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

• 批准号: 10255585
• 负责人: Justin Rowe
• 金额: $ 25.65万
• 依托单位: FLINT REHABILITATION DEVICES
• 依托单位国家: 美国
• 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
• 来源: https://reporter.nih.gov/project-details/10255585
• 关键词: Accelerometer; Activities of Daily Living; Address; Adherence; Adverse event; Algorithms; Automobile Driving; Behavior; Behavior Therapy; Behavioral; California; Chronic; Clinical; Clinical Research; Communities; Cost utility; Data; Detection; Development; Devices; Emerging Technologies; Engineering; Environment; Exhibits; Feedback; Goals; Gold; Home; Hour; Individual; Intervention; Interview; Life; Location; Lower Extremity; Measures; Monitor; Motion; Motor; Motor Skills; Movement; Participant; Patient Self-Report; Phase; Physical Function; Physical activity; Population; Price; Public Health; Recovery; Rehabilitation Centers; Rehabilitation therapy; Reporting; Research; Resources; Risk; Schedule; Serious Adverse Event; Small Business Technology Transfer Research; Social Desirability; Standardization; Stroke; Structure; Surveys; System; Techniques; Technology; Testing; Therapeutic; Time; Translating; Universities; Upper Extremity; Upper limb movement; Video Recording; Visual; Walking; arm; base; behavior change; chronic stroke; community setting; cost; design; disability; experience; fitbit; grasp; improved; improved functioning; innovation; limb movement; motivated behavior; motor behavior; motor impairment; motor recovery; neurological rehabilitation; novel; patient oriented; personalized intervention; post stroke; preempt; preference; recruit; rehabilitation technology; satisfaction; sensor; social; stroke recovery; stroke survivor; tool; usability; wearable device; wearable sensor technology

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.

中风后完全康复的最坚不可摧的问题之一是电机能力之间的差距 中风幸存者继续（即他们可以做什么）以及他们如何从事家庭和社区活动（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 专为中风存活而设计。 Migo的独特功能是能够捕获和提供两者的反馈 使用自然环境中中风存活的定量和定性上肢和下肢活性 同一系统。该项目和Migo技术的长期目标是开发数据驱动和临床 知情的行为干预策略，使用可行的定量和定性反馈来最大化 中风后的身体功能。 该项目结合了Flint Rehab的技术，以实时运动捕获和开发专业知识 具有在运动行为和中风神经康复方面具有丰富经验的神经康复设备 南加州大学的神经康复小组。 I阶段IST旨在确定可行性， Migo的有效性，准确性和可用性监视功能运动行为并将有意义的反馈提供给 在该人群中看到的各种运动障碍中的中风冲浪者（AIM 1）。具体来说，有30个人 招募中风后长期表达运动障碍的范围（即轻度重度）参加此活动 项目。 Migo的准确性和实用性对最终用户的成本将在单个单击会议上进行评估。参与者会 配备Migo并执行功能标准化评估。作为金标准的比较，上肢 将运动与从标准化评估的视频记录得出的运动数进行比较， 阶跃计数和姿势/步幅时间将在步行测试期间衍生自ADPM传感器。原始传感器数据 从Migo将使用专有算法进行运动检测，并与金标准进行比较 确定准确性。公用事业成本将使用定量调查（社会可接受性和易用性）进行评估， 传感器成本和时间don和doff每个传感器以确定最小数量的Migo传感器和最佳 放置在身体上。在随后的步骤（AIM 2）中，优化Migo的短期可行性和可用性将是 通过在自然的1周间隔内使用Migo监视社区居住的中风存活而建立 环境。将记录依从性，不良事件的发生以及对Migo的满意度。使用数据 从监视期开始，将向参与者提供“移动报告”，并具有可视化的定量显示 和定性反馈（AIM 3）。通过调查和定性访谈，我们将确定Migo的组成部分 用户认为最有意义的反馈对于驱动持久行为改变。最终的技术将集成 工程和以患者为中心的康复方法，以促进有意义的人生活动的全面参与 在一个结构较低的环境下的临床环境 - 中风存活的一种生活。