11th International Conference on Body Area Networks

Research Article

Networked Human Motion Capture System Based on Quaternion Navigation

  • @INPROCEEDINGS{10.4108/eai.15-12-2016.2267544,
        author={jie li and Zhe-long Wang and Hongyu Zhao and Raffael Gravina and Giancarlo Fortino and Yongmei Jiang and Kai Tang},
        title={Networked Human Motion Capture System Based on Quaternion Navigation},
        proceedings={11th International Conference on Body Area Networks},
        publisher={ACM},
        proceedings_a={BODYNETS},
        year={2017},
        month={4},
        keywords={motion capture; inertial navigation; particle filter; body sensor network},
        doi={10.4108/eai.15-12-2016.2267544}
    }
    
  • jie li
    Zhe-long Wang
    Hongyu Zhao
    Raffael Gravina
    Giancarlo Fortino
    Yongmei Jiang
    Kai Tang
    Year: 2017
    Networked Human Motion Capture System Based on Quaternion Navigation
    BODYNETS
    EAI
    DOI: 10.4108/eai.15-12-2016.2267544
jie li1, Zhe-long Wang1,*, Hongyu Zhao1, Raffael Gravina2, Giancarlo Fortino2, Yongmei Jiang3, Kai Tang4
  • 1: Dalian University of Technology
  • 2: University of Calabria Rende
  • 3: The Second Affiliated Hospital of Dalian Medical University
  • 4: The First Affiliated Hospital of Dalian Medical University
*Contact email: wangzl@dlut.edu.cn

Abstract

In this paper, from the perspective of human ergonomics, we analyze the movement of the joints in the process of human body movements, and we establish a dynamic model according to the human skeleton structure. On this basis, from the rigid body dynamics point of view, combined with the principle of inertial navigation, a body sensor network based on MEMS inertial sensors is built to capture human body motion in real time. On the basis of space trajectory of human body movement and traditional human motion solution strategy, a human motion solution strategy based on particle filter fusion solution is proposed to realize the prediction of human motion analysis. Therefore, we evaluate the performance of the designed system by comparing with the real motion. Finally, in order to verify the human motion data,the motion capture data verification platforms are established. Experimental results show that the proposed joint attitude solution algorithm can achieve a relatively smooth tracking effect and provides a certain reference value.