Type-2 fuzzy logic based analysis and simulation of human motions
2013
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Advisor: Yrd. Doç. Dr. Mehmet Karaköse
Abstract (EN)
Especially nowadays, there is a large work area for structural, physical and mathematical modelling studies of human movement. The formation of these models, which can be used in many areas such as robotic, computer vision and biomechanical analysis, is a difficult problem due to a high degree of freedom, large data sets and the requirement of complex optimization and control techniques. Although there are several studies using image processing, artificial intelligence and smart techniques for modelling of human movement in the literature. This thesis represents two significant contributions such as the development of image processing based defuzzication methods for type-2 fuzzy systems and fuzzy logic-based modelling and control of human movement, and gives a detailed analysis on related issues. In the context of this thesis, first of all, a new defuzzication method is suggested to reduce the complexity by analyzing complexity of type-2 fuzzy systems. The method which is verified by simulation studies produces effective results more than current techniques. Secondly, control and analysis studies through this model are confirmed by experimental results by giving a two-dimensional and five-segment human model to analyze human movement. The advantages obtained by using type-2 fuzzy systems are clearly provided in control approach basically using fuzzy systems. Modelling, control and analysis of walking, lifting and weightlifting movements are done and strength and at the same time, torque modulation are observed by considering the mass of body components. As it can be seen in the results using experimental data; proposed control component and model framework represent simple, solid, effective and quick approach. As a conclusion, high accuracy defuzzication method for type-2 fuzzy systems and an approach for modelling and analysis of human movement using fuzzy systems are suggested in the context of this thesis, and the results obtained are supported by several scientific publications.
Author
Dr. Semiha Makinist
How to Cite
Semiha Makinist (Master Thesis). Type-2 fuzzy logic based analysis and simulation of human motions, 2013, Fırat University.
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