Kinematic analysis and biomechanical modeling of cyclists' real-time motion capture data with anthropometric measurements
2022
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Advisor: Doç. Dr. Özgür Karaduman
Abstract (EN)
Individuals are always tempted to become professionals as the conditions for practicing and dealing with any sport in a country improve. Because as conditions improve, there is an inexorable desire to participate in more sports and perform better. However, the increased use in sports activities may result in a few issues. These are primarily injuries and sports-related injuries. Even the slightest deviation from proper technique can result in injury or reduce athlete performance. Among the issues encountered are a decrease in the body's efficiency rate as a result of incorrect sports practice or vehicle misuse, excessive loss of power, and a failure to detect mistakes made during sports. The study will look into the suitability of optimal angle values with individual anthropometric variables (static method) and motion capture technology (dynamic method) for optimizing the cyclist's position in his own race time. After the markers were placed, the suitability of the angles found according to the fixed interval values was determined, and using the analysis of the obtained data, the performance of professional or amateur athletes could be evaluated, it was possible to detect and thus correct driving errors depending on which driving technique the cyclist adopts (aggressive or comfortable), and it was possible to perform any biomechanical analysis and analysis. It has enabled the determination of sports training measures, research into the effects of digitalization on sports, and the development of a model for sports biomechanics research. The current findings of this study are important in improving a cyclist's performance by providing important information to sports medicine practitioners through data obtained by providing technical guidance to movements. The use of the bicycle, which is arranged according to the cyclist's anthropometric variables, reduces the load on the bicycle to a minimum without disturbing the blood flow, preventing hand numbness, low back pain, and so on. It is thought to help reduce the risk of complaints and cycling injuries significantly.
Author
Dr. Kübra Elif Tozkoparan
How to Cite
Kübra Elif Tozkoparan (Master Thesis). Kinematic analysis and biomechanical modeling of cyclists' real-time motion capture data with anthropometric measurements, 2022, Fırat University.
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