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

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 w...

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Published in2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) pp. 803 - 807
Main Authors Chen, Kai-Yu, Zheng, Wei-Zhong, Lin, Yu-Yi, Tang, Shih-Tsang, Chou, Li-Wei, Lai, Ying-Hui
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2020
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Summary: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.
ISSN:1558-4615
DOI:10.1109/EMBC44109.2020.9176120