Portable Moxibustion Robot With Intelligent Acupoint Positioning Guided by Visual Sensing
BACKGROUND: To overcome key challenges in traditional moxibustion, such as the shortage of skilled practitioners, time-consuming and labour-intensive procedures, this study developed an intelligent robotic system for automated acupoint positioning and moxibustion execution. METHODS: The system established a standardised acupoint coordinate map utilising DensePose-based body normalisation and statistical modelling from 50 subjects. A hybrid serial-parallel robot design enabled large workspace and high precision for bedside application. Safety was ensured by a Model Predictive Controller utilising real-time thermal feedback for dynamic distance adjustment. RESULTS: mm (lower limbs). The system responded to temperature changes within 0.25 s, limiting overshoot to below 0.8°C. CONCLUSIONS: This integrated robotic system provides a precise and scalable solution for automated moxibustion, particularly valuable for resource-limited clinical environments. TRIAL REGISTRATION: It was an investigational clinical study, not a registrational clinical trial.
Authors
- Mingrui Hao
- Lanhui Wang (ORCID: https://orcid.org/0000-0002-4353-1739)
- Zhaokun Deng (ORCID: https://orcid.org/0009-0005-2295-3317)
- Zi Wang (ORCID: https://orcid.org/0000-0002-3953-0493)
- S Wang
- Kairou Guo
- Ying Li
- Pengcheng Zhang (ORCID: https://orcid.org/0009-0002-8796-500X)
- Ling Guan
- Taizhong Wang
Institutions
- Chinese University of Hong Kong (HK)
- Chinese PLA General Hospital (CN)
- Shandong Institute of Automation (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Institute of Automation (CN)
- China Association of Acupuncture-Moxibustion (CN)
- Beijing Hospital of Traditional Chinese Medicine (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- International Journal of Medical Robotics and Computer Assisted Surgery
- Published
- 2026-05-09
- DOI
- https://doi.org/10.1002/rcs.70177
- Primary Topic
- Acupuncture Treatment Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China