Classification of muscle fatigue during prolonged driving

Ab Ghafar, Noor Azlyn and Azmi, Nur Liyana and Md Nor, Khairul Affendy and Nordin, Nor Hidayati Diyana (2022) Classification of muscle fatigue during prolonged driving. ELEKTRIKA, 21 (3, 2022). pp. 40-46. ISSN 0128-4428

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Abstract

Driving has become essential in transporting people from one place to another. However, prolonged driving could cause muscle fatigue, leading to drowsiness and microsleep. Electromyography (EMG) is an important type of electropsychological signal that is used to measure electrical activity in muscles. The current study attempted to use machine learning algorithms to classify EMG signals recorded from the trapezius muscle of 10 healthy subjects in non-fatigue and fatigue conditions. The EMG signals and the time when muscle fatigue was experienced by the subjects were recorded. The mean frequency (MNF) and median frequency (MDF) of the EMG signals were extracted as dataset features. Six machine learning models were used for the classification: Logistic Regression, Support Vector Machine, Naïve Bayes, k-nearest Neighbour, Decision Tree and Random Forest. The results show that both the MNF and MDF are lower when fatigue conditions exist. In term of the classification performance, the Random Forest, Decision Tree and k-nearest Neighbour classifiers produced the accuracy levels of 85.00%, 83.75% and 81.25% respectively. Thus, the highest accuracy for classifying muscle fatigue due to prolonged driving was obtained by the Random Forest classifier, using both the MNF and MDF of the EMG signals. This method of using the MNF and MDF will be useful in classifying driver’s non-fatigue and fatigue conditions during prolonged driving.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Classification, Electromyography, Median Frequency, Mean Frequency, Muscle fatigue
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA164 Bioengineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Dr Nur Liyana Azmi
Date Deposited:	05 Apr 2023 12:36
Last Modified:	05 Apr 2023 12:36
URI:	http://irep.iium.edu.my/id/eprint/104250

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