ECG-based driving fatigue detection using heart rate variability analysis with mutual information

Halomoan, Junartho and Ramli, Kalamullah and Sudiana, Dodi and Gunawan, Teddy Surya and Salman, Muhammad (2023) ECG-based driving fatigue detection using heart rate variability analysis with mutual information. Information, 14 (10). pp. 1-41. E-ISSN 2078-2489

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Abstract

One of the WHO’s strategies to reduce road traffic injuries and fatalities is to enhance vehicle safety. Driving fatigue detection can be used to increase vehicle safety. Our previous study developed an ECG-based driving fatigue detection framework with AdaBoost, producing a high cross-validated accuracy of 98.82% and a testing accuracy of 81.82%; however, the study did not consider the driver’s cognitive state related to fatigue and redundant features in the classification model. In this paper, we propose developments in the feature extraction and feature selection phases in the driving fatigue detection framework. For feature extraction, we employ heart rate fragmentation to extract non-linear features to analyze the driver’s cognitive status. These features are combined with features obtained from heart rate variability analysis in the time, frequency, and non-linear domains. In feature selection, we employ mutual information to filter redundant features. To find the number of selected features with the best model performance, we carried out 28 combination experiments consisting of 7 possible selected features out of 58 features and 4 ensemble learnings. The results of the experiments show that the random forest algorithm with 44 selected features produced the best model performance testing accuracy of 95.45%, with cross-validated accuracy of 98.65%.

Item Type:	Article (Journal)
Uncontrolled Keywords:	heart rate fragmentation; fatigue detection; non-linear feature; electrocardiogram; heart rate variability analysis; mutual information; ensemble learning
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Engineering
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	15 Nov 2023 09:11
Last Modified:	15 Nov 2023 09:13
URI:	http://irep.iium.edu.my/id/eprint/108081

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