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

据估计，每年有15,000名退伍军人中风。在美国，中风是导致长期残疾的主要原因。 据估计，新中风的急性住院治疗费用为1.11亿美元，急性后住院治疗费用为7500万美元， 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 幸存者有持续性的手损伤，显著降低了他们执行日常活动的能力 活着。虽然众所周知，健康运动模式的训练至关重要，尤其是在康复的早期， 在目前的治疗方法中，同时精确控制多个手指关节是不可能的。控制手指关节 运动是具有挑战性的，因为人类的手有超过20个自由度(DOF)密集地位于 在一个小空间里。存在用于手康复的机器人，它们训练粗大的抓取和手指的个性化。 然而，目前的机器人自由度有限，不能控制手指关节力矩，因此这些系统不能 提供确保健康运动模式的训练。因此，缺乏提供培训的工具。 这确保了健康的运动模式，并防止了代偿性运动。缺乏联合级别的培训 如果使用这种工具，患者要么处于代偿性模式，要么手部运动无法恢复。使用 为了改善手康复的长期目标，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范围广泛的患者提供多样化的干预 在恢复的不同阶段的损害。这一创新代表着从目前的 通过提供高强度、基于任务的培训和实时调整的援助来修复机器人工具 以及确保患者参与和任务突出的难度水平。这个项目的目标是开发 为训练中风患者正确的运动模式提供有前景的神经学基础的新型控制器。 具体地说，(1)补偿回避(CA)控制器将应用关节力矩将患者推离 补偿性关节协调，只有当受试者发起 补偿性运动策略。(2)任务辅助(TA)控制器将辅助关节力矩直接应用于 帮助中风患者在正确的协调下完成手指任务。对于两个控制器，手指中的扭矩 在整个治疗过程中，关节将进行调整，以适应单个患者的能力、损伤和进展 通过机器人控制程序进行培训。4名和9名手中至重度的亚急性中风老兵幸存者 残障和有一定移动手指能力的人将分别参加Aim1和Aim 2的测试。 目标1将包括一次实验，目标2将为每个参与者提供四次实验。目标1： 开发和确定CA和TA控制器的可行性。假设：CA和TA控制器是可行的，因为 通过(1)患者安全和(2)TA和CA控制器将手指关节移动到所需位置的能力来查看 轨迹和远离补偿性协调。目标2：确定培训的可行性 CA和TA控制器在亚急性卒中中的应用。假设：联合协调能力将在一次培训后得到改善 对于中度损伤的患者，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 有严重的损伤。影响：这项研究将开发一种新的训练工具来改善手指关节 协调，从而解决当前康复工作中未得到满足的需求。未来的研究将使用 开发Maestro控制器以阐明中风后练习相关神经康复的基本原理 根据损伤程度并确定Maestro在改善手指关节协调和手的有效性 功能。因此，这项研究有望增强手的功能，有助于提高独立性 以及中风退伍军人的生活质量。

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.