Recognition of Forward Head Posture Through 3D Human Pose Estimation With a Graph Convolutional Network: Development and Feasibility Study
Based on 2D image input using 3D human pose estimation joint inputs, it was found that it is possible to learn FHP-related features using the proposed GCN-based network to develop a posture correction system. We conclude the paper by addressing the limitations of our current system and proposing potential avenues for future work in this area.
Authors
- Haedeun Lee (ORCID: https://orcid.org/0000-0002-7855-7904)
- Seung-Chan Kim (ORCID: https://orcid.org/0000-0001-7292-5166)
- Bumjo Oh (ORCID: https://orcid.org/0000-0002-2468-0755)
Institutions
- Seoul National University (KR)
- Seoul Metropolitan Government (KR)
- SNUH SMG-SNU Boramae Medical Center (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2024-08-26
- DOI
- https://doi.org/10.2196/55476
- Citations
- 6
- Primary Topic
- Musculoskeletal pain and rehabilitation
- Type
- article
- Field-Weighted Citation Impact
- 2.69
Funders
- Korea Medical Device Development Fund
- Ministry of Trade, Industry and Energy