Automated Contact Tracing System for Rapid High-Accuracy Assessment to Management Dementia Patients and Staff Exposed to Infectious Diseases in Long Term Care Facilities

自动接触者追踪系统，用于对长期护理机构中暴露于传染病的痴呆症患者和工作人员进行快速高精度评估

• 批准号: 10671765
• 负责人: Suneel Ismail Sheikh
• 金额: $ 129.15万
• 依托单位: ASTER LABS, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10671765
• 关键词: 2019-nCoV; Address; Administrator; Affect; Age; Algorithms; Alzheimer' s Disease; Alzheimer' s disease related dementia; American; Back; Behavior; COVID-19; COVID-19 pandemic; Car Phone; Caregivers; Caring; Cellular Phone; Communicable Diseases; Communities; Complex; Computer software; Contact Tracing; Data; Data Storage and Retrieval; Dementia; Devices; Diagnosis; Disease; Disease Management; Disease Outbreaks; Elderly; Electronics; Engineering; Environment; Epidemiology; Evaluation; Event; Exhibits; Exposure to; Florida; Focus Groups; Health; Health care facility; Human; Human Resources; Individual; Infection Control; Infrastructure; Intelligence; Interview; Investments; Laboratories; Lead; Life; Light; Location; Logistics; Long-Term Care; Manuals; Measures; Methods; Modification; Motion; Movement; Nursing Homes; Outcome; Patients; Performance; Persons; Phase; Population; Predisposition; Prevention; Process; Production; Recording of previous events; Reporting; Research; Research Personnel; Research Training; Resources; Retrieval; Risk; Risk Assessment; Route; Safety; Secure; Series; Shoes; Small Business Innovation Research Grant; Specific qualifier value; Symptoms; System; Technology; Testing; Time; Tracer; Training; United States; Universities; Virus; Work; aging in place; base; community living; community setting; comparative; contagion; cost; data access; data communication; data management; design; distrust; efficacy evaluation; efficacy study; experience; experimental study; functional independence; health care settings; healthcare-associated infections; high risk; human study; memory care; operation; patient home care; phase 1 testing; privacy protection; programs; prototype; response; sensor; success; system architecture; tool; vulnerable community; wearable device; web app; web platform

Project Abstract In this Fast-Track SBIR project, ASTER Labs will address an urgent, immediate, need for accessible and accurate contact tracing to aid management of infectious disease outbreaks in long-term care facilities of patients with Alzheimer’s disease and related dementias. An estimated 5.8 million Americans in 2020 live with Alzheimer’s dementia and nearly half of nursing home and other long-term care residents have been diagnosed with a form of dementia. Challenges in infectious disease management in these care settings are increased by frequent interactions between patients, caregivers, staff, and visitors, as well as higher risk from contagion due to age and underlying health conditions. The COVID-19 pandemic has only exacerbated the issue due to the susceptibility of the elderly to the virus. Contact tracing to identify, test, and isolate those who may have been exposed to an infected person has traditionally been a manual, labor-intensive process. Many care facilities lack the financial, human, and logistical resources to track sufficient detail to retrace movements. For dementia patients in particular, limited recall of recent events and interactions, inability to respond to tracing questions, and potential distrust of tracers risk inaccurate data. Investment in human resources to perform contact tracing is costly, and ad hoc tracing can limit effective outcomes. Existing methods to automate contact tracing have largely been smartphone software applications, widely criticized for lack of privacy protection, and in long-term care settings, guarantees on mobile phone use are limited. The few available solutions for care facilities rely on non-discreet wearable devices that, due to unfamiliarity, may be unacceptable to dementia patients, and often require large infrastructure additions with limitations on range. Therefore, there exists a significant unmet need to support care facilities by providing an unobtrusive, on- demand, accurate, and automated contact tracing solution that works both indoors and outdoors with little to no infrastructure requirements, and that addresses the special needs of dementia patients. ASTER Labs’ proposed Activtrace system leverages intelligent processing of WiFi, GPS, cellular, and inertial sensor data from a small hardware suite concealed in a shoe insole, unnoticeable to the wearer, that achieves high- precision location and duration of close-contact encounters in complex indoor and outdoor environments. In Phase I, the prototype system will be assembled, and feasibility will be demonstrated by determining the positional and temporal accuracy of the device in timed motion experiments, and through a focus group study with contact tracers and caregivers in senior care settings. Phase I testing will provide the success criteria for the start of the Phase II program. In Phase II, the pre-production insoles and comprehensive software application will be assembled, and the integrated system evaluated in a study with research actors wearing the insoles, along with confederate targets. Comparisons of results done manually by trained contact tracers and the automated Activtrace solution in multiple planned scenarios will establish the system’s efficacy.

项目摘要 在这个快速通道SBIR项目中，ASTER实验室将解决可访问和 准确的接触者追踪，以帮助管理长期护理机构的传染病暴发 阿尔茨海默病和相关痴呆症患者。据估计，2020年有580万美国人与 阿尔茨海默氏症和近一半的养老院和其他长期护理的居民 被诊断出患有一种痴呆症。在这些护理环境中，传染病管理面临的挑战是 由于患者、护理人员、工作人员和访客之间的频繁互动以及更高的风险 由于年龄和潜在的健康状况而引起的传染病。新冠肺炎的大流行只会加剧 这一问题是由于老年人对该病毒的易感性造成的。联系追踪，以识别、测试和隔离那些 传统上，可能接触到感染者是一个手工、劳动密集型的过程。许多 护理机构缺乏财力、人力和后勤资源来追踪足够的细节来追溯行动。 尤其是痴呆症患者，对最近发生的事件和相互作用的回忆有限，无法对 追踪问题，以及对示踪剂潜在的不信任，都有可能导致数据不准确。在人力资源方面的投资 执行接触者跟踪的成本很高，临时跟踪可能会限制有效的结果。现有方法可用于 自动联系人追踪在很大程度上是智能手机软件应用程序，因缺乏 隐私保护，在长期护理环境中，对手机使用的保障是有限的。为数不多的 护理机构的可用解决方案依赖于非谨慎的可穿戴设备，由于不熟悉，这些设备可能会 痴呆症患者无法接受，通常需要大量增加基础设施，但范围有限。 因此，存在着一个重大的未得到满足的需求，即通过提供一种不引人注目的、关于- 按需、准确、自动化的接触跟踪解决方案，在室内和室外均可工作，几乎不需要 基础设施要求，这解决了痴呆症患者的特殊需求。Aster Labs‘ 建议的ActionTrack系统利用对WiFi、GPS、蜂窝和惯性传感器数据的智能处理 从一个隐藏在鞋垫中的小硬件套件，穿戴者不会注意到，它实现了高性能- 在复杂的室内和室外环境中近距离接触的精确位置和持续时间。在……里面 第一阶段，将组装原型系统，并通过确定 设备在定时运动实验中的位置和时间准确性，以及通过焦点小组研究 在老年护理环境中使用接触追踪器和护理员。第一阶段测试将提供以下成功标准 第二阶段计划的开始。在第二阶段，生产前鞋垫和综合软件 应用程序将被组装，集成系统将在与研究人员一起进行的研究中进行评估 鞋垫，以及邦联目标。由训练有素的接触示踪剂和人工进行的结果的比较 在多个计划场景中的自动活动跟踪解决方案将确立该系统的效能。