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Three Dimensional Control of Spine in Point to Point and Rhythmic Motion Using Central Pattern Generators

Layeghi, Hamed | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 43971 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Alasty, Aria; Salarieh, Hassan; Parnianpour, Mohammad
  7. Abstract:
  8. Low Back Pain (LBP) is one of the most common diseases in the world that according to the statistics 80% of people experience it at least once in their lifetime and a lot of money is spent for its therapy. Finding some methods for prediction and diagnosis of people with LBP from people without LBP helps to reduce these expenses. One of the most effective methods for diagnosing this problem, is the modeling and simulation of its skelomuscular system. However, because of the complications in modeling, simulation and neural control of human spine, it’s not been studied comprehensively. On the other hand, most of the numerical methods are based on optimization and approximation of muscle activation levels and/or on static models, where for assessing risks of injury in spine, using more accurate models which consider dynamic effects (if needed) and utilize neural controllers, seems more logical.
    As a result, in this study, it’s our intention to extract a comprehensive dynamic model for spine, and to analyze spine motion and control based on this model. Central Pattern Generators (CPG’s) are also used to model the neural behavior of body motion. To this end, a modified version of Kane’s method is presented and is then applied to derive the three dimensional dynamic equations of the system in vectorial form. In the next step, the optimal trajectories of the system for two and three dimensional movements are calculated by using some common cost functions and Fourier series estimation. Next, a special type of CPG is designed to produce the optimal trajectories obtained. For this purpose, a Hopf phase-radius oscillator is utilized to design a certain oscillator which could produce any kind of trajectory and stably and smoothly track the trajectory. Finally, by using the Feedback Linearization method, a controller is designed for tracking the optimal trajectory produced by CPG.
    The generated model has some advantages over other models that could attain more accuracy in fast dynamic movements in comparison to other models which are usually static. Some of the most important features of the model are its easy generalization capability, consideration of three dimensional dynamic effects such as gyroscopic effect, non-diagonal inertial matrix effects and the effect of lordosis in lateral bending and rotational movements of spine.
    The results for optimal trajectories show that using kinematic cost function leads to smoother and more logical answers. However, the basic dynamical analyses on the model indicate some error in the prediction of muscle forces. CPG and Controller simulations show that the closed loop system can follow any desired trajectory and is robust to disturbances which could be a suitable model of the body’s biomechanical behavior
  9. Keywords:
  10. Trajectory Optimization ; Central Pattern Generator ; Spine ; Feedback Linearization

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