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Detection of human stress using short-term ECG and HRV signals

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Main Authors: Karthikeyan, Palanisamy, Murugappan, Muthusamy, Dr., Sazali, Yaacob, Prof. Dr.
Other Authors: karthi_209170@yahoo.com
Format: Article
Language:English
Published: World Scientific Publishing Company 2014
Subjects:
Electrocardiogram (ECG)
Heart rate variability (HRV)
Human stress detection
Stroop color word test
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33938
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spelling my.unimap-339382014-04-23T04:17:02Z Detection of human stress using short-term ECG and HRV signals Karthikeyan, Palanisamy Murugappan, Muthusamy, Dr. Sazali, Yaacob, Prof. Dr. karthi_209170@yahoo.com murugappan@unimap.edu.my s.yaacob@unimap.edu.my Electrocardiogram (ECG) Heart rate variability (HRV) Human stress detection Stroop color word test Link to publisher's homepage at http://www.worldscientific.com/ This paper introduces a method for resolving the problem of human stress detection through short-term (less than 5 min) electrocardiogram (ECG) and heart rate variability (HRV) signals. The explored methodology helps to improve the stress detection rate and reliability through multiple evidences originated in same sensor. In this work, stress-inducing protocol, data acquisition, preprocessing, feature extraction and classification are the major steps involved to detect the stress. In total, 60 subjects (30 males and 30 females) participated in the Stroop color word-based stress-inducing task and ECG signal was acquired simultaneously. The wavelet denoising algorithm was applied to remove high frequency, baseline wander and power line noises. Discrete wavelet transform (DWT)-based heart rate (HR) detection algorithm is used for deriving HRV signal from the preprocessed ECG signal. The ectopic beat removal method is employed to eliminate the ectopic beat and noise peaks in the HRV signal. In order to detect the stress, the issue of uneven sampling with the HRV signal has been successfully rectified using the Lomb-Scargle periodogram (LSP). The application of LSP in short-term HRV signals (32 s), uneven sampling issue, and power spectral information issue has been rectified and the trustworthiness of the short-term HRV signal has been proved by hypothesis as well as experimental results. Theoretical analysis suggested that a minimum 25 s of online or offline ECG data is required to analyze the autonomous nervous system (ANS) activity related to stress. In addition to the HRV signal, ECG-based stress assessment has been proposed to detect the stress through optimum features using fast Fourier transform (FFT). Various features extracted from the ECG and HRV signal have been classified into normal and stress using PNN and kNN classifiers with different smoothing factor and k values. The experimental results indicate that the proposed methodology for short-term ECG and HRV signal can achieve the overall average classification accuracy of 91.66% and 94.66% in the subject-independent mode. 2014-04-23T04:17:02Z 2014-04-23T04:17:02Z 2013-04 Article Journal of Mechanics in Medicine and Biology, vol. 13(2), 2013, pages 1-29 0219-5194 http://www.worldscientific.com/doi/abs/10.1142/S0219519413500383 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33938 en World Scientific Publishing Company
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Electrocardiogram (ECG)
Heart rate variability (HRV)
Human stress detection
Stroop color word test
spellingShingle Electrocardiogram (ECG)
Heart rate variability (HRV)
Human stress detection
Stroop color word test
Karthikeyan, Palanisamy
Murugappan, Muthusamy, Dr.
Sazali, Yaacob, Prof. Dr.
Detection of human stress using short-term ECG and HRV signals
description Link to publisher's homepage at http://www.worldscientific.com/
author2 karthi_209170@yahoo.com
author_facet karthi_209170@yahoo.com
Karthikeyan, Palanisamy
Murugappan, Muthusamy, Dr.
Sazali, Yaacob, Prof. Dr.
format Article
author Karthikeyan, Palanisamy
Murugappan, Muthusamy, Dr.
Sazali, Yaacob, Prof. Dr.
author_sort Karthikeyan, Palanisamy
title Detection of human stress using short-term ECG and HRV signals
title_short Detection of human stress using short-term ECG and HRV signals
title_full Detection of human stress using short-term ECG and HRV signals
title_fullStr Detection of human stress using short-term ECG and HRV signals
title_full_unstemmed Detection of human stress using short-term ECG and HRV signals
title_sort detection of human stress using short-term ecg and hrv signals
publisher World Scientific Publishing Company
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33938
_version_ 1643797352163573760
score 13.214268

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