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Loss of Lag Response Curvilinearity of Gait Poincare Plot Indices in Neurodegenerative Disorders

机译:神经退行性疾病步态Poincare曲线指标的滞后响应曲线损失

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It is reported in the literature that the temporal structure of gait variability in healthy subjects exhibits deterministic processes where not only each stride is correlated with the neighbouring strides ( i.e . short-range correlations), but at least on a statistical basis, with tens and hundreds of preceding and following strides ( i.e . long-range correlations). Thus, an analysis hinging on a conventional gait Poincare plot with lag one which implicitly assumes that the current stride is influenced by the immediately preceding stride will likely underestimate the role of the autocovariance function of stride intervals. This implies that a series of lagged gait Poincare plots can potentially provide more information by reflecting short-range correlations of gait variability through the behaviour of Poincare indices in health as well as disease. Hence, in this study in the context of short-term variability, we assessed a curvilinear relation between lag (1 - 6) and Poincare indices in normal subjects and patients with neurodegenerative disorders. We found that while normal subjects exhibited this curvilinearity, the patients with neurodegenerative disorders showed its loss.
机译:据文献报道,健康受试者的步态变化的时间结构表现出确定性过程,其中不仅每个步幅与相邻步幅相关(即短程相关),而且至少在统计学基础上与数十个步幅相关。数以百计的向前和向后的步幅(即远程关联)。因此,在传统步态庞加莱图上进行滞后分析的分析隐含地假设当前步幅受前一步幅影响,这可能会低估步幅间隔的自协方差函数的作用。这意味着一系列滞后的步态Poincare图可以通过反映健康和疾病中Poincare指数行为的步态变异性的短时相关性来潜在地提供更多信息。因此,在短期可变性的背景下,我们评估了正常受试者和神经退行性疾病患者的滞后(1-6)与Poincare指数之间的曲线关系。我们发现,尽管正常受试者表现出这种曲线性,但患有神经退行性疾病的患者却表现出其丧失。

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