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使用多重分形去趋势波动分析来表征中风引起的下肢运动学变异性变化。

Characterizing stroke-induced changes in the variability of lower limb kinematics using multifractal detrended fluctuation analysis.

作者信息

Xu Pan, Yu Hairong, Wang Xiaoyun, Song Rong

机构信息

Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Sun Yat-sen University, Guangzhou, China.

Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, Sun Yat-sen University, Guangzhou, China.

出版信息

Front Neurol. 2022 Aug 5;13:893999. doi: 10.3389/fneur.2022.893999. eCollection 2022.

Abstract

Movement variability reflects the adaptation of the neuromuscular control system to internal or external perturbations, but its relationship to stroke-induced injury is still unclear. In this study, the multifractal detrended fluctuation analysis was used to explore the stroke-induced changes in movement variability by analyzing the joint angles in a treadmill-walking task. Eight healthy subjects and ten patients after stroke participated in the experiment, performing a treadmill-walking task at a comfortable speed. The kinematics data of the lower limbs were collected by the motion-capture system, and two indicators, the degree of multifractality (α) and degree of correlation [(2)], were used to investigate the mechanisms underlying neuromuscular control. The results showed that the knee and ankle joint angles were multifractal and persistent at various scales, and there was a significant difference in the degree of multifractality and the degree of correlation at the knee and ankle joint angles among the three groups, with the values being ranked in the following order: healthy subjects < non-paretic limb < paretic limb. These observations highlighted increased movement variability and multifractal strength in patients after stroke due to neuromotor defects. This study provided evidence that multifractal detrended analysis of the angles of the knee and ankle joints is useful to investigate the changes in movement variability and multifractal after stroke. Further research is needed to verify and promote the clinical applications.

摘要

运动变异性反映了神经肌肉控制系统对内部或外部扰动的适应性,但其与中风所致损伤的关系仍不明确。在本研究中,通过分析跑步机行走任务中的关节角度,利用多重分形去趋势波动分析来探究中风引起的运动变异性变化。八名健康受试者和十名中风后患者参与了实验,以舒适的速度进行跑步机行走任务。下肢运动学数据由动作捕捉系统收集,使用多重分形程度(α)和相关性程度[(2)]这两个指标来研究神经肌肉控制的潜在机制。结果表明,膝关节和踝关节角度在不同尺度上具有多重分形性且呈持续性,三组之间膝关节和踝关节角度的多重分形程度和相关性程度存在显著差异,其数值排序如下:健康受试者<非瘫痪侧肢体<瘫痪侧肢体。这些观察结果突出了中风后患者由于神经运动缺陷导致运动变异性和多重分形强度增加。本研究提供了证据表明,对膝关节和踝关节角度进行多重分形去趋势分析有助于研究中风后运动变异性和多重分形的变化。需要进一步的研究来验证和推广其临床应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5fc/9388820/e2b00ee6637b/fneur-13-893999-g0001.jpg

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