Deep-learning-based human motion tracking for rehabilitation applications using 3D image features

Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul:2020:803-807. doi: 10.1109/EMBC44109.2020.9176120.

Abstract

Motion rehabilitation is increasingly required owing to an aging population and suffering of stroke, which means human motion analysis must be valued. Based on the concept mentioned above, a deep-learning-based system is proposed to track human motion based on three-dimensional (3D) images in this work; meanwhile, the features of traditional red green blue (RGB) images, known as two-dimensional (2D) images, were used as a comparison. The results indicate that 3D images have an advantage over 2D images due to the information of spatial relationships, which implies that the proposed system can be a potential technology for human motion analysis applications.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Algorithms*
  • Deep Learning*
  • Humans
  • Imaging, Three-Dimensional
  • Motion