The study of time domain features of EMG signals for detecting driver’s drowsiness

Faradila, Naim and Mahfuzah, Mustafa and Norizam, Sulaiman and Noor Aisyah, Ab Rahman (2022) The study of time domain features of EMG signals for detecting driver’s drowsiness. In: Lecture Notes in Electrical Engineering. Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2020 , 6 August 2020 , Gambang. pp. 427-438., 730. ISSN 1876-1100 ISBN 978-981334596-6 (Published)

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Abstract

Fatigue or drowsiness is one of the major causes of traffic accidents in Malaysia. Physiological signals such as EMG is a useful input to detect drowsiness in drivers. The time domain features are easy to compute and well researched in the field of EMG hand motion detection. The focus of this paper is to find the best set of time domain features to detect drowsiness in drivers’ EMG signal from biceps brachii muscle. This study analyzes the time domain features of EMG signals in detecting the drowsiness in drivers during a 2 h simulated driving session. Nine time-domain features are applied to all 15 samples and classified using six classifiers. The best single feature for the long duration signal is the mean absolute value slope (MAVS) with 80% accuracy using Naïve Bayes (NB) classifiers. All features combined gives the highest accuracy of 85% using linear discriminant analysis (LDA) classifier.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Biceps brachii; Driver drowsiness; EMG; LDA; MAVS; NB; Signal processing; Time-domain features
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	30 Oct 2024 04:24
Last Modified:	30 Oct 2024 04:24
URI:	http://umpir.ump.edu.my/id/eprint/42244
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