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引用次数: 0

摘要

约 80% 的脑卒中患者会出现上肢运动障碍。在脑卒中康复中,上肢运动学评估越来越多地被用作主要或次要的结果测量。目前还没有一个通用的标准化量表来对多关节上肢运动进行分类。我们提出了一种改良的普罗克鲁斯统计形状法,作为一种定量分析方法,可以识别多个肢体节段协调运动的运动片段。这种方法并不完全依赖于离散的运动学数值来对比运动,而是可以评估运动的进展情况。对健全人运动进行的普罗克里斯特分析表明,手部和前臂的运动在开始时更加协调。在运动完成过程中,肩部和肘部会变得更加协调。在运动能力受损的情况下,随着手臂的减速,手部和前臂之间的这种协调性会被破坏。临床意义--临床医生可将这种改良的普氏形状分析方法应用于上肢运动障碍患者的运动捕捉数据,以客观地识别多关节协调和恢复情况。
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A Novel Procrustes Analysis Method to Quantify Multi-Joint Coordination of the Upper Extremity after Stroke.

Upper extremity motor impairment affects about 80% of persons after strokes. For stroke rehabilitation, upper limb kinematic assessments have increasingly been used as primary or secondary outcome measures. There is currently no universal standardized scale for categorizing multi-joint upper extremity movement. We propose a modified Procrustes statistical shape method as a quantitative analysis that can recognize segments of movement where multiple limb segments are coordinating movement. Rather than rely solely on discrete kinematic values to contrast movement, this method allows evaluation of how movement progresses. The Procrustes analysis of able-bodied movement showed that the hand and forearm segments moved in a more coordinated manner during initiation. The shoulder and elbow become more coordinated during movement completion. In impaired movement, this coordination between the hand and forearm is disrupted as the arm decelerates. The utilization of Procrustes analysis may be a step towards developing a comprehensive and universal quantitative tool that does not require changes to existing treatments or increase patient burden.Clinical relevance- This modified Procrustes Shape Analysis method can be applied by clinicians to motion capture data from patients suffering upper extremity movement deficits to objectively identify multi-joint coordination and recovery.

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