A system identification algorithm for a musculoskeletal system using an approximate expectation maximization (E-M) is presented. Effective control design for neuroprosthesis applications necessitates a well defined muscle model. A dynamic model of the lower leg with a fixed ankle is considered. The unknown parameters of the model are estimated using an approximate E-M algorithm based on knee angle measurements collected from an able-bodied subject during stimulated knee extension. The parameters estimated from the data are compared to reference values obtained by conducting experiments that separate the parameters in the dynamics from one another. The presented results demonstrate the capability of the proposed algorithm to identify the parameters of the dynamic model from knee angle measurements.
- Dynamic Systems and Control Division
Expectation Maximization Method to Identify an Electrically Stimulated Musculoskeletal Model
Ravichandar, H, Dani, A, Khadijah-Hajdu, J, Kirsch, N, Zhong, Q, & Sharma, N. "Expectation Maximization Method to Identify an Electrically Stimulated Musculoskeletal Model." Proceedings of the ASME 2015 Dynamic Systems and Control Conference. Volume 2: Diagnostics and Detection; Drilling; Dynamics and Control of Wind Energy Systems; Energy Harvesting; Estimation and Identification; Flexible and Smart Structure Control; Fuels Cells/Energy Storage; Human Robot Interaction; HVAC Building Energy Management; Industrial Applications; Intelligent Transportation Systems; Manufacturing; Mechatronics; Modelling and Validation; Motion and Vibration Control Applications. Columbus, Ohio, USA. October 28–30, 2015. V002T23A009. ASME. https://doi.org/10.1115/DSCC2015-9956
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