Functional brain network analysis of the fatigue state for coach bus driver

Traffic accident of coach bus occurred frequently in recent years. One important reason of the accident is the fatigue driving of the bus driver. Thus it is very important to monitor and research the state of the driver during the driving process, which can give an evaluation to driver´s driving condition and provide a valuable reference to the coach driving. Because there have some different features of human electroencephalogram (EEG) between the fatigue state and the natural state, we used the portable EEG acquisition device, Emotive, to get the EEG of the driver in the natural state (before driving) and the fatigue state (after driving three hours) in the real driving environment. And through the wavelet packet analysis, the EEG was decomposed to four sub frequency band: theta, alpha, beta and delta band, for each band, the nonlinear correlation of different electrode was calculated and functional brain network was constructed. Then the network was converted to binary network by choose an appropriate threshold and some network feature parameters were calculated and compared between the natural state and the fatigue state. The result shows that the differences of the functional brain network between the two states are very clear and this method can be used to monitor and evaluation the driver´s fatigue state.