Wearable Technology Infrastructure to Enhance Capacity for Real-Time, Online Assessment and Mobility (ROAMM) of Intervening Health Events in Older Adults

可穿戴技术基础设施可增强老年人干预健康事件的实时在线评估和移动性 (ROAMM) 能力

• 批准号: 10586513
• 负责人: Todd Manini
• 金额: $ 70.76万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10586513
• 关键词: Accelerometer; Address; Adherence; Adopted; Adverse event; Advisory Committees; American; Apple watch; Applied Research; Area; Automobile Driving; Behavioral; Capsicum; Charge; Clinical; Cognition; Collaborations; Communities; Data; Data Collection; Data Science; Data Storage and Retrieval; Early Diagnosis; Ecological momentary assessment; Elderly; Ensure; Event; Fatigue; Fees; Florida; Focus Groups; Foundations; Frequencies; Geriatrics; Gerontology; Grant; Health; Heart Rate; Home; Hospitalization; Incidence; Infrastructure; Interview; Licensing; Life; Location; Longitudinal Studies; Longitudinal cohort study; Measurement; Measures; Medical; Modeling; Monitor; Moods; Nature; Online Systems; Outcome; Pain; Participant; Patient Outcomes Assessments; Patients; Pattern; Persons; Phase; Phenotype; Physical Function; Physical activity; Prevention; Quality of life; Recording of previous events; Recovery; Reporting; Research; Research Infrastructure; Research Personnel; Risk; Risk Factors; Safety; Science; Secure; Services; Short-Term Memory; Symptoms; System; Technology; Testing; Time; United States National Institutes of Health; Universities; Voice; Work; advanced analytics; aged; base; cognitive testing; comorbidity; cost effectiveness; data science management; data to knowledge; data visualization; demographics; depressive symptoms; disability; executive function; experience; fall injury; fall risk; falls; focus ultra; graphical user interface; informant; mobile computing; mobile sensor; novel; primary outcome; processing speed; programs; prospective; recruit; response; secondary outcome; sensor; smart watch; therapy design; tool; usability; walking speed; wearable device; week trial

ABSTRACT Older Americans experience approximately 29 million falls and 13 million hospitalizations per year. These intervening health events (IHE - episodic falls, injuries, illnesses, and hospitalizations) are strong precipitants of disability in older adults. Because of their episodic nature, IHEs are extremely difficult to study. Continuous, long-term monitoring with remote capabilities using wearable technology is an ideal solution for capturing information surrounding an IHE and in particular, preceding it. This R21/R33 project aims to develop a sustainable research infrastructure built on the foundation of a smart watch application and server called ROAMM (Real-time Online Assessment and Mobility Monitor). It will offer long-term and continuous connectivity, bidirectional interactivity and remote programming. ROAMM will create a detailed narrative about mobility (activity patterns, walking speed, life space), patient reported outcomes/symptoms (pain, poor mood, fatigue, disability), cognition (working memory, processing speed, and executive functioning) and reports of health events (falls and hospitalizations). The infrastructure is composed of a diverse group of investigators with expertise in mobile technology/data science and applied/medical sciences who will serve in the following cores: Wearable Technology, Phenotyping, Clinical Outcomes, Data Science Management & Quality, and Recruitment, Retention & Compliance. In the R21 phase, we will create the ROAMM framework consisting of the watch application and accompanying server. We will also assess test-retest reliability, convergent validity and participant usability/acceptability. Each year, an Independent Advisory Panel and External Advisory Committee will evaluate milestone-driving activities and our Go/No-Go checkpoints for transitioning to the R33 phase. Work proposed in the R33 phase will showcase the ROAMM infrastructure by conducting a prospective, longitudinal study (range 1.25-2.5 yrs) in 200 community-dwelling persons aged 70+ yrs. This phase will test a field deployable version of ROAMM in real world settings to address the following hypotheses: 1) Pre-event patterns of low mobility, disability, fatigue, pain and depressive mood collected by ROAMM are independent predictors of incident IHE's; 2) IHE's will negatively impact the course of ROAMM measures; and 3) Additional value will be gained for explaining the change variability and recovery trajectories. An exploratory aim will evaluate safety while using ROAMM features and identify predictors of ROAMM adherence using both key-informant interviews and examine demographic and health histories to create boundaries for using ROAMM and other systems like it for long-term, continuous monitoring in research and practice. We will sustain ROAMM by targeting grant opportunities for the wearable technology surge for remote patient interaction, adopting licensing fees, and aligning our services with larger entities to become the go-to place for remote data capture. These activities will create a sustainable infrastructure to ensure research on older adults is keeping pace with the state-of-the-art “smart and connected” health with wearable technology.

抽象的 年龄较大的美国人每年经历了大约2900万的跌倒和1300万个住院。 中间的健康事件（情节性瀑布，伤害，疾病和住院）是强大的造成 由于其发作性质，ihes是极端的，因为他们的偶发性是非常困难的。 使用可穿戴技术具有远程功能的长期监控是捕获的理想解决方案 围绕IHE的信息，尤其是在此之前的R21/R33项目。 可持续研究基础设施建立在智能手表应用程序和服务器的基础上 ROAMM（实时在线评估和移动性显示器）。 连接性，双向交互性和远程编程。 流动性（活动模式，步行速度，寿命），患者报告的结局/症状（疼痛，情绪低落， 疲劳，残疾），认知（工作记忆，处理速度和执行功能）以及报告 健康事件（跌倒和住院）。 具有移动技术/数据科学和应用/医学科学方面的专业知识 核心：可穿戴技术，表型，临床结果，数据科学管理和质量 招聘，保留和编译。 手表应用程序和随附的服务器。 和参与者的可用性/接受性。 委员会将评估里程碑式驾驶活动和我们的GO/No-Go检查站，用于过渡到R33 阶段。 前瞻性，纵向研究（范围1.25-2.5年），在200岁以上的社区居民中 阶段将测试REALD设置中ROAMMM的现场可部署版本，以解决以下假设： 1）低迁移率，残疾，疲劳，疼痛和抑郁情绪的低低移动性，由ROAMM收集的情况是 事件的独立预测因素； 3）将获得额外的价值来解释变异性和恢复轨迹 AIM将在使用ROAMM功能的同时评​​估安全性，并使用两者都确定ROAMM依从性 键入访谈并检查人口统计和历史以创建用于使用的边界 ROAMM和其他类似的系统，用于研究和实践中的长期监测 通过针对远程患者的可穿戴技术激增的赠款机会来维持ROAMM 互动，采用许可费以及使我们的服务与较大实体保持一致 远程数据捕获。 与可穿戴技术的最先进的“智能和连接”健康保持同步。