New methods assess social, cognitive, physical function

新方法评估社交、认知、身体功能

• 批准号: 7145304
• 负责人: THOMAS ANDREW GLASS
• 金额: $ 31.22万
• 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 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7145304
• 关键词: actigraphy; aging; behavioral /social science research tag; bioengineering /biomedical engineering; biomedical equipment development; clinical research; cognition; computer assisted medical decision making; functional ability; geriatrics; human ecology; human middle age (35-64); human old age (65+); human subject; patient monitoring device; portable biomedical equipment; psychological aspect of aging; questionnaires; social behavior; socioenvironment; speech recognition; telemedicine

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（由研究者提供）：这个为期 4 年的项目的目的是开发和测试一种新的个人监测设备，以在现实生活环境中连续测量身体、社交和认知功能。所提出的设备称为 LIFEmeter，结合了四种技术：加速度测量（运动传感器）、数字音频记录（用于捕获语音）、自动语音识别（用于快速有效地分析语音）和位置识别（用于探索环境对功能的影响） 。这种轻质、紧凑的可穿戴设备将在数据收集的三个阶段进行测试和验证。我们还将构建第一个自动语音识别（ASR）系统，旨在转录和分析老年人的自然语音。将开发新的指标和方法来分析复杂的嵌入时间的功能数据。所提出的系统将克服当前自我报告技术中存在的偏见和限制。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，能够提供一种独特的创新方法来测量复杂功能，并具有潜在的潜力。广泛的适用性。拟议的研究建立在之前一项针对社区老年人的为期 5 年的队列研究（巴尔的摩记忆研究，AG19604）的基础上。这项研究的现有数据使我们能够将新设备获得的功能测量值与一系列自我报告和临床测量的结果进行比较和验证。我们还将根据最广泛使用的加速度计（称为 ActiGraph）来验证我们的仪器。使用我们的新设备收集的数据将使我们能够更精确地研究建筑和社会环境对功能的影响。一个关键目标还在于创建和传播工具，使其他研究人员能够采用、完善和测试这种新方法。相关性：准确可靠地评估身体、社会和认知功能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能够确定谁能够独立生活以及谁需要护理。目前的方法依赖于患者的自我报告或基于实验室的测试，已知这些测试是有问题的。改进的测量工具将有助于更好地测试治疗和服务的有效性，并提高人口健康监测的准确性。拟议的研究响应 NIH PA-05-090 和 NIH 路线图中列出的目标。