Our article “Numerical-Optimal-Control-Compliant Muscle Model for Electrically Evoked Contractions” has just been accepted for publication in IEEE Transactions on Medical Robotics and Bionics!
In this work, we adapted a physiological muscle model to make it compatible with gradient-based optimization. This allows us to predict skeletal muscle forces in response to electrical stimulation within an optimal control framework. We identified the model’s parameters using experimental torque data from electrically evoked isometric contractions of the quadriceps muscles of three individuals with spinal cord injury at various knee angles.
The result?
👉 A model that accurately predicts knee torques
👉 A foundation for optimizing stimulation patterns to better control evoked muscle force and movements
This study is a first step toward personalized, model-based control of functional electrical stimulation – opening new possibilities for movement assistance and rehabilitation technologies.
Access our paper at https://ieeexplore.ieee.org/document/11084991
