Finite Dimensional Approximation to Muscular Response in Force-Fatigue Dynamics using Functional Electrical Stimulation

TL;DR

This paper develops a finite dimensional approximation of muscular response models based on FES, enabling faster control optimization for muscle reinforcement and rehabilitation applications.

Contribution

It introduces a novel finite dimensional approximation of complex FES muscular response models, facilitating real-time control optimization.

Findings

Validated by experiments with force-fatigue models

Enables fast control optimization schemes

Supports development of smart electrostimulators

Abstract

Recent dynamical models, based on the seminal work of V. Hill, allow to predict the muscular response to functional electrostimulation (FES), in the isometric and non-isometric cases. The physical controls are modeled as Dirac pulses and lead to a sampled-data control system, sampling corresponding to times of the stimulation, where the output is the muscular force response. Such a dynamics is suitable to compute optimized controls aiming to produce a constant force or force strengthening, but is complex for real time applications. The objective of this article is to construct a finite dimensional approximation of this response to provide fast optimizing schemes, in particular for the design of a smart electrostimulator for muscularreinforcement or rehabilitation. It is an on-going industrial project based on force-fatigue models, validated by experiments.Moreover it opens the road to application of optimal control to track a reference trajectory in the joint angular variable to produce movement in the non-isometric models.