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Table of contents
1 Healthy and decient gait
1.1 Classication of gaits
1.2 Motor control
1.2.1 Basal ganglia
1.3 Parkinson’s disease
1.3.1 Anatomical pathology of Parkinson’s disease
1.3.2 Models of neuron circuitry with implied Parkinson’s disease
1.4 Conclusion
2 Central pattern generators
2.0.1 Spinal cord and descending control
2.0.2 Feedback signals of motor control
2.1 Models of central pattern generators
2.1.1 Microscopic models
2.1.2 Mesoscopic models
2.1.3 Macroscopic models
2.2 Application of CPG models
2.3 Our model of central pattern generator
2.3.1 Overall CPG architecture
2.3.2 Rhythm Generator layer
2.3.3 The other layers
2.4 Controller architecture
2.5 Equilibrium control
2.5.1 Reex controller
2.5.2 Arm control
2.6 Conclusion
3 Musculoskeletal model of human body
3.1 GAIT2DE, a simple musculoskeletal model
3.2 Musculoskeletal model in OpenSim
3.3 Modications to the musculoskeletal model
3.3.1 Simplications of the model
3.3.2 Extensions to the model
3.4 Connecting controller to the model
3.4.1 Implementation of the platform
3.4.2 Biological feedback
3.5 Conclusion
4 Simulated gait analysis
4.1 Gait cycle
4.2 Experimental data
4.3 Optimization of controller parameters
4.3.1 Parameter optimization methods
4.3.2 Target functions
4.4 Correlation gait evaluation criterion
4.4.1 Cross-correlation
4.5 Conclusion
5 Results of neuro-musculoskeletal simulations
5.1 CPG control of a single joint
5.1.1 Movement with constant speed
5.1.2 Movement with variable speed
5.2 Joint-targeted CPG controller
5.2.1 Walking with constant speed
5.2.2 Walking with variable speed
5.3 Muscle-targeted CPG controller
5.3.1 Simulation with GAIT2DE model
5.3.2 Simulation with OpenSim model
5.3.3 Disrupted gait
5.4 Phase-targeted CPG controller
5.5 Balance controller
5.6 Conclusion
Bibliography
