A spike triggered averaging technique for high resolution assessment of single motor unit conduction velocity changes during fatiguing voluntary contractions

D. Farina, L. Arendt-Nielsen, R. Merletti, T. Graven‐Nielsen
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引用次数: 6

Abstract

In this paper we propose an improved spike triggered averaging technique for the assessment of control properties and conduction velocity (CV) of single motor units (MUs) during voluntary sub-maximal muscle contractions. The method is based on the detection of multi-channel surface EMG signals (with linear electrode arrays) and intramuscular recorded single MU action potentials (MUAPs). Intramuscular electrodes are inserted taking into account the MU structural properties (innervation zone and tendon locations, length of the fibers), assessed by the linear array surface EMG detection. A technique for intramuscular EMG signal decomposition is used to identify single MUAP trains. The MUAPs obtained from the intramuscular EMG decomposition algorithm are used to trigger and average the multi-channel EMG signals. CV of single averaged surface MUAPs is estimated by the use of advanced signal processing methods based on multi-channel recordings which allow to consistently reduce the variance of CV estimates with respect to traditional two channel delay estimators. The number of averaged potentials can thus be reduced, improving temporal resolution. The technique proposed is tested with recordings from the tibialis anterior muscle of 11 volunteers. It is shown that the method allows the assessment of CV changes (fatigue) of single MUs as small as 0.1 m/s with a limited number of averages (temporal resolution of 1-2 seconds), leading to a consistent improvement with respect to traditional surface EMG spike triggered averaging techniques. The method has potential usefulness in a number of basic and applied research fields.
一种高分辨率评估疲劳自发性收缩时单个运动单元传导速度变化的峰值触发平均技术
在本文中,我们提出了一种改进的脉冲触发平均技术,用于评估单个运动单元(MUs)在自主次最大肌肉收缩期间的控制特性和传导速度(CV)。该方法基于检测多通道表面肌电信号(线性电极阵列)和肌内记录的单MU动作电位(MUAPs)。考虑到MU的结构特性(神经支配区和肌腱的位置,纤维的长度),通过线性阵列表面肌电检测来评估肌内电极的插入。一种肌内肌电信号分解技术被用于识别单个MUAP序列。由肌内肌电信号分解算法得到的muap用于触发和平均多通道肌电信号。单平均表面muap的CV是通过使用基于多通道记录的先进信号处理方法来估计的,这种方法允许相对于传统的双通道延迟估计器一致地减少CV估计的方差。因此可以减少平均电位的数量,提高时间分辨率。这项技术通过11名志愿者的胫骨前肌记录进行了测试。结果表明,该方法可以在有限的平均次数(时间分辨率为1-2秒)下评估单个mu的CV变化(疲劳),最小值为0.1 m/s,与传统的表面肌电信号峰值触发平均技术相比,具有一致性的改进。该方法在许多基础和应用研究领域具有潜在的用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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