Non-Intrusive Automated Portable Data Collection System for Aging Surveys

描述(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。调查这一人群并收集有关他们生活各方面的纵向数据的方法是必要的，如活动水平、睡眠模式、生理数据和行为模式，并已被国家老龄研究所强调为一个感兴趣的领域。这样的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、健康和健康政策分析师以及更私密的护理人员都很有用。然而，成本和依从性在收集这类数据的能力方面发挥着关键作用，因此需要一个易于使用、低成本的自动数据收集系统；该系统能够并将被老年人定期使用，并且能够捕获各种关键健康指标。这个第二阶段的应用旨在展示便携式实时调查系统的有效性，该系统能够从手表外形尺寸中的手腕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自我报告数据，这些数据涉及多种不同的主题，包括疼痛程度、饮食和营养或压力。该应用程序旨在证明以下假设：拟议的监测系统提供了一种有效的手段，可以在较长一段时间内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)，并能够识别偏离个性化基线标准的情况，这些偏离可能表明疾病或需要干预。在研究期间，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，预计将发生多次急性CHF恶化；该系统将学会识别此类事件并对其保持警惕。选择CHF是为了更好地证明该系统在标记偏离个人的系统学习基线方面的有效性。所有研究参与者将由一名访问护士/医生每周监测一次。此外，30名CHF参与者和30名其他参与者也将使用拟议的系统进行监测，该系统配置为向负责每个参与者的护士提供实时数据。该项目的具体目标将是建立：1)该平台可以并将由 2)该手表装置有效地收集纵向睡眠和活动数据，以及3)该系统有效地向监护护士提供有用的调查数据，同时减轻护理负担。 与公共健康相关：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。调查这一人群并收集有关他们生活的许多方面的纵向数据的方法是必要的，如活动水平、睡眠模式、生理数据和行为模式，并已被国家老龄研究所强调为一个感兴趣的领域。在第二阶段研究期间建议评估的监测系统有望提供一种有效的手段，方便地收集较长一段时间内老年人的实时调查(包括生理、活动、睡眠和自我报告)数据，并自动识别偏离个性化基线标准的情况，表明可能患病或需要干预。

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. PUBLIC HEALTH RELEVANCE: 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 many 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. The monitoring system proposed for evaluation during this Phase II study is expected to provide an effective means of easily collecting real-time survey (including physiological, activity, sleep and self-report) data from elderly individuals for an extended period of time as well as automatically recognize deviations from individualized baseline norms indicating the possibility of illness or need for intervention.