Jan Muhammad Tanveer, Furht Borko, Moshfeghi Sonia, Jang Jinwoo, Ghoreishi Seyedeh Gol Ara, Boateng Charles, Yang Kwangsoo, Conniff Joshua, Rosselli Monica, Newman David, Tappen Ruth
Department of Electrical Engineering & Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA.
Charles E. Schmidth College of Science, Florida Atlantic University, Boca Raton, FL 33431, USA.
Multimed Tools Appl. 2025 May;84(17):18711-18732. doi: 10.1007/s11042-024-19833-1. Epub 2024 Jul 22.
With the ongoing expansion of the aging population, it is increasingly critical to prioritize the safety of older drivers. The objective of this study is to utilize sensor data in order to detect early indications of impairment, thereby facilitating proactive interventions and enhancing road safety for the elderly. This article provides an overview of the research approach, presents significant results, and analyzes the consequences of utilizing in-vehicle sensors i.e. vision and telematics, to mitigate cognitive decline among elderly drivers; in doing so, it promotes progress in the domains of public health and transportation safety by standardizing the use of such devices to automatically assess the drivers' cognitive functions.
随着老龄人口的不断增加，优先考虑老年驾驶员的安全变得越来越重要。本研究的目的是利用传感器数据来检测损伤的早期迹象，从而促进积极干预并提高老年人的道路安全。本文概述了研究方法，展示了重要成果，并分析了利用车载传感器（即视觉和远程信息处理）来减轻老年驾驶员认知衰退的后果；通过规范此类设备的使用以自动评估驾驶员的认知功能，本文促进了公共卫生和交通安全领域的进展。
