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Heart Rate Variability-Based Detection of Driver Drowsiness and its Validation using EEG

Rajkumar V. P.*, Papitha P.**, Rashiyadevi M.***, Shalini G.****, Thrisha G.*****

*-***** Department of Biomedical Engineering, Gnanamani College of Technology, Namakkal, Tamil Nadu, India.

Periodicity:January - June'2024
DOI : https://doi.org/10.26634/jes.12.2.20922

Abstract

Being drowsy while driving is considered highly dangerous. Addressing this issue is crucial because drivers' lives are at risk. Preventing accidents becomes challenging if drivers experience drowsiness. This study aims to develop a device to assist drivers, especially at night, in preventing accidents caused by drowsiness or sleepiness. The goal is to design an electronic device capable of detecting driver drowsiness by monitoring random changes in steering movement and wheel speed reduction. The vibration sensor's threshold can be adjusted accordingly to take appropriate action. If the driver falls asleep, a vibrator attached to the eye blink sensor frame vibrates, accompanied by warning messages on an LCD display. Depending on the severity, the device can slow down or stop the vehicle. Furthermore, the IoT module notifies the owner, providing the driver's location, photograph, and nearby police stations' details. This alerts the driver and informs the owner simultaneously. The proposed web application manages system parameters and sends alerts to drivers. The system proposes using a heartbeat sensor and an eye blink sensor to detect driver stress and pupil dilation. If drowsiness is detected, the system alerts the driver with a buzzer and slows down the vehicle if the driver fails to wake up. Additionally, a gas sensor indicator with a buzzer monitors fuel levels and detects leaks.

Keywords

Heart Rate Variability (HRV), Driver Drowsiness Detection, EEG Validation, Physiological Indicators of Drowsiness, Autonomic Nervous System, Biofeedback Systems.

How to Cite this Article?

Rajkumar, V. P., Papitha, P., Rashiyadevi, M., Shalini, G. and Thrisha, G. (2024). Heart Rate Variability-Based Detection of Driver Drowsiness and its Validation using EEG. i-manager’s Journal on Embedded Systems, 12(2), 20-25. https://doi.org/10.26634/jes.12.2.20922

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