Sensor Activity Monitoring, Feedback, and Outcome Measures, Stroke Rehabilitation

描述（由申请人提供）：“健康独立生活技术”符合我们的目标，即测试和进一步开发具有通信和分析平台的廉价无线传感器，以监测残疾人的日常活动，如步行和锻炼。我们的医疗日常活动无线网络（MDAWN）旨在使研究人员、试验人员和临床医生能够获得家庭和社区日常身体活动的可靠数据，而不仅仅是在诊所和实验室访问期间或通过问卷调查。通过脚踝加速度计为每个人开发的新型机器学习算法将识别连续运动和步行的类型、数量和质量。此外，我们将测试一种为残疾人士设计的廉价、仪器化、符合人体工程学的踏板，称为UCFit，以促进家庭健身运动。MDAWN和UFCFit传感器将数据发送到安卓智能手机，然后通过互联网发送到加州大学洛杉矶分校的服务器进行分析。我们将对这些遥感设备的实用性进行进一步的评估，在现实世界中对近期致残性中风患者进行临床试验，这些患者的正式康复通常无法实现功能性行走和心血管健康。在第二阶段的随机对照试验中，我们将比较两种水平的每周电话反馈对日常表现的影响，这是第一次通过远程数据采集实现的。高反馈组将收到每天的表现数据，包括蹬车的次数和分钟数、速率/ rpm和使用的力量，以及步行的次数、持续时间、平均速度和在家庭和社区使用的距离。反馈最少的一组只听到每天总的UCFit锻炼和步行时间。经过4个月的鼓励，每周进行多达4次30分钟的UCFit锻炼，我们将测试组间每日运动量和步行时间的差异为50%。次要结果检查健康水平、步行速度和身体功能的变化。然后，两组人在4个多月的时间里交替进行高反馈或低反馈，然后重新评估结果。然后，没有任何反馈，参与者在12个月内接受运动量和健康状况测试。我们将确定哪种形式的反馈能激发更好的自我管理，以优化健身和步行。我们将收集有关从康复医院到家庭过渡过程中流动性的独特数据；在日常护理中量化步态训练；在比实验室更复杂的条件下评估行走技能；并测试传感器数据的响应性，作为比率尺度结果测量在预期增益的时间。这项研究将首次全面展示移动健康远程监测和日常身体活动的结果测量！

DESCRIPTION (provided by applicant): "Technologies for Healthy Independent Living" coincides with our goal to test and further develop inexpensive wireless sensors with communication and analysis platforms to monitor everyday activities, such as walking and exercise, in disabled persons. Our Medical Daily Activity Wireless Network (MDAWN) aims to enable researchers, trialists, and clinicians to acquire reliable data about daily physical activites in the home and community, rather than only during clinic and laboratory visits or by questionnaires. Novel machine-learning algorithms developed for each person from ankle accelerometers will identify the type, quantity and quality of exercise and walking on a continuous basis. In addition, we will test an inexpensive, instrumented, ergometric pedaler designed for disabled persons, called the UCFit, to promote home-based fitness exercise. The MDAWN and UFCFit sensors send data to an Android smartphone, then over the Internet to a UCLA server for analysis. We will nest further evaluation of the utility of these remote sensing devices within the real-world setting of a clinical trial of patients with recent disabling stroke,for whom formal rehabilitation often falls short of enabling functional walking and cardiovascular fitness. In a phase 2, randomized controlled trial, we will compare two levels of weekly telephonic feedback about daily performance, made possible for the first time by remote data acquisition. The high feedback group will receive everyday performance data that includes the number of bouts and minutes of pedaling plus rate/RPMs and forces used, as well as the number of bouts of walking, duration, and average speed and distance used in home and community. The minimal feedback group only hears about total daily UCFit exercise and walking time. After 4 months of encouraging up to four 30-min sessions per week of UCFit exercise, we will test for a 50% between-group difference in amount of daily exercise and walking time. Secondary outcomes examine change in level of fitness, walking speed, and physical functioning. The two groups then cross over to high or low feedback for 4 more months, before outcomes are reassessed. Then, no feedback is given and participants are tested for amount of exercise and fitness at 12 months. We will determine which form of feedback motivates better self-management to optimize fitness and walking. We will gather unique data about mobility in the transition from rehabilitation hospital to home; quantify gait training durin usual care; assess walking skills under more complex conditions than in a laboratory; and test the responsiveness of sensor data as a ratio scale outcome measurement during a time of expected gains. This study will be the first comprehensive demonstration of mHealth remote monitoring and outcome measures of daily physical activity! PUBLIC HEALTH RELEVANCE: Several important public health needs will be met by testing, within a clinical trial in the home and community, a system of wearable activity and exercise monitoring technologies that measure the type, quantity and quality of walking and exercise. Our trial aims to increase fitness and enable more functional levels of daily activities in disable persons after stroke, while providing a proof-of-principle for the utility of wireless health toolsto reliably monitor real-world physical functioning and to provide clinically meaningful outcome measures. These generic tools for daily care and research can be deployed across diseases and disabilities.