Rehabilitation Using Community-Based Affordable Robotic Exercise Systems (Rehab CARES)

使用基于社区的经济实惠的机器人运动系统进行康复（Rehab CARES）

• 批准号: 10923752
• 负责人: MICHELLE J. JOHNSON
• 金额: $ 6.78万
• 依托单位: RECUPERO ROBOTICS LLC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-22 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10923752
• 关键词: Adult; Adverse event; Algorithms; Caring; Characteristics; Clinic; Clinical; Clinical Trials; Clinical assessments; Collaborations; Communities; Compensation; Computer software; Control Groups; Data; Day Care; Docking; Dose; Equation; Exercise; Feedback; Fingers; Freedom; Frequencies; Friends; Goals; Hand; Health; Health Care Costs; Health Insurance; Health care facility; Heart Rate; Hospitals; Hour; Impaired cognition; Impairment; Improve Access; Individual; Infrastructure; Insurance Coverage; Intelligence; Intervention; Lead; Lower Extremity; Monitor; Motivation; Motor; Movement; Muscle; Occupational Therapy; Patient-Focused Outcomes; Patients; Performance; Persons; Phase; Physical therapy; Play; Play Therapy; Population; Positioning Attribute; Quality of Care; Randomized; Rehabilitation Centers; Rehabilitation therapy; Resource-limited setting; Resources; Robot; Robotics; Rural; Safety; Socioeconomic Status; Speech Therapy; Stroke; System; Technology; Testing; Therapeutic; Time; Upper Extremity; arm; base; care seeking; clinical predictors; cloud based; cohort; community based care; cost; cost effective; design; disability; empowerment; exercise rehabilitation; experience; follow up assessment; force feedback; functional improvement; functional outcomes; haptics; health care disparity; improved; individualized medicine; innovative technologies; instrument; kinematics; motor control; motor impairment; multidisciplinary; neurological rehabilitation; novel; nursing skill; post stroke; recruit; rehabilitation technology; rehabilitative care; robot assistance; robot control; robot rehabilitation; safety and feasibility; safety testing; sensor; stroke patient; stroke survivor; stroke therapy; success; targeted treatment; treatment duration; usability

PROJECT SUMMARY Stroke is the leading cause of serious long-term disability. It is estimated that 5.8–6.5 million people currently live with stroke related disability in the US and that this number will increase by 20.5% by 2030. The current US health infrastructure is not prepared for these increasing numbers. Limitations in health insurance coverage and the shortage of rehabilitation practitioners decrease access to rehabilitation. Community-based settings are becoming viable venues for delivering long-term post-stroke care, however, they are plagued by staff with limited expertise, low number of therapists and lack of financial resources for rehabilitation. Because of this, the quality of care is compromised, and functional outcomes of patients are not equal to hospital-based rehabilitation settings. We seek to develop a novel solution to this problem. Implementing affordable design is a fundamental strategy for increasing access to rehabilitation technology for patients regardless of socio-economic status. Doing so, decreases healthcare disparities and reduces long-term healthcare costs. We propose to use affordable robots to improve access to quality rehabilitation care in low-resource, community-based settings. In Phase 1, we leverage a 1 degree of freedom haptic robot with control algorithms to develop a beta version of the robot hardware and software. The new robot have a novel end-effector to allow more diverse arm and hand exercises, be connected to cloud-based gaming, and provide patient-specific therapy that adjusts for motor impairment and cognitive impairment. 15 stroke patients with a wide range of motor impairment levels will complete clinical assessments of motor and cognitive impairment followed by robot-based assessment and therapy games. Subjects will be instrumented with sensors monitoring key upper extremity muscle activity, trunk activity and heart rate during robot tasks. A key milestone will be to identify kinematic metrics from the robot tasks that strongly correlate and predict clinical scores of motor and cognitive impairment. Another milestone will to drive patient-specific strategies by adjusting the robot’s control parameters and the game parameters. In Phase 2, we will develop the hardware to allow three haptic robots to dock (a gym) and be configured to allow patients to play therapy games alone or collaboratively. We will test the safety and feasibility of the gym in a community-based rehabilitation setting where stroke patients typically receive 1 hour each of physical therapy (PT), occupational therapy (OT) and speech therapy (SLP). 36 patients will be randomized to either a robot (RT) or a control group (CT). Both groups will receive PT and SLP, but the RT will receive the robot gym therapy targeting the upper limb and the CT will receive a dose-matched hour of OT. Therapy will occur over 4 weeks with two follow-up assessments. Key milestones will be to show that the RT has the same or better functional outcomes, motivation, and adverse events as the CT. Also, to show that the robot gym is a cost-effective solution to increasing access to quality rehabilitation care in low-resource, community-based settings. Success here will validate this potential solution, justify design changes revealed via user-feedback and a larger clinical trial.

项目摘要 中风是严重长期残疾的主要原因。据估计目前有58-650万人 美国与中风相关的残疾生活，到2030年这个数字将增加20.5％。 卫生基础设施尚未为这些越来越多的数量做好准备。健康保险范围的限制和 康复从业人员的短缺减少了获得康复的机会。基于社区的设置是 成为提供长期冲程后护理的可行场所，但是，他们受到有限的员工的困扰 专业知识，治疗师数量少以及缺乏康复财务资源。因此，质量 护理受到损害，患者的功能结果不等于基于医院的康复 设置。我们试图为这个问题开发一种新颖的解决方案。实施负担得起的设计是基本的 无论社会经济地位如何，都可以增加患者获得康复技术的策略。 这样做，减少医疗保健分配并降低长期医疗保健成本。我们建议使用 负担得起的机器人可以在低资源，基于社区的环境中改善获得优质康复护理的机会。在 第1阶段，我们利用具有控制算法的1度自由触觉机器人来开发Beta版本 机器人硬件和软件。新机器人有一个新颖的最终效果，可以允许更多多样化的手臂和手 练习，连接到基于云的游戏，并提供针对运动调整的患者特定疗法 障碍和认知障碍。 15名中风患者具有广泛的运动障碍水平 对运动和认知障碍的完整临床评估，然后是基于机器人的评估和 治疗游戏。受试者将使用传感器进行仪器，以监视关键的上肢肌肉活动，后备箱 机器人任务期间的活动和心率。一个关键的里程碑将是从机器人中识别运动学指标 密切相关并预测运动和认知障碍的临床评分的任务。另一个里程碑 通过调整机器人的控制参数和游戏参数来推动患者特定的策略。 第2阶段，我们将开发硬件，以允许三个触觉机器人停靠（健身房），并配置为允许 患者单独或共同玩治疗游戏。我们将测试健身房在 基于社区的康复环境，中风患者通常每次接受1小时的物理疗法 （PT），职业治疗（OT）和语音疗法（SLP）。 36名患者将被随机分为机器人（RT） 或对照组（CT）。两组都将获得PT和SLP，但RT将获得机器人健身疗法 瞄准上肢和CT将获得剂量匹配的OT小时。治疗将在4周内进行 进行两次后续评估。关键里程碑将表明RT具有相同或更好的功能 结果，动机和不利事件作为CT。另外，要证明机器人体育馆是一种具有成本效益的解决方案 在低资源，基于社区的环境中增加获得优质康复护理的机会。在这里成功 验证该潜在解决方案，证明通过用户反馈和更大的临床试验揭示的设计变化是合理的。