Study protocol for “In-vehicle sensors to detect changes in cognition of older drivers”

Author:

Tappen Ruth,Newman David,Rosselli Monica,Jang Jinwoo,Furht Borko,Yang KwangSoo,Ghoreishi Seyedeh Gol Ara,Zhai Jiannan,Conniff Joshua,Jan Muhammad Tanveer,Moshfeghi Sonia,Panday Somi,Jackson Kelley,Adonis-Rizzo Marie

Abstract

Abstract Background Driving is a complex behavior that may be affected by early changes in the cognition of older individuals. Early changes in driving behavior may include driving more slowly, making fewer and shorter trips, and errors related to inadequate anticipation of situations. Sensor systems installed in older drivers’ vehicles may detect these changes and may generate early warnings of possible changes in cognition. Method A naturalistic longitudinal design is employed to obtain continuous information on driving behavior that will be compared with the results of extensive cognitive testing conducted every 3 months for 3 years. A driver facing camera, forward facing camera, and telematics unit are installed in the vehicle and data downloaded every 3 months when the cognitive tests are administered. Results Data processing and analysis will proceed through a series of steps including data normalization, adding information on external factors (weather, traffic conditions), and identifying critical features (variables). Traditional prediction modeling results will be compared with Recurring Neural Network (RNN) approach to produce Driver Behavior Indices (DBIs), and algorithms to classify drivers within age, gender, ethnic group membership, and other potential group characteristics. Conclusion It is well established that individuals with progressive dementias are eventually unable to drive safely, yet many remain unaware of their cognitive decrements. Current screening and evaluation services can test only a small number of individuals with cognitive concerns, missing many who need to know if they require treatment. Given the increasing number of sensors being installed in passenger vehicles and pick-up trucks and their increasing acceptability, reconfigured in-vehicle sensing systems could provide widespread, low-cost early warnings of cognitive decline to the large number of older drivers on the road in the U.S. 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 cognitive change for this large number of older drivers in the U.S. and elsewhere.

Funder

National Institutes of Health (NIH), National Institute on Aging

Publisher

Springer Science and Business Media LLC

Subject

Geriatrics and Gerontology

Reference50 articles.

1. Rajan KB, Weuve J, Barnes LL, McAninch EA, Wilson RS, Evans DA. Population estimate of people with clinical Alzheimer’s disease and mild cognitive impairment in the United States (2020–2060). U.S. National Library of Medicine. Available from: https://pubmed.ncbi.nlm.nih.gov/34043283/. Cited 2023 Sept 6.

2. Aita SL, Beach JD, Taylor SE, Borgogna NC, Harrell MN, Hill BD. Alzheimer’s disease facts and figures. 2022. Available from: https://www.alz.org/alzheimers-dementia/facts-figures. Cited 2023 Sept 6.

3. Ott BR, Jones RN, Noto RB, Yoo DC, Snyder PJ, Bernier JN, et al. Brain amyloid in preclinical Alzheimer’s disease is associated with increased driving risk. U.S. National Library of Medicine; 2016. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5318288/. Cited 2023 Sept 6.

4. Meuleners LB, Stevenson M, Chow K, Ng J. Motor vehicle crashes and dementia: a population-based study. U.S. National Library of Medicine; 2016. Available from: https://pubmed.ncbi.nlm.nih.gov/27171906/. Cited 2023 Sept 6.

5. Chee JN, Rapoport MJ, Molnar F, Herrmann N, O’Neill D, Marottoli R, Mitchell S, Tant M, Dow J, Ayotte D, Lanctôt KL, McFadden R, Taylor JP, Donaghy PC, Olsen K, Classen S, Elzohairy Y, Carr DB. Update on the risk of motor vehicle collision or driving impairment with dementia: a collaborative international systematic review and meta-analysis. U.S. National Library of Medicine; 2017. Available from: https://pubmed.ncbi.nlm.nih.gov/28917504/. Cited 2023 Sept 6.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3