Research Journal of Pharmacy and Technology

Saroj Kumar Panigrahy ¹, Sanjay Kumar Jena ¹, Ashok Kumar Turuk ¹

Affiliations
1 Department of Computer Science Engineering, NIT, Rourkela, IN

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.

Keywords

Stress, Biological Sensor, Electrodermal Activity, EDA, Galvanic Skin Response, GSR, Wireless Body Sensor Network, WBSN.

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Saroj Kumar Panigrahy ¹, Sanjay Kumar Jena ¹, Ashok Kumar Turuk ¹

Affiliations
1 Department of Computer Science Engineering, NIT, Rourkela, IN

Abstract

It is an infeasible task for psychoanalysts to monitor the chronic mental stress of patients. Due to topical and innovative developments in wireless sensor technology and physiological sensors, researchers have been attracted to pursue research in wireless body area sensor networks (WBASN) or wireless body area networks (WBSN). As a result, the wireless sensor technology has enabled medical science in enhancing real-time health monitoring and maintaining a better healthcare scenario. In our previous work, the mental stress sensor presented was able to detect the stress condition based on the Galvanic Skin Response (GSR) only with an average accuracy of about 76%. In this article, a system has been presented for sensing human mental stress by acquisition, processing and analysing the GSR and heart rate or pulse rate signals from human body. This system is proficient in detection of the mental stress condition using the GSR and heart rate signals assimilated by wearable physiological sensors in wired or wireless environments. For evaluation of the system performance, well-known supervised binary classifiers have been selected for classifying the GSR and heart rate data from the physiological dataset available and the results are discussed. This multi-sensor stress detection system has average accuracy more than the previous stress detection system using GSR.

Keywords

Mental Stress, Biological Sensor, Physiological Sensor, Electrodermal Activity, EDA, Galvanic Skin Response, GSR, Wireless Body Area Sensor Network, WBASN, Wireless Body Area Network (WBAN).

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