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Motor unit synchronization during fatigue: A novel quantification method

机译:疲劳过程中的运动单元同步:一种新颖的量化方法

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Motor unit (MU) synchronization is the result of commonality in the pre-synaptic input to MUs. Previously proposed techniques to estimate MU synchronization based on invasive and surface electromyography (sEMG) recordings have been, respectively, limited by the analyzed MU population size and influence of changes in muscle fibre conduction velocities (MFCVs). The aim of this paper was to evaluate a novel descriptor of MU synchronization on a large MU population, and to minimize its dependency on MFCV. The method is based on the asymmetry of MU action potentials, causing synchronized MU action potentials to skew the monopolar sEMG signal distribution. The descriptor was the skewness statistic used on sub-band filtered monopolar sEMG signals (sub-band skewness). The method was evaluated using simulated signals and its performance was evaluated in terms of bias and sensitivity of the sub-band skewness quantifying the MU synchronization level. The best sensitivity was obtained using sub-band filtering at scale 5 (Mexican hat wavelet). The sensitivity was in general about 0.1 units per 5% MU synchronization level. Changes in MFCV had a minimal influence, and caused at most a 5% deviant MU synchronization quantification level. A halved recruitment level had higher bias and a 20% lower sensitivity. Increased firing rate (14-34 Hz) reduced the sensitivity about 50%. The sensitivity of the descriptor was robust to noise, and different volume conduction properties. It should be noted that the sub-band skewness comprises a subject-dependent component implying that only changes in MU synchronization level can be quantified.
机译:电机单元(MU)同步是MU的突触前输入中通用性的结果。先前提出的基于有创和表面肌电图(sEMG)记录估算MU同步的技术分别受到分析的MU种群大小和肌肉纤维传导速度(MFCVs)变化影响的限制。本文的目的是评估在大的MU群体上MU同步的新颖描述符,并最小化其对MFCV的依赖性。该方法基于MU动作电位的不对称性,导致同步的MU动作电位使单极sEMG信号分布偏斜。描述符是在子带滤波后的单极性sEMG信号上使用的偏斜度统计量(子带偏斜度)。使用模拟信号评估该方法,并根据量化MU同步水平的子带偏度的偏差和灵敏度评估其性能。使用等级5(墨西哥帽小波)的子带滤波可获得最佳灵敏度。灵敏度通常为每5%MU同步级别约0.1个单位。 MFCV的变化影响最小,最多导致5%的MU同步量化水平偏差。减半的招聘水平有更高的偏见,敏感性降低了20%。增加的发射速率(14-34 Hz)使灵敏度降低了约50%。描述子的灵敏度对噪声和不同的体积传导特性具有鲁棒性。应当注意的是,子带偏斜包括取决于对象的分量,这意味着只能量化MU同步水平的变化。

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