New Methods to assess social, cognitive, and physical function in older persons

评估老年人社交、认知和身体功能的新方法

• 批准号: 7666047
• 负责人: THOMAS ANDREW GLASS
• 金额: $ 29.74万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-30 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7666047
• 关键词: Acoustics; Activities of Daily Living; Adopted; Aging; Area; Baltimore; Blood Pressure; Caring; Clinic; Cognitive; Cohort Studies; Communities; Complex; Data; Data Analyses; Data Collection; Devices; Dimensions; Elderly; Engineering; Environment; Environmental Risk Factor; Evolution; Gerontology; Glass; Goals; Health Policy; Home environment; Human; Laboratories; Language; Life; Location; Measurement; Measures; Memory; Mental Health; Methods; Metric; Monitor; Motion; Movement; Neighborhoods; Outcome Measure; Participant; Patient Self-Report; Pattern; Performance; Performance at work; Persons; Phase; Physical Function; Physical assessment; Population Study; Public Health Schools; Research; Research Personnel; Resources; Respondent; Sampling; Schools; Self Care; Services; Simulate; Social Environment; Social Impacts; Social Interaction; Societies; Speech; Speed; Statistical Methods; System; Talents; Task Performances; Techniques; Technology; Testing; Time; Treatment Effectiveness; United States National Institutes of Health; Walking; Woman; Writing; base; cognitive function; design; digital; functional disability; functional status; improved; infancy; innovation; instrument; light weight; monitoring device; multidisciplinary; novel; novel strategies; performance tests; population health; programs; psychologic; response; sensor; simulation; social; sound; speech processing; speech recognition; tool

DESCRIPTION (provided by investigator): The aim of this 4-year project is to develop and test a new personal monitoring device to measure physical, social and cognitive functioning in continuous time and in real life settings. The proposed device, called the LIFEmeter, combines four technologies: accelerometry (motion sensors), digital audio recording (for capturing speech), automatic speech recognition (for fast efficient analysis of speech), and location identification (to explore environmental influences on function). This light-weight, compact, and wearable device will be tested and validated in three phases of data collection. We will also construct the first automatic speech recognition (ASR) system designed to transcribe and analyze the natural speech of older adults. New metrics and methods will be developed to analyze complex time-embedded data on functioning. The proposed system will overcome biases and limitations found in current self-report techniques. Our team combines expertise from the MIT Media Lab (sensors and wearable computing), the JHU Center for Language and Speech Processing (ASR) and the Bloomberg School of Public Health, which is uniquely able to deliver an innovative approach to measuring complex function with potentially broad applicability. The proposed research builds on a previous 5-year cohort study (The Baltimore Memory Study, AG19604) of community-dwelling older adults. Existing data from this study allow us to compare and validate measures of function obtained from our new device against a range of self-reported and clinically-measured outcomes. We will also validate our instrument against the most widely used accelerometer (called ActiGraph). Data gathered using our new device will allow us to study of the impact of the built and social environment on functioning with improved precision. .A key goal will also be to create and disseminate tools that allow other investigators to adopt, refine and test this new approach. RELEVANCE: Accurate and reliable assessment of physical, social and cognitive functioning is the most important measurement challenge in gerontology. Effective health policy for an aging society requires the ability to determine who is able to live independently and who requires care. Current approaches rely on patient self-reports or lab-based tests which are known to be problematic. Improved measurement tools will allow for better testing of the effectiveness of treatments and services, as well as greater accuracy in population health monitoring. The proposed research is responsive to NIH PA-05-090 and to objectives laid out in the NIH roadmap.

描述（调查员提供）：这个4年项目的目的是开发和测试一种新的个人监测设备，以在连续的时间和现实生活中衡量身体，社会和认知功能。所提出的称为生命值的设备结合了四种技术：加速度计（运动传感器），数字音频记录（用于捕获语音），自动语音识别（用于对语音的快速分析）和位置识别（探索环境对功能的影响）。这种轻巧，紧凑和可穿戴设备将在数据收集的三个阶段进行测试和验证。我们还将构建旨在转录和分析老年人自然语音的第一个自动语音识别（ASR）系统。将开发新的指标和方法来分析复杂的时间安装功能的数据。提出的系统将克服当前自我报告技术中发现的偏见和局限性。我们的团队结合了麻省理工学院媒体实验室（传感器和可穿戴计算），JHU语言和语音处理中心（ASR）和彭博公共卫生学院的专业知识，该学院具有独特的能力，能够提供具有潜在广泛适用性的复杂功能的创新方法。拟议的研究基于一项对社区居民老年人的前5年队列研究（巴尔的摩记忆研究，AG19604）。这项研究的现有数据使我们能够比较和验证从我们的新设备获得的功能度量与一系列自我报告和临床测量的结果。我们还将验证我们的仪器使用最广泛使用的加速度计（称为Actigraph）。使用我们的新设备收集的数据将使我们能够以提高的精度研究建筑和社交环境对功能的影响。 。一个关键目标还将是创建和传播工具，使其他研究人员能够采用，完善和测试这种新方法。相关性：对身体，社会和认知功能的准确评估是老年学中最重要的测量挑战。老龄化社会的有效卫生政策需要确定谁能够独立生活和需要照顾的能力。当前的方法依赖于已知存在问题的患者自我报告或基于实验室的测试。改进的测量工具将可以更好地测试治疗和服务的有效性，以及在人口健康监测中的准确性。拟议的研究对NIH PA-05-090响应，并对在NIH路线图中提出的目标响应。