Analysis of Kolmogorov Complexity in Spontaneous EEG Signal and It's Application to Assessment of Mental Fatigue

Abstract

In this paper, an attempt was made to evaluate mental fatigue using Kolmogorov complexity analysis of spontaneous EEG. EEG signals registered from Fp1 and Fp2 under different mental fatigue states were recorded and analyzed using Kolmogorov complexity (KC) to investigate whether mental fatigue could be assessed using this measure. The result indicates that the value of KC is strongly correlative with the mental fatigue state and the values of KC decrease with mental fatigue increasing. It may be possible to differentiate different mental fatigue level according to the value of 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.