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重度膝骨关节炎患者行走时的肌肉共同激活模式。

Muscle co-activation patterns during walking in those with severe knee osteoarthritis.

作者信息

Hubley-Kozey Cheryl, Deluzio Kevin, Dunbar Michael

机构信息

School of Physiotherapy, Dalhousie University, 5869 University Avenue, Halifax NS, Canada B3J 3H5.

出版信息

Clin Biomech (Bristol). 2008 Jan;23(1):71-80. doi: 10.1016/j.clinbiomech.2007.08.019. Epub 2007 Nov 1.

Abstract

BACKGROUND

Sensory and motor impairments have been found for those with knee osteoarthritis; however, how these impairments are manifested during functional movements such as walking is not well established. A few studies suggest an increase in co-activity among lower limb muscles. The objective of this study was to characterize the neuromuscular patterns of knee joint muscles during walking for those with severe knee osteoarthritis using pattern recognition techniques on the entire waveform.

METHODS

Fifty-one subjects received a gait assessment within one-week prior to total knee replacement surgery. Subjects walked along a 6-m walkway at their preferred walking speed while surface electromyograms from seven muscles were recorded. The electromyographic data were entered into a pattern recognition procedure that captured both the amplitude and shape characteristics of electromyographic waveforms. ANOVA models tested whether differences existed both among and within muscle groups for these waveform characteristics.

FINDINGS

Four principal patterns explained 97% of the variance in the waveform data, with principal pattern one explaining 86% of the total variance. There were statistically significant differences (P<0.05) among muscle sites for all principal pattern scores. The analyses supported the hypothesis that similarities existed in patterns among muscles from different groups indicating (i) a general co-activity pattern and (ii) differential recruitment between muscles within a muscle group.

INTERPRETATION

In addition to the roles during impact loading and propulsion, the muscle responses were consistent with attempts to (i) decrease medial knee joint loading, (ii) decrease peak knee joint loading during push off and (iii) increase stiffness during stance phase to improve joint stability. The technique employed provides a novel approach to quantify synergistic co-activity.

摘要

背景

已发现膝关节骨关节炎患者存在感觉和运动障碍;然而,这些障碍在诸如行走等功能运动中如何表现尚未明确。一些研究表明下肢肌肉的共同激活增加。本研究的目的是使用基于整个波形的模式识别技术,对重度膝关节骨关节炎患者行走时膝关节肌肉的神经肌肉模式进行特征描述。

方法

51名受试者在全膝关节置换手术前一周内接受步态评估。受试者以其偏好的步行速度沿着6米长的通道行走,同时记录七块肌肉的表面肌电图。将肌电图数据输入到一个模式识别程序中,该程序可捕捉肌电图波形的幅度和形状特征。方差分析模型检验了这些波形特征在肌肉组之间和组内是否存在差异。

结果

四种主要模式解释了波形数据中97%的方差,其中主要模式一解释了总方差的86%。所有主要模式得分在肌肉部位之间存在统计学显著差异(P<0.05)。分析支持了以下假设:不同组肌肉之间的模式存在相似性,表明(i)一种普遍的共同激活模式,以及(ii)肌肉组内各肌肉之间的不同募集情况。

解读

除了在冲击负荷和推进过程中的作用外,肌肉反应还与以下尝试一致:(i)减少膝关节内侧负荷,(ii)在蹬离时减少膝关节峰值负荷,以及(iii)在站立期增加刚度以改善关节稳定性。所采用的技术提供了一种量化协同共同激活的新方法。

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