Identification of Human Control During Walking
This project focuses on a combination of experimental data and modeling to identify the control schemes humans use in gait during locomotion. We are particularly interested in mapping the identified controllers to powered prosthetic devices. We start by collecting typical gait data (kinematics and kinetics) of a person walking or running while being perturbed longitudinally and laterally with pseudo-random forces in a wide frequency spectrum. With the collected data we then make use of various optimization techniques and plant/controller structures to identify a controller employed by the subject. This controller is then used to inform the design of a controller for a powered prosthetic device which has different but similar sensors and actuators than the human.
Papers
An elaborate data set on human gait and the effect of mechanical perturbations
- Data Publication: https://peerj.com/articles/918
- Data Publication Preprint: https://peerj.com/preprints/700
- Publication Source Repository: https://github.com/csu-hmc/perturbed-data-paper
Quiet Standing Control Identification Methods Comparison [Draft]
- Publication Source Repository: https://github.com/csu-hmc/inverted-pendulum-sys-id-paper
Gait Control Direct Identification [Draft]
- Publication Source Repository: https://github.com/csu-hmc/gait-control-direct-id-paper
Data
Software
- GaitAnalysisToolKit: https://github.com/csu-hmc/GaitAnalysisToolKit
- Opty: https://github.com/csu-hmc/opty
Presentations
- SciPy 2015: "Optimal Control and Parameter Identification of Dynamical Systems with Direct Collocation and SymPy"
- ISB TGCS 2015: "Human standing control parameter identification with direct collocation"
Media
The following videos show a subject walking at various speeds while being perturbed by the treadmill belt.
0.8 m/s
1.2 m/s
1.6 m/s