Non-Intrusive Automated Portable Data Collection System for Aging Surveys

用于老龄化调查的非侵入式自动便携式数据收集系统

• 批准号: 8450730
• 负责人: Amy Papadopoulos
• 金额: $ 45.08万
• 依托单位: AFRAME DIGITAL, INC.
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-15 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8450730
• 关键词: Accounting; Acute; Address; Adherence; Affect; Aging; Agreement; Area; Beds; Behavior; Behavior Therapy; Blood Pressure; Caregivers; Caring; Centers for Disease Control and Prevention (U.S.); Charge; Chronic; Chronic Disease; Congestive Heart Failure; Data; Data Collection; Dementia; Devices; Diabetes Mellitus; Diet and Nutrition; Disease; Early Intervention; Economics; Effectiveness; Elderly; Evaluation; Health; Health Personnel; Health Policy; Healthcare; Household; Human; Hypertension; Individual; Institutes; Insurance Carriers; Intervention; Learning; Location; Measures; Monitor; Nurses; Pain; Participant; Patient Self-Report; Patients; Pattern; Phase; Physical Function; Physicians; Physiological; Play; Population; Reporting; Research Personnel; Sampling; Sleep; Stress; Survey Methodology; Surveys; System; Time; United States; Visiting Nurse; Weight; Wireless Technology; Wrist; aged; base; care burden; cost; data collection methodology; falls; instrument; interest; phase 2 study; population based; population survey; sample collection; sensor; touchscreen

DESCRIPTION (provided by applicant): As the percentage of the U.S. population aged 65 and older grows from the 12.9 percent reported in 2009 to the estimated 19 percent projected in 20301, it is becoming increasingly important that the many factors affecting the health and well being of this portion of the population are understood and addressed. Methods of surveying this population and gathering longitudinal data regarding aspects of their lives, such as activity level sleep patterns, physiological data, and behavior patterns are needed and have been highlighted as an area of interest by the National Institute of Aging. Such data are not only useful to academic researchers, but to insurers, health care providers, health and health policy analysts and, on a more intimate level, by caregivers. However, cost and adherence play key roles in the ability to collect such data, so an easy-to-use, low-cost automatic data collection system is required; one which can and will be utilized by the elderly on a regular basis and which is capable of capturing a wide range of key health indicators. This Phase II application aims to demonstrate the effectiveness of a portable and real-time survey system capable of collecting activity level, location, and sleep patterns on a continual basis from a wrist-based device in a watch form factor, as well as physiological data such as blood pressure and weight from easy-to-use wireless devices, and self-reported data from easy, touch-screen interfaces regarding a number of varying topics including pain level, diet and nutrition, or stress. The application aims to prove the following hypothesis: The proposed monitoring system provides an effective means of collecting real-time survey data (including physiological, activity, sleep, and self- report dat) from elderly individuals for an extended period of time and is capable of recognizing deviations from individualized baseline norms that could be indicative of illness or need for intervention. During the study, 30 reasonably healthy elderly individuals and 60 elderly individuals with congestive heart failure (CHF) will be monitored over six months, during which a number of episodes of acute CHF exacerbation are expected to occur; the system will learn to recognize and alert upon such episodes. CHF was chosen so that the effectiveness of the system in flagging deviations from an individual's system-learned baseline could be better demonstrated. All study participants will be monitored by a visiting nurse/physician once each week. Moreover, 30 of the CHF participants and the 30 other participants will also be monitored using the proposed system configured to provide real-time data to the nurse in charge of each participant. The specific aims of the project will be to establish that: 1) the platform can and will be used by an elderly population for an extended (six-month) period of time, 2) the watch device is effective for collecting longitudinal sleep and activity data, and 3) the system is effective in providing useful survey data to monitoring nurses while reducing the burden of care.

描述（由申请人提供）：随着美国 65 岁及以上人口的比例从 2009 年报告的 12.9% 增长到 20301 年预计的 19%，了解和解决影响这部分人口健康和福祉的许多因素变得越来越重要。需要对这一人群进行调查并收集有关他们生活各方面的纵向数据（例如活动水平、睡眠模式、生理数据和行为模式）的方法，并且已被国家老龄化研究所强调为一个感兴趣的领域。这些数据不仅对学术研究人员有用，而且对保险公司、医疗保健提供者、健康和卫生政策分析师以及更亲密的护理人员有用。然而，成本和依从性对于收集此类数据的能力起着关键作用，因此需要一种易于使用、低成本的自动数据收集系统；一种可以并且将会被老年人定期使用的工具，并且能够捕获广泛的关键健康指标。该第二阶段应用旨在展示便携式实时调查系统的有效性，该系统能够从手表形状的腕式设备连续收集活动水平、位置和睡眠模式，以及来自易于使用的无线设备的血压和体重等生理数据，以及来自简单的触摸屏界面的关于许多不同主题（包括疼痛程度、饮食和营养或压力）的自我报告数据。该应用旨在证明以下假设：所提出的监测系统提供了一种有效的方法，可以长时间收集老年人的实时调查数据（包括生理、活动、睡眠和自我报告数据），并且能够识别可能表明疾病或需要干预的个体化基线规范的偏差。研究期间，将对 30 名相当健康的老年人和 60 名患有充血性心力衰竭 (CHF) 的老年人进行为期六个月的监测，在此期间预计会发生多次 CHF 急性加重；系统将学会识别此类事件并发出警报。选择 CHF 是为了更好地证明系统在标记与个人系统学习基线的偏差方面的有效性。所有研究参与者将由上门护士/医生每周进行一次监测。此外，还将使用所提议的系统对 30 名 CHF 参与者和其他 30 名参与者进行监控，该系统配置为向负责每个参与者的护士提供实时数据。该项目的具体目标是确定： 1) 该平台可以并且将会被使用 长时间（六个月）的老年人口，2）手表设备可有效收集纵向睡眠和活动数据，3）该系统可有效为监测护士提供有用的调查数据，同时减轻护理负担。