Neurological injuries such as stroke often differentially impair hand motor and somatosensory function, as well as the interplay between the two, which leads to limitations in performing activities of daily living. However, it is challenging to identify which specific aspects of sensorimotor function are impaired based on conventional clinical assessments that are often insensitive and subjective. In this work we propose and validate a set of robot-assisted assessments aiming at disentangling hand proprioceptive from motor impairments, and capturing their interrelation (sensorimotor impairments). A battery of five complementary assessment tasks was implemented on a one degree-of-freedom end-effector robotic platform acting on the index finger metacarpophalangeal joint. Specifically, proprioceptive impairments were assessed using a position matching paradigm. Fast target reaching, range of motion and maximum fingertip force tasks characterized motor function deficits. Finally, sensorimotor impairments were assessed using a dexterous trajectory following task. Clinical feasibility (duration), reliability (intra-class correlation coefficient ICC, smallest real difference SRD) and validity (Kruskal-Wallis test, Spearman correlations $$\rho$$ with Fugl-Meyer Upper Limb Motor Assessment, kinesthetic Up-Down Test, Box & Block Test) of robotic tasks were evaluated with 36 sub-acute stroke subjects and 31 age-matched neurologically intact controls. Eighty-three percent of stroke survivors with varied impairment severity (mild to severe) could complete all robotic tasks (duration: <15 min per tested hand). Further, the study demonstrated good to excellent reliability of the robotic tasks in the stroke population (ICC>0.7, SRD<30%), as well as discriminant validity, as indicated by significant differences (p-value<0.001) between stroke and control subjects. Concurrent validity was shown through moderate to strong correlations ( $$\rho$$ =0.4-0.8) between robotic outcome measures and clinical scales. Finally, robotic tasks targeting different deficits (motor, sensory) were not strongly correlated with each other ( $$\rho \le$$ 0.32, p-value>0.1), thereby presenting complementary information about a patient’s impairment profile. The proposed robot-assisted assessments provide a clinically feasible, reliable, and valid approach to distinctly characterize impairments in hand proprioceptive and motor function, along with the interaction between the two. This opens new avenues to help unravel the contributions of unique aspects of sensorimotor function in post-stroke recovery, as well as to contribute to future developments towards personalized, assessment-driven therapies.

中文翻译：

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中风后手本体感觉、运动和感觉运动障碍的可靠和有效的机器人辅助评估

中风等神经损伤通常会不同程度地损害手部运动和躯体感觉功能，以及两者之间的相互作用，从而导致日常生活活动受到限制。然而，根据通常不敏感和主观的常规临床评估来确定感觉运动功能的哪些特定方面受损是具有挑战性的。在这项工作中，我们提出并验证了一组机器人辅助评估，旨在将手本体感觉与运动障碍分开，并捕捉它们的相互关系（感觉运动障碍）。在作用于食指掌指关节的单自由度末端执行器机器人平台上实施了五个互补的评估任务。具体来说，使用位置匹配范式评估本体感受障碍。快速目标到达、运动范围和最大指尖力任务以运动功能缺陷为特征。最后，使用完成任务后的灵巧轨迹来评估感觉运动障碍。临床可行性（持续时间）、可靠性（类内相关系数 ICC、最小实际差异 SRD）和有效性（Kruskal-Wallis 检验、Spearman 相关性 $$\rho$$ 与 Fugl-Meyer 上肢运动评估、动觉上下测试, Box & Block Test) 的机器人任务评估了 36 名亚急性中风受试者和 31 名年龄匹配的神经系统完整对照。83% 具有不同损伤严重程度（轻度到重度）的中风幸存者可以完成所有机器人任务（持续时间：每只测试手 <15 分钟）。更远，该研究证明了中风人群中机器人任务的良好至极好可靠性（ICC>0.7，SRD<30%），以及区分效度，如中风和对照受试者之间的显着差异（p 值 <0.001）所示。通过机器人结果测量和临床量表之间的中到强相关性（$$\rho$$ =0.4-0.8）显示了同时有效性。最后，针对不同缺陷（运动、感觉）的机器人任务彼此之间没有很强的相关性（$$\rho\le$$ 0.32，p 值>0.1），从而提供了关于患者损伤概况的补充信息。拟议的机器人辅助评估提供了一种临床上可行、可靠和有效的方法，可以明确表征手本体感觉和运动功能的损伤，以及两者之间的互动。这开辟了新的途径，有助于阐明感觉运动功能的独特方面在中风后恢复中的贡献，并有助于未来向个性化、评估驱动的疗法发展。