Study on Detecting Drowsiness Using Heart Rate Variability via Time and Frequency Domain Analysis

Chong, Kok Lun (2024) Study on Detecting Drowsiness Using Heart Rate Variability via Time and Frequency Domain Analysis. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

Driver drowsiness is a major safety concern on the roads in Malaysia, as it can lead to accidents and fatalities. In this research, the proposed idea is physiological signal-based approach for detecting drowsiness. This study uses physiological signals such as ECG from volunteers, and uses algorithms to analyze these signals and classify them as either drowsy or alert. In this study, an in-depth analysis was conducted on extensive datasets of physiological signal recordings, each accompanied by annotations indicating the drowsy or alert state. The proposed approach is poised to contribute significantly to the development of accurate and dependable drowsiness detection systems, tailored to the unique road conditions in Malaysia, with the potential to reduce accidents stemming from drowsiness. This study also considers the unique challenges of implementing such a system in Malaysia, such as the need for multi-lingual support and the impact of cultural factors on driver behavior. The proposed approach has the potential to significantly improve road safety in Malaysia by detecting driver drowsiness in real-time and alerting the driver to take appropriate actions.