Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender

Good mental health is important in our daily life. A person commonly finds stress as a barrier to enhance an individual’s performance. Be reminded that not all people have the same level of stress because different people have dissimilar problems in their life. In addition, different level of age an...

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Main Authors:	Nor Shahrudin, Nur Shahirah, Sidek, Khairul Azami, Jusoh, Ahmad Zamani
Format:	Article
Language:	English English
Published:	Institute of Advanced Engineering and Science 2019
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/71191/ http://irep.iium.edu.my/71191/ http://irep.iium.edu.my/71191/ http://irep.iium.edu.my/71191/1/18478-35802-1-PB.pdf http://irep.iium.edu.my/71191/7/71191_Electrocardiogram_scopus.pdf

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recordtype	eprints
spelling	iium-711912019-07-12T01:16:02Z http://irep.iium.edu.my/71191/ Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender Nor Shahrudin, Nur Shahirah Sidek, Khairul Azami Jusoh, Ahmad Zamani TK7885 Computer engineering Good mental health is important in our daily life. A person commonly finds stress as a barrier to enhance an individual’s performance. Be reminded that not all people have the same level of stress because different people have dissimilar problems in their life. In addition, different level of age and gender will affect unequal amount of stress. Electrocardiogram (ECG) signal is an electrical indicator of the heart that can detect changes of human response which relates to our emotions and reactions. Thus, this research proposed a non-intrusive detector to identify stress level for both gender and different classification of age using the ECG. A total of 30 healthy subjects were involved during the data acquisition stage. Data acquisition which initialize ECG data were divided into two conditions; which are normal and stress states. ECG data for normal state only need the participant to breath in and out normally. In other hand, the participants also need to undergo Stroop Colour word test as a stress inducer to represent ECG in stress state. Then, Sgolay filter was selected in the pre-processing stage to remove artifacts in the signal. The process was followed by feature extraction of the ECG signal and finally classified using RR Interval (RRI), different amplitudes of R peaks and Cardioid graph were used to evaluate the performance of the proposed technique. As a result, Class 5 (age range between 50-59 years old) marks the highest changes of stress level rather than other classes, while women are more affected by stress rather than men by showing tremendous percentage changes between normal and stress level over the proposed classifiers. The result proves that ECG signals can be used as an alternative mechanism to recognize stress more efficiently with the integration of gender and age variabilities. Institute of Advanced Engineering and Science 2019-07 Article PeerReviewed application/pdf en http://irep.iium.edu.my/71191/1/18478-35802-1-PB.pdf application/pdf en http://irep.iium.edu.my/71191/7/71191_Electrocardiogram_scopus.pdf Nor Shahrudin, Nur Shahirah and Sidek, Khairul Azami and Jusoh, Ahmad Zamani (2019) Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender. Indonesian Journal of Electrical Engineering and Computer Science, 15 (1). pp. 199-210. ISSN 2502-4752 E-ISSN 2502-4760 http://ijeecs.iaescore.com/index.php/IJEECS/article/view/18478/12555 10.11591/ijeecs.v15.i1.pp199-210
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK7885 Computer engineering
spellingShingle	TK7885 Computer engineering Nor Shahrudin, Nur Shahirah Sidek, Khairul Azami Jusoh, Ahmad Zamani Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender
description	Good mental health is important in our daily life. A person commonly finds stress as a barrier to enhance an individual’s performance. Be reminded that not all people have the same level of stress because different people have dissimilar problems in their life. In addition, different level of age and gender will affect unequal amount of stress. Electrocardiogram (ECG) signal is an electrical indicator of the heart that can detect changes of human response which relates to our emotions and reactions. Thus, this research proposed a non-intrusive detector to identify stress level for both gender and different classification of age using the ECG. A total of 30 healthy subjects were involved during the data acquisition stage. Data acquisition which initialize ECG data were divided into two conditions; which are normal and stress states. ECG data for normal state only need the participant to breath in and out normally. In other hand, the participants also need to undergo Stroop Colour word test as a stress inducer to represent ECG in stress state. Then, Sgolay filter was selected in the pre-processing stage to remove artifacts in the signal. The process was followed by feature extraction of the ECG signal and finally classified using RR Interval (RRI), different amplitudes of R peaks and Cardioid graph were used to evaluate the performance of the proposed technique. As a result, Class 5 (age range between 50-59 years old) marks the highest changes of stress level rather than other classes, while women are more affected by stress rather than men by showing tremendous percentage changes between normal and stress level over the proposed classifiers. The result proves that ECG signals can be used as an alternative mechanism to recognize stress more efficiently with the integration of gender and age variabilities.
format	Article
author	Nor Shahrudin, Nur Shahirah Sidek, Khairul Azami Jusoh, Ahmad Zamani
author_facet	Nor Shahrudin, Nur Shahirah Sidek, Khairul Azami Jusoh, Ahmad Zamani
author_sort	Nor Shahrudin, Nur Shahirah
title	Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender
title_short	Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender
title_full	Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender
title_fullStr	Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender
title_full_unstemmed	Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender
title_sort	electrocardiogram (ecg) based stress recognition integrated with different classification of age and gender
publisher	Institute of Advanced Engineering and Science
publishDate	2019
url	http://irep.iium.edu.my/71191/ http://irep.iium.edu.my/71191/ http://irep.iium.edu.my/71191/ http://irep.iium.edu.my/71191/1/18478-35802-1-PB.pdf http://irep.iium.edu.my/71191/7/71191_Electrocardiogram_scopus.pdf
first_indexed	2023-09-18T21:41:03Z
last_indexed	2023-09-18T21:41:03Z
_version_	1777413142806003712

Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender

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