Balance of a Multijoint Biomechanical System in Natural and Artificial Environments: A Simulation Model

Abstract

The paper is devoted to a neurobionic simulation model for controlling balance in a biomechanical pendulum. The model is realized by a complex of fuzzy regulators and an artificial neural network. Fuzzy regulators are used for simulating the physiological characteristics of the motor system and the functions of the sensory systems. The second level of control is the central integrator. It is realized as an artificial neural network (ANN), which simulates a real process of analysis and synthesis of afferent signals, formation of the model of action, etc.
Equilibrium control in a multijoint biomechanical object is a specific example of a self-developing multilevel system of movement control. In the course of elaboration of the model and further examination of its behavior we have received model results which revealed correspondence with the results demonstrated by real subjects in stabilographic tests performed after long-term space flights.
We concluded that the model permits us to simulate the peculiarities of human movement control and can be used for creating individual plans of recovery and rehabilitation of patients after long-term motionless or learning movement control in unknown environments.