Study and Analysis of Human Stress Detection using Galvanic Skin Response (GSR) Sensor in Wired and Wireless Environments

Abstract

Continuous monitoring of the chronic stress is an infeasible task for physicians and hence its diagnosis is also nontrivial. Recent development in biological sensor and wireless technology has attracted researchers to carry out research in wireless body sensor networks (WBSN). This has enabled medical science in improving real-time monitoring and maintaining human health in a better way. In this work, a system has been developed for sensing human stress, based on acquisition, processing and analysis of the Galvanic Skin Response (GSR) signal collected from human bodies. The system detects human stress condition using the GSR signal acquired by wearable biological sensing devices when the person is in sitting, standing or sleeping conditions using a wired environment. Also the system is capable of remotely sensing human stress (while the person is in remote place within the range of wireless medium) with wireless sensor network technology. Popular supervised binary classifiers have been used for classifying the GSR data from the physiological dataset available in literature into binary classes, i.e., stress condition or relaxed condition and the results are presented.