An Initial Study on Automated Acupoint Positioning for Laser Acupuncture

Kun Chan Lan, Chang Yin Lee, Guan Sheng Lee, Tzu Hao Tsai, Yu Chen Lee, Chih Yu Wang

研究成果: Article同行評審

3 引文 斯高帕斯(Scopus)

摘要

Acupuncture plays an important role in traditional Chinese medicine (TCM) and is one kind of an inexpensive and effective treatment. However, some people might be reluctant to receive acupuncture treatment due to fear of pain. Laser acupuncture, thanks to its painless and infection-free advantages, has recently become an alternative choice to traditional acupuncture. The accuracy of acupuncture point positioning has a decisive influence on the quality of laser acupuncture. In this study, built on top of our prior work, we proposed a low-cost automated acupoint positioning system for laser acupuncture. By integrating several machine learning algorithms and computer vision techniques, we design and implement a robot-assisted laser acupuncture system on top of a smartphone. Our contributions include the following: (a) development of an effective acupoint estimation algorithm with a localization error less than 5 mm; (b) implementation of a smartphone-controlled automated laser acupuncture system with lift-thrust function, as a point-of-care device, that can be used by patients to relieve their symptoms at home.

原文English
文章編號8997051
期刊Evidence-based Complementary and Alternative Medicine
2022
DOIs
出版狀態Published - 2022

All Science Journal Classification (ASJC) codes

  • 補充和替代醫學

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