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Regression Analysis of Heart Rate for Driving Fatigue Using Box-Behnken Design.
Muhammad Shafiq Ibrahim1, Seri Rahayu Kamat1, Syamimi Shamsuddin2
Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia1
Department of Community Health, Advanced Medical and Dental Institute, Universiti Sains Malaysia, 13200 Kepala Batas, Pulau Pinang, Malaysia2
Page 1 – 13 | Vol. 8 No. 2 2023 | Available online on 30 Dec 2023
There are few road accident studies that use heart rate as an indicator of driving fatigue. This study offers a mathematical regression analysis to discover which independent variables (driving speed, driving duration, body mass index (BMI), gender and types of roads) are significant in influencing the heart rate and the way these parameters interact to indicate driver fatigue. The regression analysis was conducted using a Box-Behnken design by Design Expert software. The results revealed that the values of Prob>F for all variables were less than 0.01%, indicating that all variables influenced heart rate significantly. The heart rate increased when driving speed, driving duration and BMI increased. The similar pattern was observed as the driving path shifted from urban to a moderately difficult uphill/downhill road. However, the pulse rate reduced when a female driver was replaced by a male driver. The model’s accuracy was evaluated by comparing the output data obtained from actual road driving with software prediction. First, the prediction interval of both techniques’ output data was within 95%, meeting the minimum quantitative criteria of 90% predictive interval. Subsequently, the residual errors were less than 10%. The application of regression analysis to investigate the driver’s physiological system as a factor in driving fatigue is becoming less common. The majority of current research focuses on perceptual, psychological and electrophysiological methods to detect driving fatigue. As a result, a future study will assess the effect of cognitive skills impairment, such as decision-making, on driving fatigue using the same methodology. The regression model will be useful to shed light on traffic safety measures for preventing fatigue-related road accidents.
driving fatigue, heart rate, regression analysis, road accident, mathematical regression analysis.
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Human Factors & Ergonomics Journal (HFEJ), eISSN: 2590-3705 is the official Journal of Human Factors and Ergonomics Society Malaysia. The journal is published on a biannual basis. HFEJ aims to address current research in the field of Ergonomics in addition to the broad coverage of cognitive ergonomics, user experience, physical ergonomics and others such as transportation, industrial design and industrial engineering. HFEJ is a member of, and subscribes to the principles of the COPE (Committee on Publication Ethics), as such we only accept original work.