A proposal to analyze muscle fiber type composition in the soleus muscle of untrained subjects and sprinters using surface EMG signals.

IF 1.7 4区 医学 Q3 ENGINEERING, BIOMEDICAL
Venugopal Gopinath, Manuskandan Swaminathan Ramakrishnan, Remya R Nair, Ramakrishnan Swaminathan
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Abstract

Muscle fiber type proportion is a key determinant of fatigue, force generation, and functions of different skeletal muscles. Analysis of muscle fiber type composition aids in the assessment of athletic abilities and individualization of training methods. This study attempts to non-invasively analyze the muscle fiber type composition in the soleus (SOL) of untrained subjects (UT) and sprinters (SP) using surface electromyography-based time-frequency analysis. Signals are recorded from both groups during an isometric calf raise test with loads until fatigue. Filtered signals are segmented into epochs of 1-s duration and processed using a reassigned Morlet scalogram. Four time-frequency features namely averaged frequency, squared frequency bandwidth, averaged time, and squared time duration are extracted from the reassigned distribution and are subjected to linear regression analysis. A fiber-type-specific reassigned profile is noticed for UT and SP reflecting their distinct muscle composition during their non-fatigue and fatigue states. The regression parameters namely slope, intercept, and Adjusted R-square values are higher for the signals of SP indicating their fast-fatigue characteristics. Greater variation of features during fatigue is noticed in the signals of UT compared to SP. Among the features, the squared time duration exhibits the highest significance of p = 8.75E-07 in differentiating the signals of UT and SP during the non-fatigue state. Thus, the proposed approach is found suitable for analyzing the fiber type differences in both subject groups. This work may be further extended in sports biomechanics for studying the fiber-type transformations in muscles due to different athletic training strategies.

利用表面肌电图信号分析未经训练的受试者和短跑运动员比目鱼肌的肌肉纤维类型组成的建议。
肌纤维类型比例是不同骨骼肌疲劳、力产生和功能的关键决定因素。分析肌纤维类型组成有助于运动能力的评估和训练方法的个性化。本研究试图利用基于表面肌电图的时频分析,对未经训练的受试者(UT)和短跑运动员(SP)的比目鱼肌(SOL)的肌纤维类型组成进行无创分析。在负重至疲劳的等距抬小腿试验中,记录两组的信号。滤波后的信号被分割成1-s持续时间的时代,并使用重新分配的Morlet尺度图进行处理。从重新分配的分布中提取平均频率、频率带宽平方、平均时间和时间持续时间平方四个时频特征,并进行线性回归分析。在非疲劳状态和疲劳状态下,注意到UT和SP的纤维类型特异性重新分配剖面反映了它们不同的肌肉成分。SP信号的回归参数斜率、截距和调整后的r方值较大,表明其具有快速疲劳特性。与SP相比,UT信号在疲劳状态下的特征变化更大。其中,时间持续时间的平方在区分UT和SP非疲劳状态信号方面具有最高的显著性,p = 8.75E-07。因此,所提出的方法适用于分析两组受试者的纤维类型差异。这项工作可以进一步扩展到运动生物力学中,以研究不同运动训练策略导致的肌肉纤维类型转换。
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来源期刊
CiteScore
3.60
自引率
5.60%
发文量
122
审稿时长
6 months
期刊介绍: The Journal of Engineering in Medicine is an interdisciplinary journal encompassing all aspects of engineering in medicine. The Journal is a vital tool for maintaining an understanding of the newest techniques and research in medical engineering.
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