MiGo: wearable sensors that combine actionable data with a behavioral intervention to improve function after stroke

MiGo:可穿戴传感器,将可操作数据与行为干预相结合,以改善中风后的功能

基本信息

  • 批准号:
    10255585
  • 负责人:
  • 金额:
    $ 25.65万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-08-01 至 2024-01-31
  • 项目状态:
    已结题

项目摘要

One of the most impenetrable problems challenging full recovery after stroke is the gap between motor capacity that a stroke survivor regains (i.e. what they can do) and how they engage in home and community activities (i.e. what they choose to do). To address this challenge, Flint Rehab developed MiGo, a novel multi-sensor activity tracker specifically designed for stroke survivors. The unique feature of MiGo is the ability to capture and deliver feedback on both quantitative and qualitative upper and lower limb activity of stroke survivors in their natural environment using the same system. The long-term goal for this project and the MiGo technology is to develop a data-driven and clinically informed behavioral intervention strategy that uses actionable quantitative and qualitative feedback to maximize physical function after stroke. This project combines Flint Rehab’s technology for real-time motion capture and expertise in developing neurorehabilitation devices with the extensive experience in stroke neurorehabilitation of the Motor Behavior and Neurorehabilitation team at the University of Southern California. This Phase I STTR aims to establish the feasibility, validity, accuracy and usability of MiGo to monitor functional movement behaviors and deliver meaningful feedback to stroke survivors across a broad range of motor impairments seen in this population (Aim 1). Specifically, 30 individuals expressing a range (i.e., mild-severe) of motor impairment chronically after stroke will be recruited to participate in this project. MiGo’s accuracy and utility cost to the end user will be assessed in a single in-lab session. Participants will be outfitted with MiGo and perform functional standardized assessments. As gold-standard comparison, upper limb movements will be compared to movement counts derived from a video recording of the standardized assessments, whereas step counts and stance/stride time will be derived from the ADPM sensors during a walk test. Raw sensor data from MiGo will be analyzed using proprietary algorithms for movement detection and compared to the gold-standards to determine accuracy. Utility cost will be assessed using quantitative survey (social acceptability and ease-of-use), sensor cost and time to don and doff each sensor to determine the minimal number of MiGo sensors and the optimal placement on the body. In a subsequent step (Aim 2), short term feasibility and usability of the optimized MiGo will be established by monitoring community-dwelling stroke survivors using MiGo over a 1-week interval in the natural environment. Adherence, occurrence of adverse events, and satisfaction with MiGo will be recorded. Using the data from the monitoring period, participants will be presented with a ‘Movement report’ with visual displays of quantitative and qualitative feedback (Aim 3). Through survey and qualitative interview, we will identify the components of MiGo feedback that users find most meaningful for driving lasting behavior change. The resulting technology will integrate engineering and patient-centered rehabilitation approaches to promote fuller participation in meaningful life activities outside clinical settings in a less structured environment—one where stroke survivors live their lives.
挑战中风后完全康复的最棘手的问题之一是运动能力之间的差距 中风幸存者重新获得(即他们能做什么)以及他们如何参与家庭和社区活动(即他们 选择去做)。为了应对这一挑战,Flint Rehab开发了一种新型的多传感器活动跟踪器MIGO 专为中风幸存者设计。MIGO的独特功能是能够捕获并提供关于这两个方面的反馈 中风幸存者在其自然环境中的定量和定性的上肢和下肢活动 同样的系统。该项目和MIGO技术的长期目标是开发一种数据驱动的临床 知情的行为干预策略,使用可操作的定量和定性反馈来最大限度地 中风后的身体功能。 该项目结合了Flint Rehab的实时运动捕获技术和开发专业知识 神经康复设备具有丰富的中风神经康复经验的运动行为和 南加州大学的神经康复团队。这项第一阶段的STTR旨在确定可行性, MIGO监控功能性运动行为的有效性、准确性和可用性,并向 中风幸存者在这个人群中看到的广泛的运动障碍(目标1)。具体地说,30个人 中风后表现为一系列(即轻度-重度)运动障碍的患者将被招募参与这一活动 项目。MIGO的准确性和对最终用户的实用成本将在一次实验室会议中进行评估。参与者将是 配备MIGO并进行功能标准化评估。作为黄金标准的对比,上肢 运动将与从标准化评估的视频记录中得出的运动计数进行比较, 而步数和站立/大步时间将在步行测试期间从ADPM传感器获得。原始传感器数据 将使用专有的运动检测算法进行分析,并与黄金标准进行比较 以确定准确性。将使用定量调查(社会可接受性和易用性)来评估公用事业成本, 传感器成本和戴上和放下每个传感器的时间,以确定MIGO传感器的最小数量和最佳数量 放置在身体上。在接下来的步骤(目标2)中,优化的MIGO的短期可行性和可用性将是 通过在自然界使用MIGO监测社区居住的中风幸存者1周的间隔而建立的 环境。将记录对MIGO的依从性、不良事件的发生和满意度。使用数据 在监控期内,参赛者将收到一份《运动报告》,其中显示了 和定性反馈(目标3)。通过调查和定性访谈,我们将确定MIGO的组成部分 用户认为对推动持久的行为改变最有意义的反馈。由此产生的技术将整合到 工程学和以患者为中心的康复方法,促进更充分地参与有意义的生活活动 在外部的临床环境中,中风幸存者在一个结构较差的环境中生活。

项目成果

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Justin Rowe其他文献

Justin Rowe的其他文献

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{{ truncateString('Justin Rowe', 18)}}的其他基金

MiGo-Wheels: A comprehensive feedback system to help wheelchair users maintain a healthy lifestyle
MiGo-Wheels:帮助轮椅使用者保持健康生活方式的综合反馈系统
  • 批准号:
    10001364
  • 财政年份:
    2020
  • 资助金额:
    $ 25.65万
  • 项目类别:
RehabTouch: A mixed-reality gym for rehabilitating the hands, arms, trunk, and legs after stroke
RehabTouch:混合现实健身房,用于中风后手、手臂、躯干和腿的康复
  • 批准号:
    9409324
  • 财政年份:
    2017
  • 资助金额:
    $ 25.65万
  • 项目类别:

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