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Individual patterns of motor deficits evident in movement distribution analysis

机译:运动分布分析中明显的运动缺陷个体模式

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摘要

Recent studies in rehabilitation have shown potential benefits of patient-initiated exploratory practice. Such findings, however, lead to new challenges in how to quantify and interpret movement patterns. We posit that changes in coordination are most evident in statistical distributions of movements. In a test on 10 chronic stroke subjects practicing for 3 days, we found that inter-quartile range of motion did not show improvement. However, a multivariate Gaussians analysis required more complexity at the end of training. Beyond simply characterizing movement, linear discriminant classification of each patient’s movement distribution also identified that each patient’s motor deficit left a unique signature. The greatest distinctions were observed in the space of accelerations (rather than position or velocity). These results suggest that unique deficits are best detected with such a distribution analysis, and also point to the need for customized interventions that consider such patient-specific motor deficits.
机译:康复方面的最新研究表明,患者进行探索性练习的潜在益处。但是,这些发现给如何量化和解释运动模式带来了新的挑战。我们认为,协调的变化在运动的统计分布中最为明显。在对10名慢性中风受试者进行3天的测试中,我们发现四分位间距的运动范围没有改善。但是,多元高斯分析在训练结束时需要更多的复杂性。除了简单地描述运动特征之外,对每个患者的运动分布进行线性判别分类还可以确定每个患者的运动障碍都具有独特的特征。在加速度的空间(而不是位置或速度)中观察到最大的区别。这些结果表明,通过这种分布分析可以最好地检测出独特的缺陷,并且还指出了需要考虑此类患者特定运动缺陷的定制干预措施的需求。

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