Modeling of human gait control using CPGs

Andrii Dmytrovych Shachykov (1, 2, 3, 4) , Patrick Henaff (4, 3) , Alexander Shulyak (2)

1 UL - Université de Lorraine
2 National Technical University of Ukraine "Kyiv Polytechnic Institute" [Kiev]
3 NEUROSYS - Analysis and modeling of neural systems by a system neuroscience approach
4 LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications

In this paper, a way of controlling musculoskeletal gait of human using central pattern generators (CPG) is presented. Our controller is able to produce healthy or altered gait in sagittal plane using musculoskeletal model with six joints and sixteen muscles. Controller consists of eight CPGs and it uses five types of sensory feedback. Simulation results in Matlab shows that changing intrinsic parameters of CPGs, model produces different types of gait.

Mots clés: central pattern generator; musculoskeletal model; human walking; Parkinson's disease

Domaines: Informatique [cs]; Rhumatologie et système ostéo-articulaire

Andrii Dmytrovych Shachykov, Patrick Henaff, Alexander Shulyak. Modeling of human gait control using CPGs. JNRH 2018 - Journées Nationales de la Robotique Humanoïde, Jun 2018, Nancy, France. ⟨hal-02006019⟩