Bonfring International Journal of Software Engineering and Soft Computing
Online ISSN: 2277-5099 | Print ISSN: 2250-1045 | Frequency: 4 Issues/Year
Impact Factor: 0.375 | International Scientific Indexing(ISI) calculate based on International Citation Report(ICR)
Design and Implementation of Stress Management System
Colin D'Souza, U. Vijay Kuma, Vinayak Baddi, Vaibhav J. Revanka and Rohini Hongal
Abstract:
Today?s life is full of frustrations, deadlines, and demands. For many people, stress is so common that it has become an integral part of life. Stress is body?s way of responding to any kind of demand or threat. When you feel threatened, your nervous system responds by re- leasing a flood of stress hormones, including adrenaline due to which body?s conductance changes, heart pounds faster, muscles tighten, blood pressure rises and breath quickens. And they directly correlate the level of stress to one?s emotion or mood. Hence Heartbeat, Body temperature and GSR (Galvanic skin resistance) are the three informative signals that can be used to determine the stress. This work proposes a system which can detect the stress of a person using Temperature, GSR and Pulse sensors to measure body temperature, Skin conductance and Heartbeat respectively and provides a suitable medication. The system can also be used as personal stress assistance system which creates a calm environment to meditate with a time interval of 2minutes, 5minutes and 10minutes.The Raspberry Pi, Arduino and sensors form the hardware part and a GUI provides a user friendly interface .The human body resistance varies from 2 Mega ohm to 10 Kilo ohm based on the emotion, While the normal Heart beat and Body temperature is 60-90 BPM, 28C respectively. The proposed system is successful in measuring these values thus act as a stress management system which helps to cope with the stress and get relieved.
Keywords: Arduino, Raspberry pi2, GSR Sensor, Heartbeat Sensor.
Volume: 6 | Issue: Special Issue on Advances in Computer Science and Engineering and Workshop on Big Data Analytics Editors: Dr.S.B. Kulkarni, Dr.U.P. Kulkarni, Dr.S.M. Joshi and J.V. Vadavi
Pages: 93-97
Issue Date: October , 2016
DOI: 10.9756/BIJSESC.8251
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