TY - JOUR
T1 - An Initial Study on Automated Acupoint Positioning for Laser Acupuncture
AU - Lan, Kun Chan
AU - Lee, Chang Yin
AU - Lee, Guan Sheng
AU - Tsai, Tzu Hao
AU - Lee, Yu Chen
AU - Wang, Chih Yu
N1 - Publisher Copyright:
© 2022 Kun-Chan Lan et al.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.1155/2022/8997051
DO - 10.1155/2022/8997051
M3 - Article
AN - SCOPUS:85138234992
SN - 1741-427X
VL - 2022
JO - Evidence-based Complementary and Alternative Medicine
JF - Evidence-based Complementary and Alternative Medicine
M1 - 8997051
ER -