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Comparative study of approximate entropy and sample entropy in EEG data analysis

Cao Rui, Li Li, Chen Junjie

ApEn and SampEn are widely adopted in the Biomedical Signal Processing in recent years. This paper makes a comparative study on the application of both in the analysis of EEG data. Theoretically, SampEn has higher accuracy and needs much less computation time thanApEn. Experiments based on two EEG data sets showthat SampEn can better classify different emotions and canmore accurately distinguish the alcoholismfromcontrols thanApEn. This study indicates that SampEn is more suitable to be used to analyze EEG data thanApEn, which has relatively high significance for the quantitative analysis of EEG.