Recurrence Quantification Analysis of EEGs for Mental Fatigue Evaluation
It is important to evaluate the level of mental fatigue by using electroencephalograms (EEGs). In this research, a recurrence quantification analysis (RQA) is proposed to reveal dynamical characteristics in EEGs of subjects suffering from mental fatigue. In contrast with traditional spectrum methods, the merits of RQA method is that it can measure the complexity of non-stationary and noisy signal without any assumptions such as linear, stationary and noiseless. In this study, eight channels of EEGs were collected in calculation-rest-calculation experiment. Both RQA measure i.e. determinism (％DET) and spectrum estimator i.e. central frequency (CenF) was computed. The test results show that ％DET is sensitive to mental load and mental fatigue while CenF fails to track the change of mental fatigue. Particularly, ％DET clearly reflects the rest effect in sustained mental work. Therefore, RQA could be a promising approach in evaluation and treatment for mental fatigue.
Recurrence Quantification Analysis (RQA) EEGs Mental Fatigue Spectrum Estimation
CHEN Lanlan ZOU Junzhong ZHANG Jian
Department of Automation, School of Information Science and Engineering,East China University of Science and Technology, Shanghai, 200237, China
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
3824-3827
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）