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Modélisation et Identification des Muscles Squelettiques
sous Stimulation Electrique Fonctionnelle

Abstract : The main contributions of this thesis concern the modelling and the identification of the
skeletal muscles under Functional Electrical Stimulation for the rehabilitation of the paralysed limbs.
There are two objectives of modelling: 1) the simulation and the synthesis of the movement, to
evaluate the performances of the system a priori and, 2) to test and validate the control schemes based
on the referred control model such as the adaptive control or predictive control.
The muscle model proposed is an original multi-scale model presented in the state space with a set of
differential equations where the input is an electrical signal provided by electrical stimulator such as
the "PROSTIM" offering the possibility of tuning the amplitude, the pulse width and the frequency of
the electrical signal of stimulation, and the outputs are the muscle force and stiffness. The model
proposed integrates the macroscopic (muscle scale) and microscopic (fibre scale) dynamic behaviour of
the muscle with two control input, a "static" input for the rate of recruitment and a "chemical" input.
The parameters of this model were identified experimentally in isometric mode on animal with classical
techniques of identification such as Levenberg-Marquardt and the Extended Kalman Filter. The cross
validations illustrate the pertinence of the model and the quality of the estimate.
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Submitted on : Friday, March 23, 2007 - 4:31:36 PM
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  • HAL Id : tel-00138186, version 1



Hassan El Makssoud. Modélisation et Identification des Muscles Squelettiques
sous Stimulation Electrique Fonctionnelle. Automatique / Robotique. Université Montpellier II - Sciences et Techniques du Languedoc, 2005. Français. ⟨tel-00138186⟩



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