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SVM to Classify Mental Stress in Driver’s Using HRV Analysis


Affiliations
1 Department of ECE, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, India
2 Department of ECE, JNTUK, Narasaraopet, India
     

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Mental stress can be evoked by a number of mental tasks like solving arithmetic problems, public speaking, financial worries, work pressure, etc. Today stress has become a part of our life. Stress causes anger, anxiety, depression, heart attacks, etc. which leads to physical and mental illness. A lot of research work has been happening to measure, identify and analyze human stress levels. By using physiological signals human stress levels can be resolved and this is the most reliable method among many stress monitoring methods. HRV is used as a measure for stress as it makes a change in HRV. In this work time domain, frequency domain and nonlinear parameters obtained from HRV analysis (from ECG signal) are used to detect mental stress in driver’s and Support Vector Machine (SVM) is used to classify mental stress. The algorithm is validated through MIT-BIH database ECG signals. The collected data is “Stress Recognition in Automobile Driver database (DRIVEDB)”.

Keywords

Mental Stress, Heart Rate Variability (HRV), Electrocardiogram (ECG), Support Vector Machine (SVM), MIT-BIH Database.
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Abstract Views: 359

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  • SVM to Classify Mental Stress in Driver’s Using HRV Analysis

Abstract Views: 359  |  PDF Views: 4

Authors

L. V. Rajani Kumari
Department of ECE, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, India
Y. Padma Sai
Department of ECE, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, India
N. Balaji
Department of ECE, JNTUK, Narasaraopet, India

Abstract


Mental stress can be evoked by a number of mental tasks like solving arithmetic problems, public speaking, financial worries, work pressure, etc. Today stress has become a part of our life. Stress causes anger, anxiety, depression, heart attacks, etc. which leads to physical and mental illness. A lot of research work has been happening to measure, identify and analyze human stress levels. By using physiological signals human stress levels can be resolved and this is the most reliable method among many stress monitoring methods. HRV is used as a measure for stress as it makes a change in HRV. In this work time domain, frequency domain and nonlinear parameters obtained from HRV analysis (from ECG signal) are used to detect mental stress in driver’s and Support Vector Machine (SVM) is used to classify mental stress. The algorithm is validated through MIT-BIH database ECG signals. The collected data is “Stress Recognition in Automobile Driver database (DRIVEDB)”.

Keywords


Mental Stress, Heart Rate Variability (HRV), Electrocardiogram (ECG), Support Vector Machine (SVM), MIT-BIH Database.

References





DOI: https://doi.org/10.36039/ciitaas%2F9%2F9%2F2017%2F165809.181-185