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使用高密度肌电图评估躯干伸肌耐力及其与动作电位传导速度和频谱参数的关系。

Trunk extensor muscle endurance and its relationship to action potential conduction velocity and spectral parameters estimated using high-density electromyography.

机构信息

Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, The Netherlands.

TNO, Leiden, The Netherlands.

出版信息

J Electromyogr Kinesiol. 2023 Dec;73:102830. doi: 10.1016/j.jelekin.2023.102830. Epub 2023 Oct 12.

Abstract

Trunk extensor muscle fatigue typically manifests as a decline in spectral content of surface electromyography. However, previous research on the relationship of this decline with trunk extensor muscle endurance have shown inconsistent results. The decline of spectral content mainly reflects the decrease in average motor unit action potential conduction velocity (CV). We evaluated whether the rate of change in CV, as well as two approaches employing the change in spectral content, are related to trunk extensor muscle endurance. Fourteen healthy male participants without a low-back pain history performed a non-strictly controlled static forward trunk bending trial until exhaustion while standing. For 13 participants, physiologically plausible CV estimates were obtained from high-density surface electromyography bilaterally from T6 to L5. Laterally between L1 and L2, the linear rate of CV change was strongly correlated to endurance time (R = 0.79), whereas analyses involving the linear rate of change in spectral measures showed a lower (R = 0.38) or no correlation. For medial electrode locations, estimating CV and its relationship with endurance time was less successful, while the linear rate of change in spectral measures correlated moderately to endurance time (R = 0.44; R = 0.56). This study provides guidance on monitoring trunk extensor muscle fatigue development using electromyography.

摘要

躯干伸肌疲劳通常表现为表面肌电图频谱含量下降。然而,先前关于这种下降与躯干伸肌耐力关系的研究结果并不一致。频谱含量的下降主要反映了平均运动单位动作电位传导速度(CV)的降低。我们评估了 CV 的变化率以及两种利用频谱含量变化的方法是否与躯干伸肌耐力有关。14 名无腰痛史的健康男性参与者在站立位进行非严格控制的静态向前躯干弯曲试验,直至力竭。对于 13 名参与者,从 T6 到 L5 双侧高密度表面肌电图获得了生理上合理的 CV 估计值。在 L1 和 L2 之间的外侧,CV 变化的线性速率与耐力时间强烈相关(R=0.79),而涉及频谱测量线性变化率的分析显示相关性较低(R=0.38)或无相关性。对于内侧电极位置,估计 CV 及其与耐力时间的关系不太成功,而频谱测量线性变化率与耐力时间中度相关(R=0.44;R=0.56)。本研究为使用肌电图监测躯干伸肌疲劳发展提供了指导。

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