In-Vehicle Sensors to Detect Cognitive Change in Older Drivers

车载传感器检测老年驾驶员的认知变化

• 批准号: 10624471
• 负责人: David Newman
• 金额: $ 4.41万
• 依托单位: FLORIDA ATLANTIC UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10624471
• 关键词: Activities of Daily Living; Age; Aging; Algorithms; Alzheimer' s Disease; American; Automobile Driving; Awareness; Behavior; Brain; Chronic; Clinical; Cognition; Cognitive; Complex; Computer software; Custom; Data; Databases; Dementia; Detection; Diagnostic; Disease Progression; Early Diagnosis; Elderly; Emotional; Enrollment; Evaluation; Exhibits; Family; Future; Gender; Goals; Government; Grouping; Impaired cognition; Individual; Language; Measurable; Measurement; Measures; Medical; Medicare; Memory; Methods; Modernization; Monitor; Output; Participant; Performance; Persons; Public Health; Reporting; Research; Research Project Grants; Risk; Safety; Services; Societies; Symptoms; System; Techniques; Technology; Testing; Time; Translating; Vehicle crash; Visit; Visual attention; Visuospatial; Weather; cognitive change; cognitive function; cognitive testing; cost; distracted driving; distraction; driving behavior; executive function; experience; human old age (65+); indexing; innovation; interest; mild cognitive impairment; older driver; open source; recruit; response; screening; screening program; sensor; willingness

Project Summary / Abstract Brain changes associated with Alzheimer's disease and related chronic degenerative dementias may begin as long as 20 years before clinical symptoms become evident. There is increasing evidence that unobtrusive monitoring of older adults' performance of complex daily activities of living may allow us to detect some of these subtle early changes in cognition. The rapidly increasing use of sensors not only in commercial vehicles, but also in passenger vehicles, and large number of older drivers on U.S. roads suggest that sensor data may be reconfigured to provide this early warning system. In this longitudinal mixed methods study, we will recruit and enroll 750 older drivers, establish their baseline cognitive function and driving behavior profiles, and repeat the cognitive testing and in-vehicle sensor data downloading every three months for three years (12 data points). Over this time, we expect approximately 200 participants to have experienced measurable cognitive decline either from unimpaired to mild cognitive impairment levels and/or mild cognitive impairment to early stage dementia levels. We propose to install a sensor system which will include unobtrusive cameras, on-board diagnostics (OBD), GPS and inertial measurement units (IMU) configured to track and record driver behavior in the passenger vehicles of these 750 older adult (≥ 65) drivers. The recorded changes in driver behavior will be compared to results from a battery of cognitive tests (global cognition, executive function, memory, visuospatial, visual attention and language) with demonstrated ability to detect early cognitive changes and to predict driver risk. The innovation of this research project lies in the rigorous testing of an unobtrusive, rapidly and readily available in-vehicle sensing and monitoring system for its ability to detect early changes in cognition in older drivers. There is an estimated 4 to 8 million older drivers with mild cognitive impairment on the roads in the U.S. This significant number of older drivers poses a major concern for public safety. Moreover, the majority may be unaware of the cognitive changes occurring. Current dementia screening programs are able to test only a small number of older adults and the wellness visits covered by Medicare do not detect these early, subtle changes. Yet early detection offers many medical, emotional and financial benefits for the individual, family and society, opening a “window of time” to intervene in the progression of the disease in the future (Alzheimer's Association 2019 Report). The proposed testing and evaluation of a readily and rapidly available, unobtrusive in-vehicle sensing system could provide the first step toward future widespread, low-cost, early warnings of change for the large number of older drivers in the U.S.

项目概要/摘要 与阿尔茨海默病和相关的慢性退行性痴呆相关的大脑变化可能 越来越多的证据表明，在临床症状显现之前长达 20 年。 对老年人复杂的日常生活活动的表现进行不引人注目的监测可能使我们能够发现 其中一些微妙的早期认知变化不仅在商业领域，而且传感器的使用迅速增加。 车辆，以及乘用车，以及美国道路上的大量老年驾驶员表明传感器 在这项纵向混合方法研究中，我们可以重新配置数据以提供这种预警系统。 将招募和登记 750 名老年驾驶员，建立他们的基线认知功能和驾驶行为 配置文件，并每三个月重复一次认知测试和车载传感器数据下载，持续三个月 年（12 个数据点），我们预计大约有 200 名参与者经历过。 可测量的认知能力下降，从未受损到轻度认知障碍水平和/或轻度 我们建议安装一个传感器系统，其中包括早期痴呆症的认知障碍。 不显眼的摄像头、车载诊断 (OBD)、GPS 和惯性测量单元 (IMU) 配置为 跟踪并记录这 750 名老年（≥ 65 岁）驾驶员在客车中的驾驶员行为。 驾驶员行为的变化将与一系列认知测试（全局认知、 执行功能、记忆力、视觉空间、视觉注意力和语言），具有检测能力 早期认知变化并预测驾驶员风险该研究项目的创新之处在于严谨。 测试不显眼、快速且易于使用的车载传感和监控系统的能力 检测老年驾驶员认知的早期变化 据估计，有 4 至 800 万老年驾驶员患有这种疾病。 美国道路上的轻度认知障碍 大量老年驾驶员构成了一个重大问题 此外，大多数人可能没有意识到当前正在发生的认知变化。 痴呆症筛查计划只能对少数老年人进行测试，并且健康就诊 医疗保险无法检测到这些早期、微妙的变化，但早期检测可以提供许多医疗、 为个人、家庭和社会带来情感和经济利益，打开干预的“时间之窗” 未来疾病的进展（阿尔茨海默病协会 2019 年报告）。 对易于快速使用、不引人注目的车载传感系统进行评估可以提供第一个 朝着未来广泛、低成本、早期预警的方向迈出一步，为大量老年司机提供改变的机会 我们。