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: 10045777
• 负责人: David Newman
• 金额: $ 142.15万
• 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/10045777
• 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; Public Health; Reporting; Research; Research Project Grants; Risk; Safety; Services; Societies; Symptoms; System; Techniques; Technology; Testing; Time; Translating; 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.

项目摘要/摘要 与阿尔茨海默病和相关的慢性退行性痴呆相关的脑变化可能 在临床症状显现之前长达20年的时间就开始了。越来越多的证据表明 对老年人在复杂日常生活活动中的表现进行不引人注目的监测，可能会让我们发现 其中一些是认知上的早期细微变化。传感器的快速使用不仅在商业上 车辆，也包括乘用车，以及美国道路上的大量老年司机表明，传感器 可以对数据进行重新配置，以提供该早期预警系统。在这项纵向混合方法研究中，我们 将招募和登记750名年长司机，建立他们的基线认知功能和驾驶行为 配置文件，并重复认知测试和车载传感器数据下载，每三个月 年(12个数据点)。在这段时间里，我们预计大约有200名参与者经历了 可测量的认知功能下降，从未受损到轻度认知障碍和/或轻度 认知障碍达到早期痴呆症水平。我们建议安装一个传感器系统，这将包括 不显眼的摄像头、车载诊断(OBD)、GPS和惯性测量单元(IMU) 跟踪和记录这750名老年(≥65)司机在乘用车中的司机行为。录制的 驾驶员行为的变化将与一系列认知测试的结果进行比较(全球认知， 执行功能、记忆、视觉空间、视觉注意力和语言)具有被证明的检测能力 早期认知变化和预测司机风险。本研究项目的创新之处在于严谨 测试隐蔽、快速和容易获得的车载传感和监控系统的能力 以检测老年司机认知的早期变化。据估计，有400万至800万年长司机患有 美国道路上的轻度认知障碍。这一数量可观的老年司机构成了主要的 对公共安全的关注。此外，大多数人可能没有意识到正在发生的认知变化。当前 痴呆症筛查计划只能测试一小部分老年人和健康探视 联邦医疗保险覆盖的人不会检测到这些早期的、细微的变化。然而，早期发现提供了许多医学上的， 为个人、家庭和社会带来情感和经济利益，为干预打开了一扇“时间之窗” (阿尔茨海默氏症协会2019年报告)。建议的测试 对容易、快速、不显眼的车载传感系统的评估可以提供第一个 迈向未来广泛的、低成本的、针对大量老年司机变化的早期警告 美国