Literature DB >> 12690487

Modeling of a bipedal locomotor using coupled nonlinear oscillators of Van der Pol.

Max S Dutra1, Armando C De Pina Filho, Vitor F Romano.   

Abstract

Research to date points to an understanding of human biped locomotion that has been primarily experimental in nature largely due to the complexity of the process. In view of the new, exciting possibilities of programmed electrostimulation of artificial muscles to generate motion (locomotion), a critical study at the theoretical level is greatly warranted. There is strong evidence that many biological clocks consist of a population of mutually coupled oscillators [Pavlidis T (1973) Biological oscillators, Academic; Johnsson A (1978) Zur Biophysik biologischer Oszillatoren. In: Biophisik, Springer]. In this work, a form of bipedal locomotion is simulated by using mutually coupled nonlinear oscillators. A planar model, which includes three out of the six determinants of gait that characterize the human locomotion, was adopted.

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Year:  2003        PMID: 12690487     DOI: 10.1007/s00422-002-0380-8

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  4 in total

1.  On the role of sensory feedbacks in rowat-selverston CpG to improve robot legged locomotion.

Authors:  Elmira Amrollah; Patrick Henaff
Journal:  Front Neurorobot       Date:  2010-12-29       Impact factor: 2.650

2.  The Passive Series Stiffness That Optimizes Torque Tracking for a Lower-Limb Exoskeleton in Human Walking.

Authors:  Juanjuan Zhang; Steven H Collins
Journal:  Front Neurorobot       Date:  2017-12-20       Impact factor: 2.650

3.  Synchronization of Non-linear Oscillators for Neurobiologically Inspired Control on a Bionic Parallel Waist of Legged Robot.

Authors:  Yaguang Zhu; Shuangjie Zhou; Dongxiao Gao; Qiong Liu
Journal:  Front Neurorobot       Date:  2019-08-02       Impact factor: 2.650

4.  Contribution of Phase Resetting to Statistical Persistence in Stride Intervals: A Modeling Study.

Authors:  Kota Okamoto; Ippei Obayashi; Hiroshi Kokubu; Kei Senda; Kazuo Tsuchiya; Shinya Aoi
Journal:  Front Neural Circuits       Date:  2022-06-22       Impact factor: 3.342

  4 in total

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