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A Virtually Supervised Web-Based Home Exercise Technology for Older Adults

针对老年人的虚拟监督的基于网络的家庭锻炼技术

基本信息

批准号：
8726275
负责人：
Joseph T Gwin
金额：
$ 19.79万
依托单位：
BIOSENSICS, LLC
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-01 至 2016-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8726275
关键词：
Address Adherence Adult Age Aging Algorithms Ankle Arizona Balance training Binding Biomechanics Caregivers Clinical Research Communities Computer software Data Dementia Development Diabetes Mellitus Disease E-learning Effectiveness Elderly Elements Engineering Ensure Equilibrium Exercise Fall prevention Feedback Future Gait Goals Guidelines Health Healthcare Systems Hip region structure Home environment Human body Impaired cognition Instruction Interdisciplinary Study Internet Intervention Lower Extremity Mails Measures Methodology Methods Metric Modality Modeling Monitor Motion Motor Movement Neoprene Online Systems Outcome Measure Participant Performance Phase Population Positioning Attribute Process Qualifying Quality of life Randomized Controlled Trials Recruitment Activity Regimen Research Research Personnel Rewards Sample Size Signal Transduction Small Business Innovation Research Grant Solutions Stroke System Target Populations Techniques Technology Text Time Training Training Programs Transportation Universities Vendor Wireless Technology aging population base caregiving commercialization community setting compare effectiveness cost cost effective design evidence base fall risk falls foot functional decline high risk improved improved functioning improved mobility instrument kinematics new technology novel post intervention prevent programs prototype public health relevance rural area sensor signal processing software development strength training time use usability virtual virtual reality web site

项目摘要

DESCRIPTION (provided by applicant): Strength and balance training has been demonstrated to prevent physical decline and falls in older adults. The majority of fall prevention studies have focused on supervised group or home-based exercise interventions utilizing qualified personal. The implementation of these interventions on a community-wide level is limited due to home-bound status because of functional or cognitive decline, care-giving responsibilities, or transportation difficulties. High costs for personal, and lack of group exercie facilities are likewise problematic. A promising and cost-effective approach for tailoring strength and balance exercise to older adults in a community setting is to provide training via the internet. However, interactive web-based home exercise technologies, including virtually supervised training, have not yet been developed. The objective of this collaborative SHIFT SBIR project between BioSensics LLC (Cambridge, MA) and the University of Arizona (Interdisciplinary Consortium on Advance Motion Performance (iCAMP) and Arizona Center on Aging) is to develop a low cost, easy-to-use, interactive web application for home-based strength and balance training to improve mobility and reduce fall risk in older adults. The proposed system will be developed based on an existing non-interactive prototype web-based training program using a virtual on- screen trainer. The new interactive web application will include an on-screen 'user avatar' that mimics its users movements. This will be accomplished by developing an instrumented overshoe containing kinematic sensors. Based on the sensor signals, body segment kinematics (e.g., foot position, ankle angle, and hip angle) will be estimated in real-time using a simplified biomechanical model of the human body. The kinematic data will drive the on-screen user avatar, which will provide real-time feedback to the user regarding their exercise performance. Game-based features will be included for rewarding correctly performed exercises and motivating the user to achieve individually set exercise goals based on his/her initial motor performance. To ensure user-friendliness, the application will be developed based on established guidelines for media use in older adults. In the first of two clinical studies we will evaluate the accuracy of the estimates of lower extremity kinematics during exercise provided by the new system. In the second clinical study (a randomized controlled trial) we will evaluate the effectiveness of the proposed technology for improving mobility, gait, balance, quality of life, and risk of falling compared to unsupervised home trainin. Several validated outcome measures will be used to assess training-related changes in functional performance, as well as user perceived acceptability/usability of the new technology. A unique element of the present study is that both exercise adherence and exercise accuracy will be objectively assessed. A larger clinical study to further assess the benefits of the proposed technology for improving mobility and reducing falls in older adults is planned for Phase II of this project. In addition, in Phase II additional hardware and software development will be performed to make the system suitable for commercialization to the target population. The proposed technology could have an important effect on the US health care system by reducing the risk of falling and improving function, quality-of-life, and independence among older adults. This methodology addresses key issues for an aging population with high risk of falling and multiple disease processes. Moreover, the methods evaluated and refined in this study will be used in future web-based applications focused on exercise training in various disease processes that effect mobility and balance, such as stroke, diabetes, and dementia.

描述（由申请人提供）：已证明力量和平衡训练可以预防老年人的身体衰退和跌倒。大多数跌倒预防研究重点是利用合格的个人进行有监督的团体或家庭运动干预。由于功能或认知能力下降、护理责任或交通困难而导致居家状态，这些干预措施在社区范围内的实施受到限制。个人成本高昂以及缺乏团体锻炼设施也同样存在问题。一种有前途且具有成本效益的定制强度方法在社区环境中向老年人进行平衡锻炼是通过互联网提供培训。然而，基于网络的交互式家庭锻炼技术，包括虚拟监督训练，尚未开发出来。 BioSensics LLC（马萨诸塞州剑桥）和亚利桑那大学（高级运动性能跨学科联盟 (iCAMP) 和亚利桑那州老龄化中心）合作的 SHIFT SBIR 项目的目标是开发一种低成本、易于使用的交互式网络应用程序，用于家庭力量和平衡训练，以提高老年人的活动能力并降低跌倒风险。所提议的系统将基于现有的非交互式原型网络培训计划使用虚拟屏幕培训师进行开发。新的交互式网络应用程序将包括一个模仿用户动作的屏幕“用户头像”。这将通过开发包含运动传感器的仪表套鞋来实现。根据传感器信号，将使用简化的人体生物力学模型实时估计身体部位的运动学（例如脚部位置、脚踝角度和臀部角度）。运动学数据将驱动屏幕上的用户头像，该头像将为用户提供有关其锻炼表现的实时反馈。将包括基于游戏的功能，用于奖励正确执行的锻炼并激励用户根据他/她的初始运动表现实现单独设定的锻炼目标。为了确保用户友好性，该应用程序将根据老年人媒体使用的既定指南进行开发。在两项临床研究中的第一项中，我们将评估新系统提供的运动期间下肢运动学估计的准确性。在第二项临床研究（随机对照试验）中，我们将评估所提出的技术与无人监督的家庭训练相比，在改善活动能力、步态、平衡、生活质量和跌倒风险方面的有效性。一些经过验证的结果测量将用于评估与培训相关的功能性能变化，以及用户对新技术的可接受性/可用性。本研究的一个独特之处在于，将客观评估运动依从性和运动准确性。该项目的第二阶段计划进行一项更大规模的临床研究，以进一步评估所提议的技术在改善老年人活动能力和减少跌倒方面的益处。此外，在第二阶段，将进行额外的硬件和软件开发，以使该系统适合目标人群的商业化。拟议的技术可以通过降低跌倒风险并改善老年人的功能、生活质量和独立性，对美国医疗保健系统产生重要影响。该方法解决了人口老龄化、跌倒风险高和多种疾病过程的关键问题。此外，本研究中评估和完善的方法将用于未来基于网络的应用程序，重点关注影响活动能力和平衡的各种疾病过程的运动训练，例如中风、糖尿病和痴呆症。