@InProceedings{samy:arso:2019,
  author    = {Samy, Vincent and Ayusawa, Ko and Yoshiyasu, Yusuke and Sagawa, Ryusuke and Yoshida, Eiichi},
  title     = {Musculoskeletal Estimation Using Inertial Measurement Units and Single Video Image},
  booktitle = {IEEE International Conference on Advanced Robotics and its Social Impacts},
  year      = {2019},
  pages     = {39--44},
  address   = {Beijing, China},
  month     = {October 31-November 2},
  url       = {https://hal.archives-ouvertes.fr/hal-02311483v2/document},
  keywords  = {musculoskeletal analysis, inverse kinematics, IMU-based pose estimation, vision-based pose estimation, deep learning},
  doi       = {https://doi.org/10.1109/ARSO46408.2019.8948820},
  abstract  = {We address the problem of estimating the physical burden of a human body. This translates to monitor and estimate muscle tension and joint reaction forces of a musculoskeletal model in real-time. The system should minimize the discomfort generating by any sensors that needs to be fixed on the user. Our system combines a 3D pose estimation from vision and IMU sensors. We aim to minimize the number of IMU fixed to the subject while compensating the remaining lack of information with vision.}
}