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Past Projects

 

Minimizing the Effort of a 2D Model of Human Gait by Optimizing Joint Torque Controller Gains

Ben Baldwin

One of the steps toward understanding human gait is to create simplified models of the human body and then to simulate those models.  This project applies a random perturbation force that grows steadily over time to the torso of a torque driven 2D model to investigate how particular joint gains affect the overall model effort and walking time. Specifically, the goal is to determine whether or not there is an optimum set of joint torques that maintains a satisfactory walking time while simulataneously minimizing the overall model effort.  The contestation put forth is that gains will increase to a point, beyond which, additional increases will not yield better results.  This is investigated with a model that is driven by torques generated by a simple proportional-derivative controller.  The gains of the controller are the same for each joint (two gain model), allowing a three dimensional representation of the effort or walk time on one axis plotted against the proportional gain and the derivative gain on the other two axes.  These plots can be generated either by a grid method, which runs the model at predetermined intervals of proportional and derivative control, or by using a more sophisticated optimization routine such as particle swarm optimization (PSO).  PSO is also used to determine if using separate gains for each joint (six gain model) yields a lower effort than the two gain model.  The exploration of the six gain model precludes plotting the results.  Therefore, only the optimum gains found by the routine are shown as the output.


 

Gait Optimization using GPOPS-II

Milad Zarei

I used GPOPS-II [Matlab Optimal Control Software] to optimize squared torques of one DOF pendulum problem to evaluate GPOPS-II to be used in Human Motion & Control Lab. I am currently working to optimize 2D gait problem using GPOPS-II. The optimization problem that I am talking about is to find cyclic gait with a prescribed speed and cycle time, minimizing the integral of squared torques. The initial guess is static standing, which was easy to solve. The problem is very nonlinear because of foot-ground contact in the gait model.


 

Methods for Identification of Feedback Control During Standing 

Samin Askarian

The mechanism of human balance control could be studied by a direct approach (DA) in which a relationship between observed joint moments and potential feedback signals was identified. However, the human balance system operates in a closed loop and this would bias the estimated controller towards the inverse of the plant, i.e. inverse multibody dynamics. The aim of this work was to validate the direct approach method for identification of feedback control in human standing and to study the effect of platform perturbation amplitude on the accuracy of the DA identification technique. Furthermore, indirect approach (IA) was used for the same system to remove the systematic error in gain estimation. Test data were obtained from a simulation in which the plant was modeled as a double inverted pendulum, perturbed with horizontal accelerations at the base to mimic a test protocol for human standing balance.


 

Validation of an Accelerometry Based Method of Human Gait Analysis

Obinna Nwanna

Gait analysis is the quantification of locomotion. Understanding the science behind the way we move is of interest to a wide variety of fields. Medical professionals might use gait analysis to track the rehabilitation progress of a patient. An engineer may want to design wearable robotics to augment a human operator. Use cases even extend into the sport and entertainment industries. Typically, a gait analysis is preformed in a highly specialized laboratory containing cumbersome expensive equipment. The process is tedious and requires specially trained operators. Continued development of small and cheap inertial measurement units (IMUs) offer an alternative to current methods of gait analysis. These devices are portable and simple to use allowing gait analysis to be done outside the laboratory in real world environments. Unfortunately, while current IMU based gait analysis systems are able to quantify a subject’s joint kinematics they are unable to measure joint kinetics as could be done in a traditional gait laboratory. A novel musculoskeletal model-based movement analysis system using accelerometers has been developed that can calculate both joint kinematics and joint kinetics. The aim of this master’s thesis is to validate this accelerometry based gait analysis against the industry standard optical motion capture gait analysis.