Maghsoudi Arash, Rahatabad Fereidoon Nowshiravan, Rangraz Parisa
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
J Med Signals Sens. 2020 Jul 3;10(3):185-195. doi: 10.4103/jmss.JMSS_49_19. eCollection 2020 Jul-Sep.
As people get older, muscles become more synchronized and cooperate to accomplish an activity, so the main purpose of this research is to determine the relationship between changes in age and the amount of muscle synergy. The presence of muscle synergies has been long considered in the movement control as a mechanism for reducing the degree of freedom of the motor system.
By combining these synergies, a wide range of complex movements can be produced. Muscle synergies are often extracted from the electromyogram (EMG) signal. One of the most common methods for extracting synergies is the nonnegative matrix factorization. In this research, the EMG signal is obtained from individuals from different age groups (namely 15-20 years, 25-30 years, and 35-40 years), and after preprocessing, the muscular synergies are extracted. By processing and studying these synergies.
It was observed that there is a significant difference between the muscular synergy of different age groups. Furthermore, there was a significant difference in the mean value of synergy coefficients in each group, especially in motions that were accompanied by force.
This result candidates this parameter as a biomarker to differentiate and recognize the effects of age on the individual's muscular signal. In the best case, using the synergy tool, classification of the age of persons can be done by 77%.
随着人们年龄的增长，肌肉变得更加协调并协同完成一项活动，因此本研究的主要目的是确定年龄变化与肌肉协同作用量之间的关系。在运动控制中，长期以来一直认为肌肉协同作用是一种减少运动系统自由度的机制。
通过组合这些协同作用，可以产生各种各样的复杂运动。肌肉协同作用通常从肌电图（EMG）信号中提取。提取协同作用最常用的方法之一是非负矩阵分解。在本研究中，从不同年龄组（即15 - 20岁、25 - 30岁和35 - 40岁）的个体获取EMG信号，经过预处理后，提取肌肉协同作用。通过对这些协同作用进行处理和研究。
观察到不同年龄组的肌肉协同作用存在显著差异。此外，每组协同系数的平均值也存在显著差异，特别是在伴有力量的运动中。
该结果使这个参数有望成为区分和识别年龄对个体肌肉信号影响的生物标志物。在最佳情况下，使用协同作用工具，可以对77%的人的年龄进行分类。
