Physiological Signal Monitoring System to Analyze Driver Attentiveness

Abstract

With the increase in the number of accidents, driver attentiveness is becoming more and more important, and driver attentiveness detection is a technology that is needed to save lives. This research presents preliminary results on the methods of detecting driver drowsiness through the analysis of electromyography (EMG), electroencephalography (EEG) electrocardiography (ECG) signals. EMG signals will be sensing the eye muscle movements, which indicates eye blink rate. Similarly, the sensing of ECG signals monitors the heart rate while driving. A three-lead electrode system was used for measuring EMG and ECG signals while participants were in a variety of scenarios. EEG signals monitor driver drowsiness. Scenarios include a restful state, a driving simulation, and in a moving vehicle. Filtering and correlation techniques were used to process different types of signals to determine heart rates, eye blink rates and brain activities. These rates were compared with rates indicating drowsiness, whether the participant was showing signs of drowsiness.