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

中风后完全恢复的最难以克服的问题之一是运动能力与中风后完全恢复的运动能力之间的差距。 中风幸存者恢复（即他们能做什么）以及他们如何参与家庭和社群活动（即他们 选择做）。为了应对这一挑战，Flint Rehab开发了MiGo，这是一种新颖的多传感器活动跟踪器， 专为中风幸存者设计MiGo的独特功能是能够捕获和提供对两者的反馈 定量和定性的上肢和下肢活动的中风幸存者在他们的自然环境中使用的， 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， 中风后的身体功能 该项目结合了弗林特康复的实时动作捕捉技术和专业知识， 神经康复设备在脑卒中神经康复的运动行为和 南加州大学的神经康复小组。第一阶段STTR旨在确定可行性， MiGo的有效性，准确性和可用性，以监测功能性运动行为，并提供有意义的反馈， 在该人群中观察到的广泛运动障碍的中风幸存者（目标1）。具体而言，30名 表示范围（即，轻度-重度）卒中后慢性运动障碍的患者将被招募参加本研究。 项目MiGo的准确性和最终用户的效用成本将在单个实验室会议中进行评估。参与者将被 配备MiGo进行功能标准化评估。作为金标准比较，上肢 将把人员流动情况与标准化评估录像中的人员流动情况进行比较， 而步数和站立/跨步时间将在步行测试期间从ADPM传感器导出。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）评估公用事业成本， 传感器成本以及安装和调试每个传感器的时间，以确定MiGo传感器的最小数量和最佳配置。 放在身体上。在随后的步骤（目标2）中，优化的MiGo的短期可行性和可用性将是 通过监测社区居住的中风幸存者使用MiGo超过1周的时间间隔，在自然 环境将记录依从性、不良事件发生率和对MiGo的满意度。使用数据 从监测期开始，参与者将收到一份“运动报告”，其中包含定量的视觉显示， 和质量反馈（目标3）。通过问卷调查和定性访谈，我们将识别MiGo的组件 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 工程和以患者为中心的康复方法，以促进更充分地参与有意义的生活活动 在一个不那么结构化的环境中，中风幸存者在临床环境之外生活。

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.