The goal of the optimisation is for the model (with the arm support, if necessary) to successfully complete a series of movement simulations.
The movements are able-bodied movements from our database. The model is one of the virtual patients. Given a set of muscles under sFES, the simulation tries to find the required activation patterns for muscles under voluntary control, and sFES patterns for muscles under stimulation that will produce the desired motion as well as possible. The simulation has the option of adding an arm support, in which case it also optimises the positioning and assistance level of the support. The process is repeated for all desired motions, and all candidate sFES muscle sets, until the optimal set is identified.
[ ] Find set of desired movements
[ ] Change model parameters to match one of the virtual patients
[ ] Set up optimisation cost function and constraints
The goal of the optimisation is for the model (with the arm support, if necessary) to successfully complete a series of movement simulations.
The movements are able-bodied movements from our database. The model is one of the virtual patients. Given a set of muscles under sFES, the simulation tries to find the required activation patterns for muscles under voluntary control, and sFES patterns for muscles under stimulation that will produce the desired motion as well as possible. The simulation has the option of adding an arm support, in which case it also optimises the positioning and assistance level of the support. The process is repeated for all desired motions, and all candidate sFES muscle sets, until the optimal set is identified.