Classical and adaptive control of ex vivo skeletal muscle contractions using Functional Electrical Stimulation (FES)

Abstract

Functional Electrical Stimulation is a promising approach to treat patients by stimulating the peripheral nerves and their corresponding motor neurons using electrical current. This technique helps maintain muscle mass and promote blood flow in the absence of a functioning nervous system. The goal of this work is to control muscle contractions from FES via three different algorithms and assess the most appropriate controller providing effective stimulation of the muscle. An open-loop system and a closed-loop system with three types of model-free feedback controllers were assessed for tracking control of skeletal muscle contractions: a Proportional-Integral (PI) controller, a Model Reference Adaptive Control algorithm, and an Adaptive Augmented PI system. Furthermore, a mathematical model of a muscle-mass-spring system was implemented in simulation to test the open-loop case and closed-loop controllers. These simulations were carried out and then validated through experiments ex vivo. The experiments included muscle contractions following four distinct trajectories: a step, sine, ramp, and square wave. Overall, the closed-loop controllers followed the stimulation trajectories set for all the simulated and tested muscles. When comparing the experimental outcomes of each controller, we concluded that the Adaptive Augmented PI algorithm provided the best closed-loop performance for speed of convergence and disturbance rejection.

Electrical stimulation therapy for peripheral nerve injury

“…The results have shown that, In high-frequency stimulation, VL with more fast muscle fibers was tired faster than APB with more slow muscle fibers, and the treatment time should not exceed 14-16 min (85). Jaramillo Cienfuegos et al (86) have used a proportional integral (PI) controller to achieve classical and adaptive control of FES for isolated skeletal muscle contraction, which provided the best closed-loop performance for contraction speed and antiinterference. Future research should use algorithms to control FES muscle contraction, focusing on different stimulation sites.…”