Journal of neuroengineering and rehabilitation
From simulation to stimulation: a predictive synergy-based control strategy for functional electrical stimulation cycling in a person with spinal cord injury
By Peres AB, Carmona GG, de Sousa ACC and 1 others.
Abstract
Background
Functional electrical stimulation (FES) cycling stimulation strategies are often derived from heuristics, or able-bodied kinematics and electromyography, which may be unsafe and non-representative for people with complete spinal cord injury. Optimally controlled predictive musculoskeletal simulations with synergy implementation offer a way to generate individualized, physiologically plausible muscle trajectories without prior experimental data. Building on a previous proof of concept, this study developed and experimentally validated a simulation-derived stimulation strategy for FES cycling.
Methods
A two-stage musculoskeletal predictive simulation framework was implemented using OpenSim Moco. First, a speed-tracking optimal control problem optimized the model's kinematics and individual muscle trajectories. Second, muscle excitations were decomposed into functional synergies using non-negative matrix factorization, producing coordinated activation patterns for quadriceps and hamstrings muscle groups. Subject-specific constraints were incorporated into the model. The resulting activation profile was then processed and converted to a crank-angle lookup table for real-time control. Experimental validation was conducted in one subject with complete spinal cord injury (SCI), comparing the simulation-derived control signal (CS) with a refined empirical bang-bang (BB) protocol used in the Cybathlon 2024 edition.