SUITABILITY OF HEART RATE RECORDING AS PHYSIOLOGICAL MEASURES TOOL TO DETERMINE DRIVERS' PERFORMANCE IMPAIRMENT: A PRELIMINARY STUDY

Khamis, Nor Kamaliana; Ismail, Faizul Rizal; Hesse, Benjamin; Schramm, Dieter; Maas, Niko; Koppers, Martin; Nuawi, Mohd Zaki; Deros, Baba Md · 2016 · Jurnal Teknologi (UTM Press, free-to-read)

DOI: 10.11113/jt.v78.9143

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This preliminary study investigates the suitability of heart rate (HR) recording as a physiological tool for detecting driver performance impairment and reduced alertness. Motivated by the significant role of driver fatigue in road accidents, the research aims to evaluate whether continuous HR monitoring can effectively identify mental fatigue and workload during monotonous driving tasks. The study specifically examines the impact of whole-body vibration on driver state, comparing conditions with and without vibration to determine if HR serves as a reliable indicator of physiological adaptation and effort intensity. The experimental design involved three healthy male subjects (ages 27, 32, and 40) performing one-hour driving simulations in a controlled laboratory environment. Each subject completed two sessions: one without vibration (WOV) and one with vibration (5 mm amplitude, 5–10 Hz frequency). The simulation featured a monotonous highway scenario with low traffic demand, requiring only lane keeping at speeds between 80–90 km/h to induce task monotony. HR data was recorded continuously using Wahoo Fitness TICKR sensors for 30 minutes pre-driving, one hour during driving, and 30 minutes post-driving. Baseline measurements were established using HR data from the subjects’ daily routines. Driver state was assessed subjectively using the Karolinska Sleepiness Scale (KSS) and objectively through Variation of Lane Deviation (VLD) and speed recordings. Results indicated that all subjects experienced increased sleepiness during the driving task, as reflected by higher KSS scores and observed behaviors such as yawning. In the WOV condition, HR decreased from start to finish for all subjects, correlating with reduced alertness. Conversely, in the vibration condition, HR responses varied; only one subject showed a decrease, while the others exhibited an increase, potentially due to individual physical conditions or vibration-induced stress. Performance analysis revealed that subjects tended to cross lanes, indicating reduced focus, though average speed remained controlled. Crucially, the study found no strong correlation between HR and VLD or speed. However, a good correlation was observed between HR and KSS scores, where lower HR at the end of the journey corresponded with subjective reports of sleepiness and reduced alertness. The study concludes that HR is a useful, cost-effective, and easily monitored indicator for detecting driver fatigue and physiological adaptation, particularly when integrated with subjective evaluations like KSS. While HR did not strongly correlate with objective performance metrics like lane deviation in this small sample, its alignment with subjective sleepiness suggests potential for real-time fatigue detection systems. The authors acknowledge limitations, including the small sample size and lack of control over caffeine and food intake, which may have influenced results. Future research should address these confounding variables to further validate HR as a robust tool for ergonomic interventions and fatigue management in driving contexts.

Key finding

In a controlled simulator drive of three subjects, mean HR fell over the one-hour monotonous task while KSS sleepiness rose, with concurrent increases in lane deviation — supporting HR as a feasible, non-intrusive correlate of driver fatigue and reduced alertness, especially in low-stimulation (no-vibration) driving.

Methodology

lab_experiment

Sample size: 3

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via doi_resolver on 2026-05-07 (5 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified_with_issues.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• drowsiness detection algorithms
• workload measurement
• drowsiness
• time on task
• stress driving

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: physiological data
• Methodological Resource: validation psychometrics, tool software