Koh Kyung, Oppizzi Giovanni, Baghi Raziyeh, Kehs Glenn Joseph, Zhang Li-Qun
Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA.
Department of Physical Therapy & Rehabilitation Science, University of Maryland, Baltimore, MD, USA.
Neurorehabil Neural Repair. 2025 Jun 20:15459683251340914. doi: 10.1177/15459683251340914.
BackgroundStroke often leads to long-term impairments in upper extremity motor function, including muscle weakness, spasticity, and abnormal joint synergies, which hinder independent joint control and daily activities.ObjectiveThis study examined multi-joint motor impairments and characterized abnormal synergy patterns post-stroke using a robotic exoskeleton.MethodsThe exoskeleton independently controlled shoulder, elbow, and wrist joints while measuring responses across all joints during horizontal plane movements. Fifty-three stroke survivors and 24 age-matched controls performed single-joint movements under constrained (fixed joints) and unconstrained (free joints) conditions. Coupled range of torques and range of motion at non-instructed joints were calculated relative to instructed joint movements and summarized in a 3 × 3 matrix.ResultsStroke survivors showed significantly higher coupling torques and motions at non-instructed joints compared to controls, with the greatest impairments in isolating distal movements, particularly in a proximal-to-distal gradient. Abnormal synergy patterns were systematically identified, revealing that stroke survivors exhibited two common patterns for shoulder and elbow tasks, marked by excessive coupling at neighboring joints. For wrist movement tasks, four distinct patterns emerged, involving excessive coupling at both shoulder and elbow joints.ConclusionThese findings demonstrate characteristic impairments in joint individuation and synergy following a stroke, providing a framework to understand motor deficits and guide rehabilitation strategies aimed at restoring joint-specific control.
背景
中风常常导致上肢运动功能的长期损伤，包括肌肉无力、痉挛和异常的关节协同作用，这些都会妨碍独立的关节控制和日常活动。
目的
本研究使用机器人外骨骼检查中风后的多关节运动损伤，并对异常协同模式进行特征描述。
方法
外骨骼在测量水平面运动期间所有关节的反应时，独立控制肩部、肘部和腕关节。53名中风幸存者和24名年龄匹配的对照组在受限（固定关节）和不受限（自由关节）条件下进行单关节运动。相对于指令关节运动，计算非指令关节的耦合扭矩范围和运动范围，并汇总在一个3×3矩阵中。
结果
与对照组相比，中风幸存者在非指令关节处表现出明显更高的耦合扭矩和运动，在分离远端运动时损伤最大，尤其是呈近端到远端的梯度。系统地识别出异常协同模式，表明中风幸存者在肩部和肘部任务中表现出两种常见模式，其特征是相邻关节处过度耦合。对于腕部运动任务，出现了四种不同模式，涉及肩部和肘部关节处的过度耦合。
结论
这些发现证明了中风后关节个体化和协同作用的特征性损伤，为理解运动缺陷和指导旨在恢复关节特异性控制的康复策略提供了一个框架。
