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基于心率的瞌睡监测对自然条件下重型车辆驾驶员不良驾驶事件的影响。

The impact of heart rate-based drowsiness monitoring on adverse driving events in heavy vehicle drivers under naturalistic conditions.

机构信息

Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC, Australia.

Institute for Breathing and Sleep, Department of Respiratory and Sleep Medicine, Austin Health, 145 Studley Road, PO Box 5555, Heidelberg, VIC, Australia.

出版信息

Sleep Health. 2020 Jun;6(3):366-373. doi: 10.1016/j.sleh.2020.03.005. Epub 2020 Apr 25.

DOI:10.1016/j.sleh.2020.03.005
PMID:32340910
Abstract

OBJECTIVES

This study examined the influence of a wrist-worn heart rate drowsiness detection device on heavy vehicle driver safety and sleep and its ability to predict driving events under naturalistic conditions.

DESIGN

Prospective, non-randomized trial.

SETTING

Naturalistic driving in Malaysia.

PARTICIPANTS

Heavy vehicle drivers in Malaysia were assigned to the Device (n = 25) or Control condition (n = 34).

INTERVENTION

Both conditions were monitored for driving events at work over 4-weeks in Phase 1, and 12-weeks in Phase 2. In Phase 1, the Device condition wore the device operated in the silent mode (i.e., no drowsiness alerts) to examine the accuracy of the device in predicting driving events. In Phase 2, the Device condition wore the device in the active mode to examine if drowsiness alerts from the device influenced the rate of driving events (compared to Phase 1).

MEASUREMENTS

All participants were monitored for harsh braking and harsh acceleration driving events and self-reported sleep duration and sleepiness daily.

RESULTS

There was a significant decrease in the rate of harsh braking events (Rate ratio = 0.48, p < 0.05) and a fall in subjective sleepiness (p < 0.05) when the device was operated in the active mode (compared to the silent mode). The device predicted when no driving events were occurring (specificity=98.81%), but had low accuracy in detecting when a driving event did occur (sensitivity=6.25%).

CONCLUSIONS

Including drowsiness detection devices in fatigue management programs appears to alter driver behaviour, improving safety despite the modest accuracy. Longer term studies are required to determine if this change is sustained.

摘要

目的

本研究旨在考察腕戴式心率瞌睡检测设备对重型车辆驾驶员安全和睡眠的影响,以及其在自然驾驶条件下预测驾驶事件的能力。

设计

前瞻性、非随机试验。

地点

马来西亚自然驾驶。

参与者

马来西亚的重型车辆驾驶员被分配到设备(n=25)或对照组(n=34)。

干预措施

在第 1 阶段和第 2 阶段,两组都在工作中监测 4 周和 12 周的驾驶事件。在第 1 阶段,设备组佩戴设备(无声模式运行,即无瞌睡警报)以检查设备预测驾驶事件的准确性。在第 2 阶段,设备组佩戴设备(主动模式)以检查设备的瞌睡警报是否影响驾驶事件的发生率(与第 1 阶段相比)。

测量

所有参与者都监测到急刹车和急加速驾驶事件,并每天自我报告睡眠时长和嗜睡程度。

结果

当设备处于主动模式时,急刹车事件的发生率显著下降(率比=0.48,p<0.05),主观嗜睡程度降低(p<0.05)。当设备处于主动模式时,设备能够预测何时没有驾驶事件发生(特异性=98.81%),但在检测何时发生驾驶事件时准确性较低(敏感性=6.25%)。

结论

在疲劳管理计划中纳入瞌睡检测设备似乎可以改变驾驶员的行为,尽管准确性较低,但提高了安全性。需要进行更长期的研究来确定这种变化是否持续。

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