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Modeling Neuromuscular Control System of Human Arm for Trajectory Tracking Using an Optimal Controller

Asghari, Mehran | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 49373 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Behzadipour, Saeed; Narimani, Roya
  7. Abstract:
  8. The behavior movement of human is fundamentally concerned with the relationship between the central nervous system of motor control، and musculoskeletal system of a human. Optimal control was employed to relate these structures together. Movement is one of the important part of human life، CNS is important because it has the fundamental role in the movement. Investigators believe that CNS is learned by iteration movements from childhood and finally it chooses the movement that makes a cost function minimum value of itself. Researching for CNS modeling grows in recent years on the different part of human body. Because upper body have less difficulty in movements، it is more useful for CNS modeling. Since Parkinson and stroke patients are growing up، this is more important to prob haw CNS is working. This project proposed a model for the central nervous and musculoskeletal system to predict trajectory in iterative planning movements. In this model، a function is proposed to shows deficients of patient، and model can predict the trajectory of the movements in the upper body of a human. For this goal، we got some experiment from stroke patients in arm movements، for these experiments we use camera and marker. These experiments are used to probe deficient of a patient and used for model verification. First of all، we use this model for healthy people. This model uses musculoskeletal model and initial and final point to predicting the trajectory of participate hands. This model has 2 separate section، musculoskeletal system، and central nervous system. The musculoskeletal model is 2-DOF and used for planning movements. Optimal control employees for modeling central nervous system. It can communicate between the musculoskeletal system and nervous system with the cost function. Dynamic problem solved with VE method. Then this model is propered for stroke patients. Characteristics of stroke modeled as a muscle stiffness and the specific coefficient of muscles in the cost function. Stroke patient distinguished from healthy person by parameters of the nervous system in the model. It can make a new approach to exploration in the amount of efficiency in person
  9. Keywords:
  10. Optimal Control ; Neural System Modeling ; Stroke ; Hand Motion ; Musculoskeletal System ; Neuromusculoskeletal Model ; Trajectory Tracking

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