Title: Characterisation of reflex regulation of antagonist muscles based on a spinal neuromusculoskeletal system model

Authors: L. Lan, K.Y. Zhu, C.Y. Wen

Addresses: Biomedical Instrumentation Lab, S2.1-B4-02, School of Electrical & Electronic Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore. ' Electronic and Computer Engineering Division, School of Engineering, Ngee Ann Polytechnic, 599489, Singapore. ' Block S2, School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore

Abstract: The human hierarchical motor control system provides the ability for a human being to produce many different movements to adapt to variable environment. This system is a complex non-linear system including highly integrated neural centres in the brain and the spinal cord, many actuators constructed by muscles and bones and numerous sensory receptors. It is believed that the neuromusculoskeletal model of human motor control system is very important to understand the characteristics of the system. In this paper, dynamic behaviour and mechanism of the neuromusculoskeletal model presented in Lan et al. (2005) are investigated. It is a single joint reflex model with agonist and antagonist muscles. Some intrinsic properties of the system model such as behaviour of the moment arms, characteristics of force and stabilisation are presented. The results reveal some intrinsic properties in the system. Firstly, to guarantee a unique equilibrium point of the system, the descending neuron control commands must be selected within a special range. Secondly, the reflex regulation in spinal control circuit, i.e., the feedback from Renshaw cells and γ motor neurons, is not absolutely necessary to ensure the system stability, as the system can still converge to an equilibrium point even with the constant muscle activation.

Keywords: human motor control; spinal neuromusculoskeletal system; reflex regulation; stability; equilibrium point; antagonist muscles; modelling; single joint reflex model; spinal control circuit.

DOI: 10.1504/IJMIC.2010.033213

International Journal of Modelling, Identification and Control, 2010 Vol.9 No.4, pp.382 - 391

Published online: 13 May 2010 *

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