Finding Centre of Gravity of Yoga Asana Postures to Support Self-Assisted Yoga Practice
K. Ponmozhi 1, P. Deepa Lakshmi 2, V. Vallinayagi3
1K. Ponmozhi, Department of Computer Applications, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
2P. Deepa Lakshmi, Department of Computer Science Engineering Computing, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
3V. Vallinayaki, PG Research, Assistant Professor, Department of Computer Science, Sri Sarada College for Women, Tirunelveli (Tamil Nadu), India.
Manuscript received on 02 December 2019 | Revised Manuscript received on 20 December 2019 | Manuscript Published on 31 December 2019 | PP: 706-711 | Volume-8 Issue-4S2 December 2019 | Retrieval Number: D11141284S219/2019©BEIESP | DOI: 10.35940/ijrte.D1114.1284S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Self-assisted yoga practice should ensure safety. Being in a wrong posture while doing practice may cause problems like fall or fractures in the bones. Practitioners of activities like yoga, sports etc. should maintain correct postures all through their practice. Maintaining a correct posture is influenced by Centre of Gravity whose location is based on distributing the entire body weight evenly for stability. In this paper, we propose a method to find the Centre of Gravity of any asana sequence. The location of Centre of Gravity will be used by the assistive system to instruct the practitioner how to alter their postures to avoid fall and enable to take-up perfect practice. Motion capture systems will give the details in the form of Biovision hierarchy format, from which the coordinate values of human joints can be accessed. Based on the segmentation method, whole body Centre of Gravity is calculated. We have used Vrikshasana for our experiment and yoga posture data for ten participants are used to find the Centre of Gravity variations. Data for two trails were acquired. CM Variations in segments like thigh, angle are calculated. From the results the instructors may find whether ankle or thigh’s position should be changed to maintain correct posture.
Keywords: Assisted Living, Bio- Mechanics, Bio Vision Hierarchy ,Centre of Gravity, Segmented Method, Yoga.
Scope of the Article: Computer Vision