Modelo computacional simple de la marcha bípeda humana

Abstract

This work develops a simple neural network aimed to model the oscillatory neural pattern involved in the control of the human biped walking. The neural network proposed exhibits a highly non linear dynamics and generates oscillatory firing rates which decode the angular velocity for the segments forming the human legs. This model neural network is biologically inspired since it takes into account the structure and functional connectivity found in animal nervous systems generating rhythmic movements in wild behavior. From this approach, it is possible to say that this work supports the idea of the existence of general principles for the movement neurocontrol in animals. There are no considerations about stability under gravity effects. © Springer-Verlag Berlin Heidelberg 2007.