Activation Primitive-driven Musculoskeletal Modelling of Human Locomotion: Towards Model-based Control of Bionic Legs

Powered prostheses have the potential to improve the quality of life of lower limb amputees, by improving their mobility. Myoelectric control systems that employ electromyograms (EMGs) as driving control signal have shown promising performances. However, EMG electrodes are susceptible to noise and movement artefact and may decrease myocontrolled prostheses overall robustness and stability. EMG-dependence in prosthetic controllers can be relaxed by exploiting the concept of muscle synergy and modularity.
We propose a solution based on neuromusculoskeletal modelling including a numerical model that simulates the role of neural synergies in the recruitment of skeletal muscles. The aim is to devise advanced model-based control strategies with minimal EMG-dependence to ultimately improve physical interaction between the user and a powered prostheses during dynamic motor tasks.