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A Mathematical Method for Electromyography Analysis of Muscle Functions during Yogasana

机译:瑜伽期间肌肉功能肌电学分析的数学方法

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Context: For the past few decades, the number of people practicing yoga is increasing in number. Yogasanas need smooth body movements in the process of attaining defined postures that the person must hold on to activate specific muscles of the body related to that asana. Yogasanas should be performed with perfection to derive maximum benefits. Objective: The objective of this study was to introduce a mathematical method to understand muscle functionalities while doing Yogasanas. Materials and Methods: Used Delsys surface electromyography (sEMG) – Trigno? (Delsys Inc.) sensors for data recording and analyzing muscle activation patterns. Results: Performance analysis was quantified using normalized sEMG signals. The sEMG data during final posture were fit to a straight line using linear regression analysis. Conclusion: The results suggested that the slope of the best fit line is a good metric for monitoring the muscle activity during Yoga performance. The advantages of this method are the slope of the line is a good indicator for monitoring the muscle activity while doing Yogasana and the method suggested in this study can be extended for analyzing other asanas as well.
机译:背景:在过去的几十年里,练习瑜伽的人数在数量上增加。 yogasanas需要在获得所定义的姿势的过程中需要平稳的身体运动,即该人必须坚持以激活与该Asana相关的身体的特定肌肉。 yogasanas应该用完美的完美来实现最大的效益。目的:本研究的目的是引入一种数学方法,以在做瑜伽时了解肌肉功能。材料和方法:二手熟光表面肌电图(SEMG) - Trigno? (Delsys Inc.)传感器,用于数据记录和分析肌肉激活模式。结果:使用归一化SEMG信号量化性能分析。在最终姿势期间的SEMG数据使用线性回归分析适合直线。结论:结果表明,最佳拟合线的斜率是监测瑜伽性能期间肌肉活动的良好指标。该方法的优点是线的斜率是用于监测肌肉活动的良好指标,同时进行瑜伽症,并且可以延长该研究所提出的方法,以分析其他asanas。

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