FES-induced musculoskeletal trajectory optimization with an adapted muscle model
Résumé
To increase efficiency in Functional Electrical Stimulation (FES) assisted activities, simulation can be used to explore optimized stimulation patterns and predict muscle forces and joint kinematics. In this sense, trajectory optimization can efficiently manage biomechanics and FES related constraints, ensuring the optimal activation of required muscles for specific tasks. However, the intricate mechanisms from calcium ions regulation to cross-bridge mechanics, muscle contraction and multibody systems lead to complex system’s dynamics. Here, we first demonstrate the feasibility of using trajectory optimization with an FES-stimulated muscle model to optimize a biomechanical task in simulation.
We demonstrate the feasibility of using trajectory optimization with an adapted Functional Electrical Stimulation (FES)-stimulated muscle model to optimize biomechanical tasks in simulation. We used numerical optimal control to explore optimized stimulation patterns and predict muscle forces and joint kinematics with optimal activation of the muscles required for two specific tasks: torque production and reaching movement.
We adapted an existing model to account for non-consecutive trains of pulses and demonstrated the potential of the proposed method to be used in trajectory optimization problems. Although the results are consistent with the literature, experimental validation is necessary to confirm the parameters used in the model and reevaluate the predicted forces. Future work should improve our model to account for muscle fatigue and force-velocity relationships. It is of our interest to use the proposed methodology to explore optimal control in FES-cycling stimulation.
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