Title :
A nonlinear mathematical model of electrically stimulated skeletal muscle
Author :
Dorgan, Stephen J. ; O´Malley, Mark J.
Author_Institution :
Dept. of Electron. & Electr. Eng., Univ. Coll. Dublin, Ireland
fDate :
6/1/1997 12:00:00 AM
Abstract :
A new biophysically based mathematical model for a human musculotendon system is presented. This model is developed specifically for skeletal muscle activated by functional electrical stimulation (FES). The reverse-order recruitment dynamics of PES activated systems are modeled, as are the underlying processes of force generation in mammalian muscle. The resulting system model is both nonlinear and highly coupled, reflecting the fundamental structure and behavior of skeletal muscle. A new heterogeneous model structure for a contractile element is also presented that overcomes many of the problems which arise when attempting to describe all possible contraction modes. It is found that the new model is robust, numerically stable, and easily implemented. Simulation results are presented that demonstrate the model´s ability to capture a variety of nonlinear behaviors observed in skeletal muscle activated by FES. Significant insight into the internal dynamics of force development in FES muscle may also be gained from the model. This model is intended as a possible alternative to those currently available in the literature. It may be of use to those conducting research into the modeling, control and optimization of FES generated motion, and neural feedback systems
Keywords :
bioelectric phenomena; muscle; neurophysiology; physiological models; biophysically-based mathematical model; contractile element; contraction modes; electrically stimulated skeletal muscle; force development internal dynamics; functional electrical stimulation; heterogeneous model structure; human musculotendon system; mammalian muscle force generation; neural feedback systems; nonlinear behaviors; nonlinear mathematical model; reverse-order recruitment dynamics; Couplings; Humans; Mathematical model; Motion control; Muscles; Neuromuscular stimulation; Nonlinear dynamical systems; Numerical models; Recruitment; Robustness;
Journal_Title :
Rehabilitation Engineering, IEEE Transactions on