The results indicate that multiscale permutation entropy can distinguish between normal and epileptic EEG and reflect the general process of human brain development.

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