Kinect-based non-intrusive human gait analysis and visualization

Nguyen-Luc Dao, Yuzhe Zhang, Jianmin Zheng, Jianfei Cai

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

7 Citations (Scopus)


Home healthcare becomes more and more important with the increased aging population. The advent of various low-cost sensing devices makes it tempting to develop low-cost, non-intrusive systems to monitor the variations of human being. In this paper, we describe a Kinect-based gait analysis and visualization system as a case study in this direction. The system uses depth images and skeleton captured by the Kinect to generate a BVH file recording the motion information, extracts features of gait for detecting abnormal gait, and customizes the 3D body model for personalized motion visualization. Compared to previous work in this area, the proposed system has advantages since it integrates gait classification and visualization which may bring new possibilities in healthcare. The experiments show that our proposed system achieves accurate gait classification as well as flexible personalized 3D visualization.

Original languageEnglish
Title of host publication2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) - October 19-21 2015, Xiamen, China
EditorsTao Mei , Gene Cheung
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781467374781, 9781467374774
Publication statusPublished - 2015
Externally publishedYes
EventIEEE International Workshop on Multimedia Signal Processing 2015 - Xiamen, China
Duration: 19 Oct 201521 Oct 2015
Conference number: 17th (Proceedings)


ConferenceIEEE International Workshop on Multimedia Signal Processing 2015
Abbreviated titleMMSP 2015
Internet address


  • Data visualization
  • Feature extraction
  • Foot
  • Knee
  • Medical services
  • Skeleton
  • Three-dimensional displays

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