Assessment of a novel deep learning-based marker-less motion capture system for gait study.

Journal: Gait & posture
Published Date: Mar 15, 2022

Abstract

BACKGROUND: Marker-less systems based on digital video cameras and deep learning for gait analysis could have a deep impact in clinical routine. A recently developed system has shown promising results in terms of joint center position but has not been yet evaluated in terms of gait outcomes.

Authors

  • Saman Vafadar
    Institut de Biomecanique Humaine Georges Charpak Arts et Metiers Institute of Technology Paris, France. Electronic address: saman.vafadar@yahoo.com.
  • Wafa Skalli
    Arts et Métiers, Institut de Biomécanique Humaine Georges Charpak, 151 bd de l'Hôpital, 75013, Paris, France.
  • Aurore Bonnet-Lebrun
    Institut de Biomecanique Humaine Georges Charpak Arts et Metiers Institute of Technology Paris, France. Electronic address: aurore.bonnet-lebrun@ensam.eu.
  • Ayman Assi
    Faculty of Medicine, University of Saint-Joseph in Beirut, Beirut, Lebanon. Electronic address: ayman.assi@usj.edu.lb.
  • Laurent Gajny
    Arts et Métiers, Institut de Biomécanique Humaine Georges Charpak, 151 bd de l'Hôpital, 75013, Paris, France. laurent.gajny@ensam.eu.

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