文献类型：期刊文献

英文题名：HUMAN BACK ACUPUNCTURE POINTS LOCATION USING RGB-D IMAGE FOR TCM MASSAGE ROBOTS

作者：Zhao, Weiyang[1];Yan, Jianjun[1,2];Chen, Houru[1];Gao, Lianxin[1];Zhou, Wei[1]

机构：[1]East China Univ Sci & Technol, Sch Mech & Power Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Shanghai Key Lab Intelligent Sensing & Detect Tech, Shanghai 200237, Peoples R China

年份：2023

卷号：38

期号：1

起止页码：67

外文期刊名：INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001022238600008)】；

基金：Acknowledgement The work was supported by Joint Innovation Foundation of Xin-Huangpu Joint Innovation Institute of Chinese Medicine (No. 2022IR013) .

语种：英文

外文关键词：Acupuncture points location; human posture estimation recognition; 3D image; gradient boosting decision tree; TCM massage

摘要：We present an approach to automatically locate the human back acupuncture points based on RGB and depth images for traditional Chinese medicine (TCM) massage robots. The approach extracted key points on the human back to learn the position of acupuncture points. The key points around shoulders were extracted from RGB image using OpenPose network. A buttock key point was further defined and obtained from the depth image according to depth information of the buttocks. Then the key points were fed into the gradient boosting decision tree (GBDT) algorithm to learn association between human key points and acupuncture points. Compared to the majority of traditional location approach which still requires manual identification, our approach is fully automatic. What is more, the mean per acupuncture point position error of our approach is 10.57 mm, which meets the requirements of acupuncture points location in TCM massage robots and shows the potential of our system in terms of practical use.