Study on Physiological Mental Fatigue with Nonlinear Dynamics

Abstract

Mental fatigue states in different experiments and in different conditions were studied with nonlinear dynamics. EEG signals registered from Fp1 and Fp2 under different mental fatigue states were recorded and analyzed using Kolmogorov entropy (KE) and Kolmogorov complexity (KC) to investigate whether mental fatigue could be assessed using this measures. It was shown the value of KE or KC is strongly correlative with the mental fatigue state: the value of mean Kolmogorov entropy (KE) corresponding to a special mental state fluctuates within the special range; the values of KE decrease with working times prolonging; the values of KC decrease with mental fatigue increasing. It may be possible to differentiate different mental fatigue level according to the value of KE or KC. This method may be useful in further research and efforts to evaluate mental fatigue level objectively. It may also provide a basis for the study of effects of mental fatigue on central neural system.