Real-time location of acupuncture points based on anatomical landmarks and pose estimation models
These AI-driven methods establish a solid foundation for the automated localization of acupoints, enhancing both self-guided and professional acupuncture practices. By enabling precise, real-time localization of acupoints, these technologies could improve the accuracy of treatments, facilitate self-training, and increase the accessibility of acupuncture. Future developments could expand these models to include additional acupoints and incorporate them into intuitive applications for broader use.
Authors
- Myunggi Yi (ORCID: https://orcid.org/0000-0003-4864-959X)
- Byeong-Il Lee (ORCID: https://orcid.org/0000-0002-1574-7145)
- Jin-Seong Choi
- Hadi Sedigh Malekroodi (ORCID: https://orcid.org/0009-0001-1958-1525)
- Seon-Deok Seo
- Chang-Soo Na
Institutions
- Dongshin University (KR)
- Pukyong National University (KR)
Publication Details
- Journal
- Frontiers in Neurorobotics
- Published
- 2024-11-08
- DOI
- https://doi.org/10.3389/fnbot.2024.1484038
- Citations
- 15
- Primary Topic
- Acupuncture Treatment Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 10.74
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea