Evaluating the effectiveness of camera-based fatigue and distraction detection technology in a rural truck driver cohort.

Journal of occupational and environmental medicine Pub Date : 2025-02-20 DOI:10.1097/JOM.0000000000003350

Jennifer Cori, Lauren A Booker, Tracey L Sletten, Shantha M W Rajaratnam, David Stanley, Liam Francis, Kayla McMahon, Kyle Wilson, Meghan Mulhall, Mark E Howard

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Abstract

Objective: This study aims to evaluate the effectiveness of fatigue detection technology (FDT) cabin alarms in reducing fatigue events in rural truck drivers, assess the accuracy in detecting fatigue events alarms and examine whether drivers habituate to alarms over time.

Methods: Longitudinal naturalistic study of fatigue events before and after alarm activation.in 12 rural commercial trucks.

Results: The rate showed fatigue events were significantly higher when alarms were off (0.06), compared to when alarms were activated (0.03) (rate-ratio = 0.5 [0.4, 0.7], p < 0.001). Fatigue events increased as the alarm phase continued, indicating habituation. The device classified fatigue events with 49% precision, 32% were false positives and 18% reclassified as distraction when human verified.

Conclusion: In cabin fatigue alarms significantly reduced the rate of fatigue events initially, however increased again overtime.

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研究目的本研究旨在评估疲劳检测技术（FDT）驾驶室警报器在减少农村卡车司机疲劳事件方面的效果，评估疲劳事件警报器检测的准确性，并研究司机是否会随着时间的推移习惯于警报器：方法：在 12 辆农村商用卡车上对警报启动前后的疲劳事件进行纵向自然研究：结果：警报关闭时的疲劳事件发生率（0.06）明显高于警报启动时的疲劳事件发生率（0.03）（比率比 = 0.5 [0.4, 0.7]，p < 0.001）。疲劳事件随着警报阶段的持续而增加，这表明已形成习惯。该设备对疲劳事件的分类准确率为 49%，32% 为假阳性，18% 在人工验证后被重新归类为分心：机舱内的疲劳警报最初能明显降低疲劳事件的发生率，但随着时间的推移又会增加。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Journal of occupational and environmental medicine

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