In this paper, a methodology to generate realistic gait patterns is presented. Human gait motion capture data is used along with a kinematic model of the human lower extremity to derive a parametric and time-continuous analytical description of the walking motion. This allows for reproduction of individual recorded gait cycles and for generating new artificial gait cycles. A data pool of about 5700 reproduced gait cycles from 120 participants walking at different velocities is used to generate trajectories of human lower limb joints. Walking motions of simulated male or female persons can thus be synthesized with a prescribed gait speed. The method shall serve as scientific basis for research focused on rehabilitation, motion assistance and simulations.


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    Titel :

    Generation of Parametric Gait Patterns


    Weitere Titelangaben:

    Springer Proceedings in Advanced Robotics


    Beteiligte:
    Altuzarra, Oscar (Herausgeber:in) / Kecskeméthy, Andrés (Herausgeber:in) / Ziegler, Jakob (Autor:in) / Gattringer, Hubert (Autor:in) / Müller, Andreas (Autor:in)

    Kongress:

    International Symposium on Advances in Robot Kinematics ; 2022 ; Bilbao, Spain June 26, 2022 - June 30, 2022



    Erscheinungsdatum :

    18.06.2022


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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