The current rehabilitation evaluation methods for patients with hand dysfunction face issues such as inconsistent standards and incomplete quantification processes. To address these challenges, this paper introduces a rehabilitation evaluation system that integrates various rehabilitation training modes and leverages an exoskeleton finger rehabilitation robot. This system is carefully designed and thoroughly analyzed based on the diverse training modes offered by the rehabilitation robot. Twenty stroke patients and six healthy subjects were recruited to perform grasping of static objects and gesture movement experiments, which were evaluated by Brunnstrom’s motor evaluation and rehabilitation evaluation tests, respectively, and the results were compared. The experimental results showed that the results of the robotic rehabilitation evaluation of the 20 patients were consistent with the clinical Brunnstrom motor grades, which verified the accuracy of the rehabilitation evaluation system that was designed in this study.

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