Predicting Intoxication Using Motorcycle and Head Movements of Riders Wearing Alcohol Intoxication Goggles

IF 1.8 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Safety Pub Date : 2023-04-29 DOI:10.3390/safety9020029
R. Seva, Imanuel Luir del del Rosario, Lorenzo Miguel Peñafiel, John Michael Young, E. Sybingco
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引用次数: 0

Abstract

The movement of a motorcycle is one of the critical factors that influences the stability of the ride. It has been established that the gait patterns of drunk and sober people are distinct. However, drunk motorcycle (MC) drivers’ balance has not been investigated as a predictor of intoxication. This paper characterized and used MC and head movements, such as pitch and roll, to predict intoxication while riding. Two separate experiments were conducted to monitor MC and head movement. Male participants were recruited between the ages of 23 and 50 to participate in the study. Participants used alcohol intoxication goggles (AIG) to simulate blood alcohol content (BAC) while driving on a straight path. Placebo goggles were used for control. Results showed that pitch and roll amplitudes of the MC could distinguish drivers wearing placebo and AIGs, as well as the pitch and roll frequency of the head. Deep learning can be used to predict the intoxication of MC riders. The predictive accuracy of the algorithm shows a viable opportunity for the use of movement to monitor drunk riders on the road.
摩托车中毒预测及佩戴酒精中毒护目镜的驾驶员头部运动
摩托车的运动是影响其行驶稳定性的关键因素之一。已经确定的是,醉酒和清醒的人的步态模式是不同的。然而,醉酒摩托车(MC)司机的平衡尚未被研究作为中毒的预测因素。本文描述并使用MC和头部运动,如俯仰和翻滚,来预测骑时的中毒。进行了两个独立的实验来监测MC和头部运动。研究招募了年龄在23岁到50岁之间的男性参与者。参与者使用酒精中毒护目镜(AIG)模拟在直线道路上驾驶时血液中的酒精含量(BAC)。对照组使用安慰剂护目镜。结果表明,MC的俯仰和侧倾幅度以及头部的俯仰和侧倾频率可以区分佩戴安慰剂和AIGs的驾驶员。深度学习可以用来预测MC骑手的醉酒程度。该算法的预测准确性表明,利用运动来监控道路上的醉酒车手是可行的。
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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来源期刊
Safety
Safety Social Sciences-Safety Research
CiteScore
3.20
自引率
5.30%
发文量
71
审稿时长
7 weeks
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