Feasibility of Using Maestro Hand Exoskeleton in Post-stroke Hand Rehabilitation to Improve Joint Coordination

使用 Maestro 手部外骨骼进行中风后手部康复以提高关节协调性的可行性

• 批准号: 10368417
• 负责人: Na Jin Seo
• 金额: --
• 依托单位: RALPH H JOHNSON VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10368417
• 关键词: Activities of Daily Living; Acute; Address; Animals; Articular Range of Motion; Caring; Educational Status; Ensure; Feedback; Financial compensation; Finger joint structure; Fingers; Freedom; Future; Goals; Hand; Hand functions; Human; Impairment; Individuation; Intervention; Joints; Laws; Left; Leisures; Macaca; Measures; Monkeys; Movement; Neurologic; Outcome; Participant; Patient Participation; Patients; Pattern; Performance; Quality of life; Recovery; Rehabilitation therapy; Research; Robot; Robotics; Self Care; Stroke; Study models; System; Testing; Time; Torque; Training; Upper Extremity; Veterans; Work; arm; assistive robot; base; cost estimate; design; disability; effectiveness evaluation; exoskeleton; follow-up; grasp; hand dysfunction; hand rehabilitation; hand therapy; improved; individual patient; innovation; inpatient service; joint mobilization; military veteran; novel; patient safety; post stroke; prevent; programs; recruit; rehabilitative care; robot control; robot rehabilitation; stroke model; stroke patient; stroke survivor; tool

Estimated 15,000 Veterans suffer a stroke each year. Stroke is a leading cause of long-term disability in the US. New strokes cost an estimated $111 million for acute inpatient care, $75 million for post-acute inpatient care, and $88 million for follow-up care in the first six months post-stroke in VHA. Yet, more than two thirds of stroke survivors have persistent hand impairment that significantly diminishes their abilities to perform activities of daily living. While it is known that training for healthy movement patterns is critical especially early on in rehabilitation, precise control of multiple finger joints simultaneously is not possible in current therapy. Controlling finger joint movements is challenging since the human hand has more than 20 degrees of freedom (DOF) densely located in a small space. There exist robots for hand rehabilitation that train for gross grasping and finger individuation. However, current robots have limited DOF and cannot control finger joint torques, so these systems are unable to deliver training that ensures healthy movement patterns. Thus, there is lack of tools for delivering training that ensures healthy movement pattern and prevents compensatory movements. With a lack of joint-level training tool, patients are either left with compensatory patterns, or worse, have no recovery of hand movements. With the long-term goal of improving hand rehabilitation, we have designed a robotic tool called the Maestro hand exoskeleton. Maestro’s design features enable delivery of versatile interventions for patients with a wide range of impairments in various stages of recovery. This innovation represents a substantial advancement from current rehabilitation robotic tools by providing high-intensity, task-based training with real time modulation of assistance and difficulty level ensuring patient participation and task saliency. The objective of this project is to develop novel controllers with promising neurological basis for training correct movement patterns in stroke patients. Specifically, (1) compensation avoidance (CA) controller will apply joint torques to push the patients away from the compensatory joint coordination, only interfering with the movements once the subject initiates a compensatory movement strategy. (2) Task assistance (TA) controller will apply assistive joint torques to directly help stroke patients achieve finger tasks with correct coordination. For both controllers, the torques in the finger joints will be modulated to match the individual patient’s ability, impairment, and progression throughout the training via robot control program. Four and nine Veteran subacute stroke survivors with moderate to severe hand impairment and with some ability to move fingers will participate in the testing for Aim1 and Aim 2, respectively. Aim 1 will involve one session and Aim 2 will involve four sessions of experimentation for each participant. Aim 1: Develop and determine feasibility of CA and TA controllers. Hypothesis: CA and TA controllers are feasible, as seen by (1) patient safety and (2) abilities for TA and CA controller to move the finger joints toward the desired trajectories and away from compensatory coordination, respectively. Aim 2: Determine feasibility of training using CA and TA controllers in subacute stroke. Hypothesis: Joint coordination will improve over a training session more with CA controller for patients with moderate impairment, and more with TA controller for patients with severe impairment. Impact: This research will develop a novel training tool to improve finger joint coordination, thereby addressing the unmet need in the current rehabilitation. Future studies will use the developed Maestro controllers to elucidate underlying principles of practice-related neuro-recovery post stroke per impairment level and determine the effectiveness of Maestro on improving finger joint coordination and hand function. As a result, this research is expected to enhance hand function, contributing to improved independence and quality of life for Veterans with stroke.

估计每年有15,000名退伍军人中风。中风是美国长期残疾的主要原因。 急性住院治疗估计要花费1.11亿美元，急性后住院治疗为7500万美元， 在VHA的中风后头六个月，在前六个月的后续护理中进行了8800万美元。然而，超过三分之二的中风 幸存者的手部损害持久，大大降低了他们每天进行活动的能力 活的。众所周知，健康运动模式的培训至关重要，尤其是在康复的早期，但 在当前治疗中，根本无法对多个手指关节进行精确控制。控制手指关节 动作具有挑战性，因为人的手拥有超过20度的自由度（DOF） 在一个小空间中。有用于手动康复的机器人，可以训练抓紧抓握和手指个性化的机器人。 但是，当前的机器人的DOF有限，无法控制手指关节扭矩，因此这些系统无法 提供确保健康运动模式的训练。那就是缺乏提供培训的工具 这样可以确保健康运动模式并防止补偿性运动。缺乏联合培训 工具，患者要么具有补偿模式，要么更糟，没有手动运动的恢复。和 改善手部康复的长期目标，我们设计了一种机器人工具，称为Maestro Hand 外骨骼。 Maestro的设计功能可以为具有广泛范围的患者提供多功能干预措施 恢复各个阶段的损害。这项创新代表了当前的重大进步 康复机器人工具通过提供高强度，基于任务的培训并实时调节帮助 和难以确保患者参与和任务显着性的困难水平。该项目的目的是开发 具有承诺神经基础的新型控制器，用于训练中风患者的正确运动模式。 具体而言，（1）避免补偿（CA）控制器将应用关节扭矩以将患者推开 补偿性关节协调，仅一旦受试者启动A的运动就会干扰运动 补偿运动策略。 （2）任务援助（TA）控制器将使用辅助联合扭矩直接 帮助中风患者通过正确的协调完成手指任务。对于两个控制器，手指中的扭矩 关节将受到调节以匹配整个患者的患者的能力，障碍和进展 通过机器人控制程序进行培训。中度至重度 障碍和一定能力移动手指的能力将分别参与AIM1和AIM 2的测试。 AIM 1将涉及一个会话，AIM 2将涉及每次参与的四个实验会议。目标1： 开发并确定CA和TA控制器的可行性。假设：CA和TA控制器是可行的， 可见（1）患者安全性和（2）TA和CA控制器的能力，将手指关节移向所需 轨迹和远离补偿性协调。目标2：确定培训的可行性 在亚急性中风中使用CA和TA控制器。假设：联合协调将在培训中有所改善 与现代损害患者的CA控制器更多的会议，以及患者的TA控制器更多 严重损害。影响：这项研究将开发一种新颖的培训工具来改善手指关节 协调，从而解决了当前康复中未满足的需求。未来的研究将使用 开发的大师控制器阐明了中风后与实践相关的神经恢复的基本原则 每个损伤水平并确定大师在改善手指关节协调和手的有效性 功能。结果，这项研究有望增强手部功能，有助于提高独立性 中风的退伍军人的生活质量。