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使用高阶统计量(高斯性和线性检验)研究胫前肌表面肌电图中与年龄相关的神经肌肉变化。

Age related neuromuscular changes in sEMG of m. Tibialis Anterior using higher order statistics (Gaussianity & linearity test).

作者信息

Siddiqi Ariba, Arjunan Sridhar P, Kumar Dinesh K

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:3638-3641. doi: 10.1109/EMBC.2016.7591516.

DOI:10.1109/EMBC.2016.7591516
PMID:28324992
Abstract

Age-associated changes in the surface electromyogram (sEMG) of Tibialis Anterior (TA) muscle can be attributable to neuromuscular alterations that precede strength loss. We have used our sEMG model of the Tibialis Anterior to interpret the age-related changes and compared with the experimental sEMG. Eighteen young (20-30 years) and 18 older (60-85 years) performed isometric dorsiflexion at 6 different percentage levels of maximum voluntary contractions (MVC), and their sEMG from the TA muscle was recorded. Six different age-related changes in the neuromuscular system were simulated using the sEMG model at the same MVCs as the experiment. The maximal power of the spectrum, Gaussianity and Linearity Test Statistics were computed from the simulated and experimental sEMG. A correlation analysis at α=0.05 was performed between the simulated and experimental age-related change in the sEMG features. The results show the loss in motor units was distinguished by the Gaussianity and Linearity test statistics; while the maximal power of the PSD distinguished between the muscular factors. The simulated condition of 40% loss of motor units with halved the number of fast fibers best correlated with the age-related change observed in the experimental sEMG higher order statistical features. The simulated aging condition found by this study corresponds with the moderate motor unit remodelling and negligible strength loss reported in literature for the cohorts aged 60-70 years.

摘要

胫骨前肌(TA)表面肌电图(sEMG)的年龄相关变化可能归因于力量丧失之前的神经肌肉改变。我们使用胫骨前肌的sEMG模型来解释与年龄相关的变化,并与实验性sEMG进行比较。18名年轻人(20 - 30岁)和18名老年人(60 - 85岁)在最大自主收缩(MVC)的6个不同百分比水平下进行等长背屈,并记录他们胫骨前肌的sEMG。使用sEMG模型在与实验相同的MVC下模拟神经肌肉系统中6种不同的年龄相关变化。从模拟和实验性sEMG中计算频谱的最大功率、高斯性和线性测试统计量。对sEMG特征中模拟和实验性年龄相关变化进行α = 0.05的相关性分析。结果表明,运动单位的丧失通过高斯性和线性测试统计量来区分;而功率谱密度(PSD)的最大功率区分了肌肉因素。运动单位丧失40%且快肌纤维数量减半的模拟条件与实验性sEMG高阶统计特征中观察到的年龄相关变化相关性最好。本研究发现的模拟衰老条件与文献中报道的60 - 70岁人群适度的运动单位重塑和可忽略不计的力量丧失相符。

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