Measurements of Galvanic Skin Response on Subjects Affected by Stress

Author:

Dascălu Loredana Cristina1,Babiș Claudiu1,Chivu Oana1,Iacobescu Gabriel1,Alecusan Ana Maria2,Semenescu Augustin3

Affiliation:

1. Welding and Material Technology Department, Politehnica University of Bucharest, Romania

2. Theory of Mechanisms and Robots Department, Politehnica University of Bucharest, Romania

3. Economics Engineering Department, Politehnica University of Bucharest, Romania

Abstract

Abstract The aim of the present paper is to study the Galvanic Skin Response (GSR) level on subjects affected by stress. The device that we have used, connects to the people by finger electrodes to record GSR. The purpose was to find statistical differences between the activities (mental task, walking, sitting and to fill out a survey about their lives) and their stress level. During the experiment, it was found that the survey caused the source of high stress and increasing skin conductance was caused by sweat secretion (mental, physical activity). Is needed to work of collecting data from more subjects because GSR is depended on human behaviour, is variable upon many factors (their eating habits, their emotional state, their gender, their relationship with family, etc) and we need to build a substantial data set for a valid research.

Publisher

Walter de Gruyter GmbH

Reference8 articles.

1. de nivel de estres - Investigaciones en el medio academico en Rumania y Cientifico Cultural de la Universidad Nacional de San Antonio Abad del Nr de ISSN;Dascălu;Revista,2014

2. What s your current stress level ? Detection of stress patterns from GSR sensor data Eindhoven University of Technology;John

3. Galvanic Skin Sensor for Early Diagnosis Of Sudomotor Dysfunction : Application to Sensor;Khalfallah;Diabetes IEEE,2010

4. and others Personalized Stress Detection from Physiological Measurements The Ohio State University;Minh

5. Computer Interface for classifying EEG Correlates of Chronic Mental Stress In Proceedings of International Joint Conference on San CA;Khosrowabadi;Brain Neural Networks USA,2011

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