A Neural Pattern Generator that Exhibits Arousal-Dependant Human Gait TransitionsReport as inadecuate


A Neural Pattern Generator that Exhibits Arousal-Dependant Human Gait Transitions


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Abstract

A neural pattern generator based upon a non-linear cooperative-competitive feedback neural network is presented. It can generate the two standard human gaits: the walk and the run. A scalar arousal or GO signal causes a bifurcation from one gait to the next. Although these two gaits are qualitatively different, they both have the same limb order and may exhibit oscillation frequencies that overlap. The model simulates the walk and the run via qualitatively different waveform shapes. The fraction of cycle that activity is above threshold distinguishes the two gaits, much as the duty cycles of the feet are longer in the walk than in the run.Rights

Copyright 1993 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and - or special permission.

CAS-CNS Technical Reports -



Author: Cohen, Michael A. - Grossberg, Stephen - Pribe, Christopher A. - -

Source: https://open.bu.edu/



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