A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals

Abstract

The interest in monitoring a drivers conditions and performance has increased in the past years, to make the roads safer both for drivers and pedestrians. This raised the idea of developing a system to monitor the drivers conditions to prevent road disasters. In this paper, we propose a system to monitor the drivers fatigue and drowsiness, based on the Car- dioWheel system, developed by CardioID. The proposed system records both the persons ECG signal and the motion of the steering wheel during the driving session. The amount of data acquired demands a compression stage for transmission with the goal to reduce the required bandwidth. The transmission of the compressed data is done via Bluetooth Low Energy, with an exclusive profile developed for this system. To detect fatigue and drowsiness patterns, a machine learning approach was taken. Among the evaluated classifiers, the Support Vector Machines technique proved to be the best classification method with the highest accuracy. Thus, the developed prototype has the ability to warn the driver about his physiological and physical states, increasing the safety in the roads.