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首页> 外文期刊>Journal of Biomechanics >Combining muscle synergies and biomechanical analysis to assess gait in stroke patients
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Combining muscle synergies and biomechanical analysis to assess gait in stroke patients

机译:结合肌肉协同作用和生物力学分析,以评估卒中患者的步态

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Abstract The understanding of biomechanical deficits and impaired neural control of gait after stroke is crucial to prescribe effective customized treatments aimed at improving walking function. Instrumented gait analysis has been increasingly integrated into the clinical practice to enhance precision and inter-rater reliability for the assessment of pathological gait. On the other hand, the analysis of muscle synergies has gained relevance as a novel tool to describe the neural control of walking. Since muscle synergies and gait analysis capture different but equally important aspects of walking, we hypothesized that their combination can improve the current clinical tools for the assessment of walking performance. To test this hypothesis, we performed a complete bilateral, lower limb biomechanical and muscle synergies analysis on nine poststroke hemiparetic patients during overground walking. Using stepwise multiple regression, we identified a number of kinematic, kinetic, spatiotemporal and synergy-related features from the paretic and non-paretic side that, combined together, allow to predict impaired walking function better than the Fugl-Meyer Assessment score. These variables were time of peak knee flexion, VAF total values, duration of stance phase, peak of paretic propulsion and range of hip flexion. Since these five variables describe important biomechanical and neural control features underlying walking deficits poststroke, they may be feasible to drive customized rehabilitation therapies aimed to improve walking function. This paper demonstrates the feasibility of combining biomechanical and neural-related measures to assess locomotion performance in neurologically injured individuals.
机译:摘要在中风后,对生物力学赤字和神经控制受损的理解是对规定改善行走功能的有效定制治疗至关重要。仪器步态分析越来越纳入临床实践,以提高对病理步态评估的精度和帧间间可靠性。另一方面,肌肉协同效应的分析已经获得了描述了描述行走神经控制的新工具。由于肌肉协同效应和步态分析捕获不同但同样重要的行走方面,我们假设它们的组合可以改善目前用于评估行走性能的临床工具。为了测试这一假设,我们在九次外汇血液机械患者中进行了完整的双侧,下肢生物力学和肌肉协同效应分析。使用逐步多元回归,我们确定了许多来自瘫痪和非剖面的运动,动力学,时空和协同作用,即组合在一起,允许预测流动的行走功能比Fugl-Meyer评估分数更好。这些变量是峰值弯曲屈曲的时间,VAF总值,姿势阶段持续时间,静脉推进峰的峰值和髋部屈曲范围。由于这五个变量描述了重要的生物力学和神经控制功能,因此行走缺陷失败的特征,他们可能是可行的,可以推动定制的康复治疗,旨在改善行走功能。本文展示了与生物力学和神经相关措施相结合的可行性,以评估神经损伤的个体中的运动性能。

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