A review of ECG data acquisition for driver drowsiness detection

Authors

  • Shahrudin NSN Department of Electrical and Computer Engineering, International Islamic University Malaysia, P.O. Box 10, Jalan Gombak, 50728 Kuala Lumpur
  • Sidek Department of Electrical and Computer Engineering, International Islamic University Malaysia, P.O. Box 10, Jalan Gombak, 50728 Kuala Lumpur

Keywords:

drowsiness, electrocardiogram, data acquisition, bio-signal, steering wheel, technology

Abstract

Over the years, cases related to road accidents and road fatalities keeps increasing. Both cases have potential to put life of a person at risk. One of the factors that leads to accidents are drowsiness. However, several lives can be saved with accurate and reliable drowsiness detection system. Thus, many researchers take this issue seriously by developing drowsiness detection mechanism in reducing cases related to driver drowsiness. As drowsiness is strongly correlated with the heart activities, hence bio-signal is the most preferable indicator to measure the drowsiness level. Reflection of electrical signal in the human body known as Electrocardiogram (ECG) are widely used in monitoring human action and reaction to prevent the occurrence of these devastating incidents. Thus, this paper will review the drowsiness detection technique focusing in ECG data acquisition for driver drowsiness detection. As the first step plays an important role for the whole system, this paper discussed on some open issues in drowsiness mechanism. We hope that this review will support and give some ideas to the future researchers in increasing the reliability of ECG measures towards driver drowsiness detection in reducing accident cases

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Published

2024-02-26

How to Cite

Shahrudin, N. S. N., & Sidek, K. A. (2024). A review of ECG data acquisition for driver drowsiness detection. COMPUSOFT: An International Journal of Advanced Computer Technology, 9(07), 3749–3754. Retrieved from https://ijact.in/index.php/j/article/view/578

Issue

Vol. 9 No. 07 (2020): July

Section

Original Research Article

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