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《Journal of Mianyang Teachers' College》 2017-08
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Recognition of EEG Fatigue Degree Based on Morlet Wavelet Transform

YE Chun;GAO Hao;Jiangsu Vocational College of Information and Techninology;College of Automation,Nanjing University of Posts and Telecommunications;  
In order to identify the degree of human fatigue,an EEG signal measurement method based on Morlet wavelet transform was proposed to analyze the eye movement signal of the subject,and the fatigue state was identified by the eigenvalue screening of the time domain signal to understand the fatigue of the subject degree. In this study,we used the non-invasive EEG signal measuring instrument to collect the original data of EEG signal.Morlet wavelet transform( Morlet Wavelet transform,MWT) was used to decompose the signal and then transform the data into eigenvalues,Thenthe state analysis of fatigue was carried out using Support Vector Machine( SVM)and Back Propagation Neural Network( BPNN). This method tested 400 testers at different degrees of fatigue. The results showed that the correct rate of EEG identification was 96. 15%.
【Fund】: 国家自然科学基金(61571236 61602255 61203196);; 中国博士后基金(2014M551632)资助项目;; 江苏省博士后基金(1402018A);; 江苏省省科技厅产学研资金/前瞻性联合研究项目(BY2013017);; 江苏高校品牌专业建设工程资助项目(PPZY2015C239)
【CateGory Index】: R318;TN911.7
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