A non-invasive approach to detect drowsiness in a monotonous driving environment

Awais, Muhammad ORCID: https://orcid.org/0000-0001-6421-9245, Badruddin, Nasreen and Drieberg, Micheal (2014) A non-invasive approach to detect drowsiness in a monotonous driving environment. In: TENCON 2014 - 2014 IEEE Region 10 Conference. The Institute of Electrical and Electronics Engineers (IEEE). ISBN 9781479940752

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Abstract

Many researchers have found that one of the major contributing factors of road accidents is driver drowsiness. Heart Rate Variability (HRV) is a non-invasive method to observe the influence of autonomic nervous system (ANS) of the human body. The ANS consists of parasympathetic and sympathetic nervous activities and its relation to driver drowsiness is observed by means of HRV analysis. In this study, twenty-two subjects participated in an experiment based on simulated driving environment. The temporal changes for low frequency (LF), high frequency (HF) and LF/HF ratio are observed. LF and HF spectral powers show significant changes from alert to drowsy state. Paired t-test is used to find the statistical significance. The analysis shows that there is a significant (p<;0.01) decrease in the LF/HF ratio when subject is in drowsy state. The observations also conclude with significance that LF decreases (p<;0.001) and HF increases (p<;0.05) from alert to drowsy state. This study shows very encouraging results that can be used to prevent drowsiness related accidents.

Item Type:	Book Section
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Data Science and AI
Depositing User:	LivePure Connector
Date Deposited:	17 Oct 2023 00:49
Last Modified:	10 Dec 2024 01:13
URI:	https://ueaeprints.uea.ac.uk/id/eprint/93339
DOI:	10.1109/tencon.2014.7022356

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