Acknowledgement
This work was supported by the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT (No. 2022M3A9B6082791).
Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)
- 2023.11a
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- Pages.563-565
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- 2023
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- 2005-0011(pISSN)
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- 2671-7298(eISSN)
DOI QR Code
A Computer Vision Approach for Identifying Acupuncture Points on the Face and Hand Using the MediaPipe Framework
MediaPipe Framework를 이용한 얼굴과 손의 경혈 판별을 위한 Computer Vision 접근법
- Hadi S. Malekroodi (Industry 4.0 Convergence Bionics Engineering, Pukyong National University) ;
- Myunggi Yi (Major of Biomedical Engineering, Division of Smart Healthcare, Pukyong National University) ;
- Byeong-il Lee (Major of Human Bioconvergence, Division of Smart Healthcare, Pukyong National University)
- Published : 2023.11.02
Abstract
Acupuncture and acupressure apply needles or pressure to anatomical points for therapeutic benefit. The over 350 mapped acupuncture points in the human body can each treat various conditions, but anatomical variations make precisely locating these acupoints difficult. We propose a computer vision technique using the real-time hand and face tracking capabilities of the MediaPipe framework to identify acupoint locations. Our model detects anatomical facial and hand landmarks, and then maps these to corresponding acupoint regions. In summary, our proposed model facilitates precise acupoint localization for self-treatment and enhances practitioners' abilities to deliver targeted acupuncture and acupressure therapies.
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