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非侵入式嗜睡检测技术及其在老年驾驶员早期痴呆症检测中的应用

NON-INTRUSIVE DROWSINESS DETECTION TECHNIQUES AND THEIR APPLICATION IN DETECTING EARLY DEMENTIA IN OLDER DRIVERS.

作者信息

Jan Muhammad Tanveer, Hashemi Ali, Jang Jinwoo, Yang Kwangsoo, Zhai Jiannan, Newman David, Tappen Ruth, Furht Borko

机构信息

College of Engineering and Computer Science, Florida Atlantic University, Boca Raton FL 33431 USA.

Christine E. Lynn College of Nursing , Florida Atlantic University, Boca Raton FL 33431 USA.

出版信息

Proc Future Technol Conf Vol 2 (2022). 2023;560(V2):776-796. doi: 10.1007/978-3-031-18458-1_53. Epub 2022 Oct 13.

DOI:10.1007/978-3-031-18458-1_53
PMID:36972186
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10037317/
Abstract

Drowsy drivers cause the most car accidents thus, adopting an efficient drowsiness detection system can alert the driver promptly and precisely which will reduce the numbers of accidents and also save a lot of money. This paper discusses many tactics and methods for drowsy driving warning. The non-intrusive nature of most of the strategies mentioned and contrasted means both vehicular and behavioural techniques are examined here. Thus, the latest strategies are studied and discussed for both groups, together with their benefits and drawbacks. The goal of this review was to identify a practical and low-cost approach for analysing elder drivers' behaviour.

摘要

疲劳驾驶引发的车祸最多，因此，采用高效的疲劳检测系统可以及时、准确地提醒驾驶员，这将减少事故数量并节省大量资金。本文讨论了许多疲劳驾驶预警的策略和方法。这里研究了大多数所提及和对比策略的非侵入性，这意味着对车辆技术和行为技术都进行了考察。因此，针对这两类技术，研究并讨论了最新的策略及其优缺点。本综述的目的是确定一种实用且低成本的方法来分析老年驾驶员的行为。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e18/10037317/cd6f3cea3569/nihms-1881839-f0013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e18/10037317/d2841d133146/nihms-1881839-f0005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e18/10037317/cd6f3cea3569/nihms-1881839-f0013.jpg

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