Electrocardiogram based classifier for driver drowsiness detection

Driver drowsiness may cause traffic injuries and death. In literature, various methods, for instance, image-based, vehicle-based, and biometric-signals-based, have been proposed for driver drowsiness detection. In this paper, a new approach using Electrocardiogram is discussed. Performance evaluation is carried out for the driver drowsiness classifier. The developed classifier yields overall accuracy, sensitivity, and specificity of 76.93%, 77.36%, and 76.5% respectively. Results have revealed that the performance of proposed classifier is better than traditional methods.