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从末端力中提取个体肌肉力学作用。

Extraction of individual muscle mechanical action from endpoint force.

机构信息

Applied and Interdisciplinary Mathematics, University of Michigan, Ann Arbor, Michigan, USA.

出版信息

J Neurophysiol. 2010 Jun;103(6):3535-46. doi: 10.1152/jn.00956.2009. Epub 2010 Apr 14.

Abstract

Most motor tasks require the simultaneous coordination of multiple muscles. That coordination is poorly understood in part because there is no noninvasive means of isolating a single muscle's contribution to the resultant endpoint force. The contribution of a single motor unit to isometric tasks can, however, be characterized using the spike-triggered averaging (STA) technique, applied to a single motor unit's spike train. We propose that a technique analogous to STA, which we call electromyogram (EMG)-weighted averaging (EWA), can be applied to surface EMGs to extract muscle mechanical action from the natural endpoint force fluctuations generated during steady isometric contraction. We demonstrate this technique on simultaneous recordings of fingertip force and surface EMG from the first dorsal interosseous (FDI) and extensor indicis (EI) of humans. The EWA direction was approximately the same across a wide range of fingertip force directions, and the average EWA direction was consistent with mechanical action direction of these muscles estimated from cadaveric and imaging data: the EWA directions were 193 +/- 2 degrees for the FDI and 71 +/- 5 degrees for the EI (95% confidence). EWA transient behavior also appears to capture temporal characteristics of muscle force fluctuations with peak force time and general waveform shape similar to that of the associated spike-triggered averages from single motor units. The EWA may provide a means of empirically characterizing the complex transformation between muscle force and endpoint force without the need for invasive electrode recordings or complex anatomical measurements of musculoskeletal geometry.

摘要

大多数运动任务都需要多个肌肉的协同协调。这种协调在一定程度上还没有得到很好的理解,部分原因是没有非侵入性的方法来分离单个肌肉对最终端点力的贡献。然而,使用尖峰触发平均(STA)技术可以对单个运动单位的尖峰序列进行特征描述,从而对等长任务中单个运动单位的贡献进行特征描述。我们提出,类似于 STA 的技术,我们称之为肌电图(EMG)加权平均(EWA),可以应用于表面 EMG,从在稳定等长收缩期间产生的自然端点力波动中提取肌肉机械作用。我们在人类第一背侧间骨(FDI)和食指伸肌(EI)的指尖力和表面 EMG 的同时记录上演示了该技术。EWA 方向在广泛的指尖力方向范围内大致相同,平均 EWA 方向与从尸体和成像数据估计的这些肌肉的机械作用方向一致:FDI 的 EWA 方向为 193 +/- 2 度,EI 的 EWA 方向为 71 +/- 5 度(95%置信区间)。EWA 的瞬态行为似乎也可以捕获肌肉力波动的时间特征,其峰值力时间和总体波形形状与单个运动单位的相关尖峰触发平均值相似。EWA 可能提供了一种在不需要侵入性电极记录或复杂的肌肉骨骼几何结构解剖测量的情况下,对肌肉力和端点力之间复杂转换进行经验特征描述的方法。

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