Detecting the stress level of drivers

In past few decades , a lot of people lost their life due to the increase in driver drowsiness, fatigue and mental stress. Stress and driving are a dangerous combination and can lead to life-threatening situations, evidence by the large number of road traffic crashes that occur every year due to driver stress. The aim of this paper is to detect three levels of low, medium, high stress in different events for reducing death and increasing drivers’ safety while driving.Physiological and physical response signals show symptoms for stress can be used to provide hundreds of features. We can evaluate stress and fatigue by measuring physiological parameters like Electrocardiogram (ECG), Electromyogram (EMG), Skin conductance (SC) also called as Galvanic skin response (GSR) and Respiration rate (RR) continuously over a period of time. Among physiological signals, GSR and HRV have the highest correlation with individual stress.Three levels of stress are taken into account and two independent features including rising time and amplitude are extracted. These features are extracted from foot and hand GSR signals. The result indicates that the foot amplitude feature of the GSR signal is a reliable source of stress classification with an accuracy rate of ۸۵.۴%This paper presents method of stress level classification using GSR during the real-world driving task with a new classification method. In this study, the data collected by Picard and his coworkers are used, available in the PHYSIONET database.