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The enhancement on stress levels based on physiological signal and self-stress assessment

The prolonged stress needs to be determined and controlled before it harms the physical and mental conditions. This research used questionnaire and physiological approaches in determine stress. EEG signal is an electrophysiological signal to analyze the signal features. The standard features used ar...

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Main Authors: Zarith Liyana, Zahari, Mahfuzah, Mustafa, Zaridah, Mat Zain, Rafiuddin, Abdubrani, Faradila, Naim
Format: Article
Language:English
Published: International Information and Engineering Technology Association 2021
Subjects:
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/33118/1/The%20enhancement%20on%20stress%20levels%20based%20on%20physiological%20signal.pdf
http://umpir.ump.edu.my/id/eprint/33118/
https://doi.org/10.18280/ts.380519
https://doi.org/10.18280/ts.380519
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spelling my.ump.umpir.331182022-04-28T06:34:33Z http://umpir.ump.edu.my/id/eprint/33118/ The enhancement on stress levels based on physiological signal and self-stress assessment Zarith Liyana, Zahari Mahfuzah, Mustafa Zaridah, Mat Zain Rafiuddin, Abdubrani Faradila, Naim T Technology (General) TK Electrical engineering. Electronics Nuclear engineering The prolonged stress needs to be determined and controlled before it harms the physical and mental conditions. This research used questionnaire and physiological approaches in determine stress. EEG signal is an electrophysiological signal to analyze the signal features. The standard features used are peak-to-peak values, mean, standard deviation and root means square (RMS). The unique features in this research are Matthew Correlation Coefficient Advanced (MCCA) and multimodal capabilities in the area of frequency and time-frequency analysis are proposed. In the frequency domain, Power Spectral Density (PSD) techniques were applied while Short Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were utilized to extract seven features based on time-frequency domain. Various methods applied from previous works are still limited by the stress indices. The merged works between quantities score and physiological measurements were enhanced the stress level from three-levels to six stress levels based on music application will be the second contribution. To validate the proposed method and enhance performance between electroencephalogram (EEG) signals and stress score, support vector machine (SVM), random forest (RF), K- nearest neighbor (KNN) classifier is needed. From the finding, RF gained the best performance average accuracy 85% ±10% in Ten-fold and K-fold techniques compared with SVM and KNN. International Information and Engineering Technology Association 2021-10 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/33118/1/The%20enhancement%20on%20stress%20levels%20based%20on%20physiological%20signal.pdf Zarith Liyana, Zahari and Mahfuzah, Mustafa and Zaridah, Mat Zain and Rafiuddin, Abdubrani and Faradila, Naim (2021) The enhancement on stress levels based on physiological signal and self-stress assessment. Traitement du Signal, 38 (5). pp. 1439-1447. ISSN 0765-0019 https://doi.org/10.18280/ts.380519 https://doi.org/10.18280/ts.380519
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Zarith Liyana, Zahari
Mahfuzah, Mustafa
Zaridah, Mat Zain
Rafiuddin, Abdubrani
Faradila, Naim
The enhancement on stress levels based on physiological signal and self-stress assessment
description The prolonged stress needs to be determined and controlled before it harms the physical and mental conditions. This research used questionnaire and physiological approaches in determine stress. EEG signal is an electrophysiological signal to analyze the signal features. The standard features used are peak-to-peak values, mean, standard deviation and root means square (RMS). The unique features in this research are Matthew Correlation Coefficient Advanced (MCCA) and multimodal capabilities in the area of frequency and time-frequency analysis are proposed. In the frequency domain, Power Spectral Density (PSD) techniques were applied while Short Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were utilized to extract seven features based on time-frequency domain. Various methods applied from previous works are still limited by the stress indices. The merged works between quantities score and physiological measurements were enhanced the stress level from three-levels to six stress levels based on music application will be the second contribution. To validate the proposed method and enhance performance between electroencephalogram (EEG) signals and stress score, support vector machine (SVM), random forest (RF), K- nearest neighbor (KNN) classifier is needed. From the finding, RF gained the best performance average accuracy 85% ±10% in Ten-fold and K-fold techniques compared with SVM and KNN.
format Article
author Zarith Liyana, Zahari
Mahfuzah, Mustafa
Zaridah, Mat Zain
Rafiuddin, Abdubrani
Faradila, Naim
author_facet Zarith Liyana, Zahari
Mahfuzah, Mustafa
Zaridah, Mat Zain
Rafiuddin, Abdubrani
Faradila, Naim
author_sort Zarith Liyana, Zahari
title The enhancement on stress levels based on physiological signal and self-stress assessment
title_short The enhancement on stress levels based on physiological signal and self-stress assessment
title_full The enhancement on stress levels based on physiological signal and self-stress assessment
title_fullStr The enhancement on stress levels based on physiological signal and self-stress assessment
title_full_unstemmed The enhancement on stress levels based on physiological signal and self-stress assessment
title_sort enhancement on stress levels based on physiological signal and self-stress assessment
publisher International Information and Engineering Technology Association
publishDate 2021
url http://umpir.ump.edu.my/id/eprint/33118/1/The%20enhancement%20on%20stress%20levels%20based%20on%20physiological%20signal.pdf
http://umpir.ump.edu.my/id/eprint/33118/
https://doi.org/10.18280/ts.380519
https://doi.org/10.18280/ts.380519
_version_ 1732945659795865600
score 13.211869

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