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: 10254018
• 负责人: Suneel Ismail Sheikh
• 金额: $ 44.91万
• 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 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10254018
• 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; Communication; 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 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; 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 在这个快速轨道SBIR项目中，Aster Labs将解决紧急，直接的，可访问的需求，并且 准确的接触跟踪以帮助管理长期护理机构中传染病暴发的管理 阿尔茨海默氏病和相关痴呆症患者。 2020年估计有580万美国人与 阿尔茨海默氏症的痴呆症以及几乎一半的护士住宅和其他长期护理居民已经 被诊断出患有痴呆症的形式。在这些护理环境中，传染病管理的挑战是 通过患者，看护人，员工和访客之间的经常互动以及更高的风险来增加 由于年龄和潜在的健康状况而引起的传染。 19009大流行只会加剧 由于较早对病毒的敏感性而引起的问题。联系跟踪以识别，测试和隔离那些 传统上，可能已经接触到一个受感染的人是一个手动劳动密集型的过程。许多 护理机构缺乏财务，人力和后勤资源，无法跟踪足够的细节来追溯运动。 特别是对于痴呆症患者，对最近事件和互动的回忆有限，无法做出反应 追踪问题，并潜在的不信任示踪剂风险不准确的数据。投资人力资源 执行接触跟踪是昂贵的，并且临时追踪可以限制有效的结果。现有方法 自动接触跟踪主要是智能手机软件应用程序，由于缺乏 隐私保护以及在长期护理环境中，手机使用的保证是有限的。少数 护理设施的可用解决方案依赖于由于不熟悉的非扫带可穿戴设备 痴呆症患者无法接受，并且通常需要大量的基础设施增加范围限制。 因此，通过提供一个不引人注目的，on-on-on- 需求，准确和自动接触跟踪解决方案在室内和室外工作，几乎没有 基础设施要求，并满足痴呆症患者的特殊需求。 Aster Labs的 建议的激活轨道系统利用WiFi，GPS，Cellular和惯性传感器数据的智能处理 从隐藏在鞋鞋垫上的小型硬件套件中，对佩戴者无法说明，可以实现高 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 第一阶段，原型系统将组装，并通过确定可行性来证明可行性 设备在定时运动实验中的位置和临时准确性，并通过焦点小组研究 与高级护理环境中的联系示踪剂和护理人员。第一阶段测试将为成功标准 第二阶段计划的开始。在第二阶段，前制作的鞋垫和综合软件 应用程序将组装，并在研究中与研究参与者一起评估的集成系统 鞋垫，以及同盟目标。通过训练的接触示踪剂手动完成的结果比较 在多种计划的方案中，自动化的激活trace解决方案将确定系统的效率。