Abstract
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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Acknowledgements
This work has been supported by the Linz Institute of Technology (LIT) and the COMET-K2 Center for Symbiotic Mechatronics of the Linz Center of Mechatronics (LCM) funded by the Austrian federal government and the federal state of Upper Austria.
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Ziegler, J., Gattringer, H., Müller, A. (2022). Generation of Parametric Gait Patterns. In: Altuzarra, O., Kecskeméthy, A. (eds) Advances in Robot Kinematics 2022. ARK 2022. Springer Proceedings in Advanced Robotics, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-031-08140-8_41
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DOI: https://doi.org/10.1007/978-3-031-08140-8_41
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