Journal
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
Volume 49, Issue 2, Pages 194-205Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/THMS.2019.2892318
Keywords
Human biomechanical model; inertial sensor; motion capture; orientation estimation; sensor networks; sport training
Funding
- National Natural Science Foundation of China [61873044, 61473058, 61803072]
- Dalian Science and Technology Innovation Fund [2018J12SN077]
- China Postdoctoral Science Foundation [2017M621131, 2017M621132]
- Department of Physical Education, Dalian University of Technology
Ask authors/readers for more resources
Motion capture based on wearable inertial sensors is a promising technique for swimmers' training. To apply motion capture techniques properly, a swimming motion evaluation method based on inertial motion capture technology is proposed. Our proposed method uses a multisensor data fusion algorithm for swimmers' attitude estimation, and the swimming posture is reconstructed in combination with a human biomechanical model. Furthermore, a comparative experiment between our proposed motion capture system and the NDI motion tracking system shows that our system performs reliably and accurately, and the estimation errors are well controlled. In addition, the accuracy of the orientation estimation algorithm ranges from 1.65 degrees to 3.66 degrees. The system can capture swimmers' lumbar spine in four competitive swimming styles. A kinematic analysis of lumbar spine movement indicates that the patterns of swimmers' lumbar spine movement can be used to evaluate training performance and provide quantitative data for swimmers.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available