Development of a driver drowsiness monitoring system using electrocardiogram

Driver drowsiness has become a common issue that leads to road accidents and death. Accidents not only affect the physical body of the driver, but it also affects people in the surrounding, physical road conditions, and environments. It is proven in previous studies that biological signal are closel...

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Main Authors:	Nor Shahrudin, Nur Shahirah, Sidek, Khairul Azami, Ismail, Ahmad Fadzil
Format:	Article
Language:	English English
Published:	Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) 2018
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/63338/ http://irep.iium.edu.my/63338/ http://irep.iium.edu.my/63338/1/3655-9759-1-SM.pdf http://irep.iium.edu.my/63338/7/63338%20Development%20of%20a%20driver%20drowsiness%20monitoring%20system%20using%20electrocardiogram%20SCOPUS.pdf

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recordtype	eprints
spelling	iium-633382018-04-18T00:55:11Z http://irep.iium.edu.my/63338/ Development of a driver drowsiness monitoring system using electrocardiogram Nor Shahrudin, Nur Shahirah Sidek, Khairul Azami Ismail, Ahmad Fadzil TK7885 Computer engineering Driver drowsiness has become a common issue that leads to road accidents and death. Accidents not only affect the physical body of the driver, but it also affects people in the surrounding, physical road conditions, and environments. It is proven in previous studies that biological signal are closely related to a person’s reaction. Electrocardiogram (ECG), which is an electrical indicator of the heart, provides such criteria as it reflects the heart activity. Morphological signal of the heart is strongly correlated to our actions which relates to our emotions and reactions. Thus, this study proposed a non-intrusive detector to detect driver drowsiness by using the ECG. A total of 10 subjects were obtained from The Cyclic Alternating Pattern (CAP) Sleep database. The signals are later processed using low pass Butterworth filter with 0.1 cutoff frequency. Then, QRS complexes are extracted from the acquired ECG signal. Classification techniques such as RR interval and different of amplitude at R peak were used in order to differentiate between normal and drowsy ECG signal. Cardioid based graph was used to support the argument made in analyzing area and circumference of both normal and drowsy graph. The result shows that RR Interval of a drowsy state increased almost 22% rather than in normal state. The percentage different of amplitude difference at R peak between normal and drowsy state can reach up to 36.33%. In terms of cardioid, area, perimeter and Euclidean distance of the centroid are always higher than drowsy. Thus, from the outcomes that been suggested for drowsiness detection using RR interval and amplitude of R are able to become as the most efficient drowsiness detection. Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) 2018 Article PeerReviewed application/pdf en http://irep.iium.edu.my/63338/1/3655-9759-1-SM.pdf application/pdf en http://irep.iium.edu.my/63338/7/63338%20Development%20of%20a%20driver%20drowsiness%20monitoring%20system%20using%20electrocardiogram%20SCOPUS.pdf Nor Shahrudin, Nur Shahirah and Sidek, Khairul Azami and Ismail, Ahmad Fadzil (2018) Development of a driver drowsiness monitoring system using electrocardiogram. Journal of Telecommunication, Electronic and Computer Engineering, 10 (1-6). pp. 11-15. ISSN 2180-1843 E-ISSN 2289-8131 http://journal.utem.edu.my/index.php/jtec/article/view/3655/2541
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 Ismail, Ahmad Fadzil Development of a driver drowsiness monitoring system using electrocardiogram
description	Driver drowsiness has become a common issue that leads to road accidents and death. Accidents not only affect the physical body of the driver, but it also affects people in the surrounding, physical road conditions, and environments. It is proven in previous studies that biological signal are closely related to a person’s reaction. Electrocardiogram (ECG), which is an electrical indicator of the heart, provides such criteria as it reflects the heart activity. Morphological signal of the heart is strongly correlated to our actions which relates to our emotions and reactions. Thus, this study proposed a non-intrusive detector to detect driver drowsiness by using the ECG. A total of 10 subjects were obtained from The Cyclic Alternating Pattern (CAP) Sleep database. The signals are later processed using low pass Butterworth filter with 0.1 cutoff frequency. Then, QRS complexes are extracted from the acquired ECG signal. Classification techniques such as RR interval and different of amplitude at R peak were used in order to differentiate between normal and drowsy ECG signal. Cardioid based graph was used to support the argument made in analyzing area and circumference of both normal and drowsy graph. The result shows that RR Interval of a drowsy state increased almost 22% rather than in normal state. The percentage different of amplitude difference at R peak between normal and drowsy state can reach up to 36.33%. In terms of cardioid, area, perimeter and Euclidean distance of the centroid are always higher than drowsy. Thus, from the outcomes that been suggested for drowsiness detection using RR interval and amplitude of R are able to become as the most efficient drowsiness detection.
format	Article
author	Nor Shahrudin, Nur Shahirah Sidek, Khairul Azami Ismail, Ahmad Fadzil
author_facet	Nor Shahrudin, Nur Shahirah Sidek, Khairul Azami Ismail, Ahmad Fadzil
author_sort	Nor Shahrudin, Nur Shahirah
title	Development of a driver drowsiness monitoring system using electrocardiogram
title_short	Development of a driver drowsiness monitoring system using electrocardiogram
title_full	Development of a driver drowsiness monitoring system using electrocardiogram
title_fullStr	Development of a driver drowsiness monitoring system using electrocardiogram
title_full_unstemmed	Development of a driver drowsiness monitoring system using electrocardiogram
title_sort	development of a driver drowsiness monitoring system using electrocardiogram
publisher	Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM)
publishDate	2018
url	http://irep.iium.edu.my/63338/ http://irep.iium.edu.my/63338/ http://irep.iium.edu.my/63338/1/3655-9759-1-SM.pdf http://irep.iium.edu.my/63338/7/63338%20Development%20of%20a%20driver%20drowsiness%20monitoring%20system%20using%20electrocardiogram%20SCOPUS.pdf
first_indexed	2023-09-18T21:29:50Z
last_indexed	2023-09-18T21:29:50Z
_version_	1777412436673953792

Development of a driver drowsiness monitoring system using electrocardiogram

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