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Study on Assessment Method of Mental Fatigue Based on Brain-Computer Interface

Author: WangPeng
Tutor: ChenMinYou
School: Chongqing University
Course: Electrical Engineering
Keywords: Electroencephalogram(EEG) Mental fatigue Wavelet packet Fuzzy synthetic evaluation
CLC: R318
Type: Master's thesis
Year: 2011
Downloads: 61
Quote: 0
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Abstract


Mental fatigue is, in daily life, caused by prolonged high-intensity mental or physical labor, lack of sleep, circadian rhythm disruption of biological function, and leads to temporary job barriers, operational capacity drop phenomenon. The main symptoms of mental fatigue are dazed mind, slow response, misjudgment, lack of concentration, decreased efficiency, easy to make mistakes and so on. In high-risk operations, the short-term mental fatigue resulting symptoms, such as lack of concentration, slow response, may lead to serious accidents. If somebody has mental fatigue for a long time, the physical and mental health could be affected and even lead to physical and mental diseases. Mental fatigue is the body’s protective physiological responses. The human body through proper rest and relaxation can relieve mental fatigue. Therefore, the detection and evaluation of mental fatigue is particularly important. However, there is still lack of effective and objective mental fatigue assessment methods. We try to analyze the basic rhythms changes of EEG to detect mental fatigue degree. In this paper, a detection system of mental fatigue based on LabVIEW has been developed for rapid detection of the body’s mental fatigue degree.For the sake of finding the relationships between mental fatigue and electroencephalogram(EEG) parameters, using wavelet packer analysis to extract basic rhythms from EEG and calculate the log energy entropy in different states of mental fatigue. In comparative study, it is found that the frontal pole of brain presents significant distinction of basic rhythms and log energy entropy in the states of mental fatigue. Therefore, we can regard the relative power in basic rhythms and the log energy entropy as valid indices for measuring mental fatigue. Selecting the relative power of FPz lead’s basic rhythms as indices, the fuzzy synthetic evaluation model based on the relative membership degree was used to evaluate the degree of mental fatigue. Experimental results show that the mental fatigue assessment made by the fuzzy synthetic evaluation model is consistent with the objective reality.EEG acquisition equipment NeuroScan platform supports to transmit information to other computers in real time based on TCP protocol. LabVIEW software is used to achieve real-time EEG data transmission and signal processing, and to assess the subjects’current mental fatigue degree.

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