Int J Neural Syst - Real-time EEG-based detection of fatigue driving danger for accident prediction.

Tópicos

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Resumo

This paper proposes a real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving. To determine driver fatigue in real time, wavelet entropy with a sliding window and pulse coupled neural network (PCNN) were used to process the EEG signals in the visual area (the main information input route). To detect the fatigue danger, the neural mechanism of driver fatigue was analyzed. The functional brain networks were employed to track the fatigue impact on processing capacity of brain. The results show the overall functional connectivity of the subjects is weakened after long time driving tasks. The regularity is summarized as the fatigue convergence phenomenon. Based on the fatigue convergence phenomenon, we combined both the input and global synchronizations of brain together to calculate the residual amount of the information processing capacity of brain to obtain the dangerous points in real time. Finally, the danger detection system of the driver fatigue based on the neural mechanism was validated using accident EEG. The time distributions of the output danger points of the system have a good agreement with those of the real accident points.

Resumo Limpo

paper propos realtim electroencephalogram eegbas detect method potenti danger fatigu drive determin driver fatigu real time wavelet entropi slide window puls coupl neural network pcnn use process eeg signal visual area main inform input rout detect fatigu danger neural mechan driver fatigu analyz function brain network employ track fatigu impact process capac brain result show overal function connect subject weaken long time drive task regular summar fatigu converg phenomenon base fatigu converg phenomenon combin input global synchron brain togeth calcul residu amount inform process capac brain obtain danger point real time final danger detect system driver fatigu base neural mechan valid use accid eeg time distribut output danger point system good agreement real accid point

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