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: 10515326
• 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 2024-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10515326
• 关键词: Activities of Daily Living; Acute; Address; Animals; Articular Range of Motion; Caring; Compensation; Educational Status; Ensure; Feedback; Finger joint structure; Fingers; Freedom; Future; Goals; Hand; Hand functions; Human; Impairment; Individuation; Intervention; Joints; Laws; Learning; 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; 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。 新的中风估计花费1.11亿美元用于急性住院治疗，7500万美元用于急性后住院治疗， 以及8800万美元用于VHA中风后前六个月的后续护理。然而，超过三分之二的中风患者 幸存者有持续的手部损伤，显著降低了他们进行日常活动的能力， living.虽然众所周知，健康运动模式的训练是至关重要的，特别是在康复的早期， 在当前的治疗中不可能同时精确控制多个手指关节。控制指关节 由于人手具有超过20个密集分布的自由度（DOF）， 在一个小空间里。存在用于手部康复的机器人，其训练粗抓和手指个性化。 然而，目前的机器人具有有限的自由度，并且不能控制手指关节扭矩，因此这些系统不能 提供训练，确保健康的运动模式。因此，缺乏提供培训的工具 确保健康的运动模式，防止代偿性运动。由于缺乏联合级别的培训 工具，患者要么留下代偿模式，或者更糟的是，手部运动没有恢复。与 为了实现改善手部康复的长期目标，我们设计了一种名为Maestro Hand的机器人工具 外骨骼Maestro的设计特点使其能够为患者提供多种干预措施， 在不同的恢复阶段。这一创新代表了从目前的 康复机器人工具，通过提供高强度的、基于任务的训练和真实的时间辅助调制， 和难度水平，确保患者参与和任务显著性。该项目的目标是开发 新的控制器，有前途的神经学基础，用于训练中风患者的正确运动模式。 具体地，（1）补偿避免（CA）控制器将施加关节扭矩以将患者推离 补偿性关节协调，只有在受试者开始运动时才干扰运动。 补偿运动策略(2)任务辅助（TA）控制器将应用辅助关节扭矩直接 帮助中风患者以正确的协调性完成手指任务。对于两个控制器，手指中的扭矩 关节将被调节，以匹配个体患者的能力，损伤和整个过程中的进展。 通过机器人控制程序进行训练。4例和9例中重度手的亚急性卒中幸存者 有一定手指活动能力的残疾人将分别参加目标1和目标2的测试。 目标1将涉及一个会议，目标2将涉及四个会议的实验，为每个参与者。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， 从（1）患者安全性和（2）TA和CA控制器将手指关节向所需方向移动的能力来看 轨迹和远离补偿协调，分别。目标2：确定培训的可行性 在亚急性卒中中使用CA和TA控制器。假设：联合协调将在训练中得到改善 对于中度损伤患者，使用CA控制器进行更多会话，对于患者，使用TA控制器进行更多会话 严重受损影响：本研究将开发一种新的训练工具，以改善手指关节 协调，从而解决目前恢复工作中未得到满足的需要。未来的研究将使用 开发了Maestro控制器，以阐明卒中后与实践相关的神经恢复的基本原则 并确定Maestro对改善手指关节协调和手部的有效性 功能因此，这项研究有望增强手的功能，有助于提高独立性 和中风退伍军人的生活质量