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首页> 外文会议>Annual rocky mountain bioengineering symposium >ANALYSIS OF NORMAL AND PATHOLOGICAL CONDITIONS OF BICEPS BRACHII MUSCLES IN ELDERLY POPULATION USING SEMG MODEL
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ANALYSIS OF NORMAL AND PATHOLOGICAL CONDITIONS OF BICEPS BRACHII MUSCLES IN ELDERLY POPULATION USING SEMG MODEL

机译：半型模型分析二头肌肱二头肌肌肉肌肉的正常和病理条件

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Models of surface electromyography (sEMG) signals are extensively used in muscle biomechanics to analyze and validate clinical investigation in healthy and pathological muscles of adult and elderly populations. sEMG is a noninvasive technique to measure electrical activity of skeletal muscles. In this work, an attempt has been made to analyze biceps brachii muscle in normal and pathological conditions for elderly people using modified sEMG model. Age associated changes such as reduction in number of motor units and ratio of type II fibers are already reported in the earlier model proposed by Arjunan et al. However, experimentally it was found that there is an increase in motor unit action potential duration (MUAPD) due to aging. This effect is incorporated in this present work to model sEMG signal. Influence of physiological changes such as loss of muscle fibers, increased fiber diameter variation and decreased MUAPD are also included in this sEMG model in myopathyic conditions. Features namely, root mean square (RMS), median frequency (MDF), entropy and fractal dimension (FD) is extracted from the signal in normal and pathological conditions. Results show that the modified sEMG model gives distinct values for both normal aging muscles and myopathic muscles. The corresponding variations in feature values are significant (p<0.05). The values of RMS, MDF and FD are found to be higher in myopathic conditions compared to normal aging. The description of the sEMG model, the method of analysis and the observations are presented in this work. It appears that this sEMG model can be used to analyze myopathic conditions in elderly populations.
机译：表面肌电图（SEMG）信号的模型广泛用于肌肉生物力学，分析和验证成人和老年人口的健康和病理肌肉中的临床调查。 SEMG是一种测量骨骼肌的电活动的非侵入性技术。在这项工作中，已经尝试在使用改进的SEMG模型的老年人的正常和病理条件下分析二头肌肌肉。在Arjunan等人提出的早期模型中已经报道了年龄相关变化，例如电机单元数量和II型纤维的比率。然而，实验结果发现，由于老化，电动机单元动作潜在持续时间（MUAPD）增加。在本现有的工作中并入这种效果以模拟SEMG信号。这种肌肉纤维损失，增加的纤维直径变化和降低的MuAPD的影响也包括在近视病症中的这种半模型中。特征即，从正常和病理条件下的信号中提取根均线（RMS），中值（MDF），熵和分形尺寸（FD）。结果表明，修改过的SEMG模型为正常老化肌肉和肌病肌肉提供了不同的值。特征值的相应变化很大（P <0.05）。与正常老化相比，发现抗体，MDF和FD的值较高。 SEMG模型的描述，分析方法和观察结果在这项工作中提出。似乎这个SEMG模型可用于分析老年人口中的肌病病症。

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