Estimation of Fatigue in Drivers by Analysis of Brain Networks

Synchronization measures between Electro-Encephalogram (EEG) signals from different regions of the brain characterize the integration and segregation of brain areas during any mental and physical activity. EEG can reflect both the normal and abnormal activity of the brain and is widely used as a powerful tool in the field of clinical neurophysiology. Being sensitive to decreasing alertness and decline in vigilance, EEG can be used to predict performance degradation due to mental or physical fatigue. This paper studies the variation of fatigue levels in human drivers in a sleep-deprivation experiment by analyzing the synchronization between EEG recorded from brain areas. A Weighted Visibility Graph (WVG) technique has been proposed to quantify the synchronization between brain regions, which is then formulated in terms of a complex network. The change in the parameters of the network is analyzed to find the variation of connectivity and hence to trace the increase in fatigue levels of an individual.