Driver fatigue is a major exogenous cause of fatal road accidents and has implications for Malaysian road safety. The major aspect that causes human errors is fatigue/drowsiness due to task-induced factors or attitude/behavior of the driver. Therefore, it is necessary to identify significant index to detect driver fatigue and associate that index with the level of alertness, for road safety and for use by regulatory bodies. This can be carried out by observing the physiological behavior through the Event-related potentials (ERPs) and electroencephalography (EEG) measures. ERP’s are very small voltage potentials that examine the information processing and characterize the brain structures in response to specific events or stimuli. Studies have shown EEG changes that are time-locked to sensory, cognitive or motor events are the most promising psychophysiological measures for assessing mental process and better indicators of fatigue. Hence, in this research work, to detect the driver fatigue and associate with alertness, it is proposed to develop an adaptive fatigue identification algorithm based on the EEG frequency spindles. As for a preliminary work, two secondary set of EEG data from Physionet are used. The signals will be analyzed to extract discriminant features and for classification of the level of fatigue
Volume 11 | Issue 5
Pages: 514-523