Research on mental fatigue detection based on portable EEG acquisition equipment

Using multi-channel EEG acquisition equipment for mental fatigue detection has several limitations to its application. Therefore, this paper will explore single-channel EEG signals based on portable EEG acquisition equipment to detect mental fatigue. In addition, improved single sub-band reconstruction of wavelet packet algorithm is proposed to eliminate frequency aliasing. This aliasing phenomenon occurs in the EEG signals analysis process when using the fast wavelet packet algorithm. Two feature parameters, 8 energy ratios of the EEG four rhythms and the variance of various sub-bands wavelet packet coefficients, are extracted. The experimental results show that 5 of the energy ratios and the variance of 3 sub-bands wavelet packet coefficients have significant differences between the awake and mental fatigue states and, therefore, taking these features as mental fatigue evaluation indices is feasible. In conclusion, using portable EEG acquisition equipment to conduct mental fatigue detection is a portable and effective method which is both practical and convenient.