Multi-modal cloud based system for detecting early signs of driver cognitive decline and/or high risk driving behaviors

基于多模式云的系统，用于检测驾驶员认知能力下降和/或高风险驾驶行为的早期迹象

• 批准号: 10258737
• 负责人: GOPI N MAGULURI
• 金额: $ 41.64万
• 依托单位: PHYSICAL SCIENCES, INC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10258737
• 关键词: Affect; Age; Alzheimer' s Disease; Alzheimer' s disease related dementia; Attention; Automobile Driving; Automobiles; Behavior; Biological Markers; Brain scan; Caregivers; Clinical; Cognition; Cognitive; Collaborations; Complex; Computer Vision Systems; Computer software; Consultations; Data; Data Analytics; Databases; Derivation procedure; Diagnosis; Elderly; Enrollment; Environment; Evaluation; Event; Exercise; Failure; Goals; Habits; Hand; Heart Rate; Impaired cognition; Individual; Industry; Insurance; Measurement; Measures; Memory; Methods; Michigan; Modality; Monitor; Motor Vehicles; Neuropsychology; Patients; Pattern; Performance; Phase; Physiologic Monitoring; Physiological; Pilot Projects; Positron-Emission Tomography; Preventive measure; Reaction Time; Registries; Research; Risk; Risk Assessment; Safety; Scientist; Signal Transduction; Skin; Software Design; Stress; Surface; System; Techniques; Technology; Testing; Time; Universities; Volunteer Group; Wireless Technology; Young driver; adaptive devices; aged; base; cloud based; complex data; conditioning; data exchange; design; driving behavior; flexibility; hazard; high risk; human subject; impaired driving performance; improved; indexing; insight; minimal risk; motor vehicle injury; multidisciplinary; multimodality; new technology; physical science; programs; risky driving; routine screening; screening; sensor; success; volunteer; wearable sensor technology

Project Summary/Abstract Physical Sciences Inc. (PSI), in collaboration with Michigan State University (MSU) and the University of Michigan (U-M), proposes to develop a novel technology that will non-intrusively monitor driver cognitive decline and/or high-risk driving behavior that is especially suited for seniors (aged >65). Contextual physiological biomarkers along with computer vision based drive quality measurements will be obtained through a cloud-based acquisition system. Real-time risk assessments that are measures of cognitive status will be performed on the cloud to provide comprehensive analysis on drive quality metrics for seniors with varying levels of cognitive impairment. Assessment of a driver’s cognitive status requires the use of a complex monitoring platform that can be seamlessly installed into any automobile without interfering or adding complexity to driving. Therefore, our goal is to develop a cloud-based, multi-modal routine cognitive/drive assessment system that combines a Smart Steering Sleeve (S3), which monitors physiological biomarkers, along with a Computer Vision (CV) system that provides contextual insight for biomarker changes and monitors a driver's habits. The Cloud-based Computer Vision Smart Steering Sleeve (C-CVS3) sensor system will be capable of monitoring biomarkers such as heart rate, hand gripping force, and the presence of excessive sweat from the skin surface indicating stress levels affecting potential drive quality degradation, which are also factors expected to be associated with cognitive impairment during critical events. Dash cameras provide temporal context including reaction times to unexpected hazards in addition to driver’s safety measures, such as staying within the lane, and maintaining distance to surrounding vehicles. The transmitted data to the cloud from both modalities will be used to derive cognitive/drive quality indices (QI) for driving risks that can be associated with increased stress levels, attention deficiency and/or cognitive decline in individuals. This modality will result in an add-on adaptive platform in automobiles that gauges cognitive status/decline providing value to the auto insurance industry, RMV, as well as to the caregivers of the cognitively impaired patient apart from the individual himself to identify a quantifiable parameter before giving up driving or to seek additional cognitive diagnosis. The basic functions of this comprehensive drive monitoring system will be evaluated in Phase I on a number of individuals in a driving simulator. The technology will be improved in Phase II and will be further tested during real-world driving scenarios.

项目摘要/摘要 物理科学公司（PSI），与密歇根州立大学（MSU）和大学合作 密歇根州（U-M），提出了一项新型技术，该技术将非侵入性监控驱动程序认知 特别适合老年人的下降和/或高风险驾驶行为（年龄> 65岁）。上下文 将获得生理生物标志物以及基于计算机的驱动质量测量 通过基于云的采集系统。实时风险评估是认知状况的度量 将在云上进行，以提供有关老年人的驱动质量指标的全面分析 不同水平的认知障碍。 评估驾驶员的认知状况需要使用复杂的监控平台 无缝安装到任何汽车中，而无需干扰或增加驾驶复杂性。因此，我们的目标 是开发基于云的多模式常规认知/驱动器评估系统，该系统结合了一个智能 方向盘（S3），可监视物理生物标志物，以及计算机视觉（CV）系统 为生物标志物变化提供上下文见解，并监视驾驶员的习惯。基于云的计算机 视觉智能转向套筒（C-CVS3）传感器系统将能够监视Heart等生物标志物 速率，手工握力以及从皮肤表面出现过多的汗液表明应力水平 影响潜在的驱动质量降解，这也是预期与认知有关的因素 关键事件中的损害。破折号摄像机提供临时环境，包括 除了驾驶员的安全措施（例如留在车道内）和维护 到周围车辆的距离。从两种方式传输到云的数据将用于得出 认知/驱动质量指数（QI）用于驱动风险，这些风险可能与压力增加相关，注意力 个体的缺乏和/或认知能力下降。这种方式将导致一个附加的自适应平台 衡量认知状况/下降的汽车为汽车保险行业提供价值，RMV 至于认知受损患者的照顾者，除了个人本人以外 放弃驾驶或寻求其他认知诊断之前的参数。 该综合驱动器监控系统的基本功能将在A阶段评估 驾驶模拟器中的个人数量。该技术将在第二阶段改进，将进一步 在现实世界驾驶场景中进行了测试。