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Updated: May 16, 2025

Visualizing Motion Patterns in Acupuncture Manipulation
Published on: July 16, 2016
[Research status of automatic localization of acupoint based on deep learning]
Yuge Dong1, Chengbin Wang2, Weigang Ma1
1School of Acupuncture-Moxibustion and Tuina, Tianjin University of TCM, Tianjin 301617, China; Experimental Acupuncture Research Center, Tianjin University of TCM, Tianjin 301617.
Abstract:
This paper reviews the published articles of recent years on the application of deep learning methods in automatic localization of acupoint, and summarizes it from 3 key links, i.e. the dataset construction, the neural network model design, and the accuracy evaluation of acupoint localization. The significant progress has been obtained in the field of deep learning for acupoint localization, but the scale of acupoint detection needs to be expanded and the precision, the generalization ability, and the real-time performance of the model be advanced. The future research should focus on the support of standardized datasets, and the integration of 3D modeling and multimodal data fusion, so as to increase the accuracy and strengthen the personalization of acupoint localization.

