Acupoint Detection Based on Deep Convolutional Neural Network

As an important component of Traditional Chinese Medicine (TCM), science of acupoint therapy has achieved significant results in clinical practice, but recognizing and positioning acupoints is heavily depends on the skills of practitioners. In recent years, researchers have proposed a few methods of...

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Bibliographic Details
Published in2020 39th Chinese Control Conference (CCC) pp. 7418 - 7422
Main Authors Sun, Lingyao, Sun, Shiying, Fu, Yuanbo, Zhao, Xiaoguang
Format Conference Proceeding
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 01.07.2020
Subjects
5G mobile communication
acupoint detection
convolutional neural network
convolutional pose machine
deep learning
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Summary:As an important component of Traditional Chinese Medicine (TCM), science of acupoint therapy has achieved significant results in clinical practice, but recognizing and positioning acupoints is heavily depends on the skills of practitioners. In recent years, researchers have proposed a few methods of automatic acupoints detection and positioning, but most of the methods are still based on manual designed features. In this paper, we propose an acupoints detection method based on deep convolutional neural network, and an evaluation method is proposed for acupoint detection. What's more, we build an acupoint detection dataset. Experiments are performed and a promising result is achieved.
ISSN:2161-2927
DOI:10.23919/CCC50068.2020.9188367