Real time control of a CPG-based model of the human trunk in different walking conditions

Jean-Charles Ceccato 1, 2 Christine Azevedo Coste 1, * Jean-René Cazalets 2
* Corresponding author
1 DEMAR - Artificial movement and gait restoration
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Artificial central pattern generators (CPGs) framework is well adapted to the control of bio-mimetic systems during rhythmic tasks like locomotion. They have the ability to reproduce biological behavior as well as to be used as feedforward controllers for multi-articulated systems. In this paper we present a model of human gait activity based on an oscillator network. The model is especially dedicated to reproduce trunk muscular activities as observed in previous studies, and to fill a lack in trunk modeling in human gait simulation. An offline validation is performed using recorded accelerometer signal that monitors trunk movements during locomotion. We are able to control the model based on this real data and to adapt its pattern to contextual changes (stairs, slope).
Document type :
Poster communications
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00407771
Contributor : Christine Azevedo Coste <>
Submitted on : Monday, July 27, 2009 - 3:38:33 PM
Last modification on : Tuesday, January 22, 2019 - 3:24:02 PM

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Jean-Charles Ceccato, Christine Azevedo Coste, Jean-René Cazalets. Real time control of a CPG-based model of the human trunk in different walking conditions. EMBC: Engineering in Medicine and Biology Conference, Sep 2009, Minneapolis, MN, United States. 31th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1388-1391, 2009, ⟨10.1109/IEMBS.2009.5334115⟩. ⟨lirmm-00407771⟩

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