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A Mathematical Method for Electromyography Analysis of Muscle Functions during Yogasana

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 performe...

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Detalles Bibliográficos
Autores principales: Devaraju, V, Ramesh, Ashitha Besagarahalli, Alva, K Kshamith, Debur, V Ramesh, Omkar, SN
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6746055/
https://www.ncbi.nlm.nih.gov/pubmed/31543633
http://dx.doi.org/10.4103/ijoy.IJOY_63_18
Descripción
Sumario: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.