Dynamic Multiaction Recognition and Expert Movement Mapping for Closed Pelvic Reduction
文献类型：期刊论文
| 作者 | Pan, Ming-Zhang2; Deng, Ya-Wen2; Li, Zhen1,3 ; Chen, Yuan2; Liao, Xiao-Lan2; Bian, Gui-Bin3
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| 刊名 | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
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| 出版日期 | 2023-08-01 |
| 卷号 | 19期号:8页码:8667-8678 |
| 关键词 | Action recognition conv-BiLSTM closed pelvic reduction dynamic movement primitives multimodal data fusion surgeon movement mapping |
| ISSN号 | 1551-3203 |
| DOI | 10.1109/TII.2022.3220872 |
| 通讯作者 | Bian, Gui-Bin(guibin.bian@ia.ac.cn) |
| 英文摘要 | Pelvic fractures are one of the most serious traumas in orthopedic care, and reduction during routine surgery is a significant challenge. Because there are so many vital organs, blood vessels, and nerves around the pelvis, and the reduction force is large, the operational requirements for the surgeon are extremely strict and require extensive experience and surgical skills. This article proposes a method for collecting and digitizing doctors' reduction movements, which aims to help intelligent devices recognize surgeons' reduction actions and provides a means to learn from expert experience to improve the accuracy of surgery. First, the convolutional bidirectional long short-term memory algorithm with multilayer cross-fused features is proposed. It extracts time and spatial correlations between multimodal data in a hierarchical manner. Second, discrete dynamic motion primitives are adopted for mapping the surgeon's palm movement trajectory. Finally, this article constructs a data acquisition platform and collects data from surgeons with varying proficiency in closed reduction. Experiment results show that the closed reduction action recognition accuracy is 99% and posture recognition accuracy is 95.5%. The recognition algorithm proposed by this article is significantly higher than the commonly used algorithms in terms of Accuracy, Precision, Recall, and F1-Score. This article provides methods and means for the digitization of surgical expertise and transfers learning for robot-assisted surgery. |
| WOS关键词 | NEURAL-NETWORKS |
| 资助项目 | National Key Research and Development Program of China[2020YFB1313800] ; National Natural Science Foundation of China[62027813] ; National Natural Science Foundation of China[U20A20196] ; National Natural Science Foundation of China[62176266] ; CAS Interdisciplinary Innovation Team[JCTD-2019-07] ; Beijing Science Fund for Distinguished Young Scholars[JQ21016] |
| WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001030673600011 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; CAS Interdisciplinary Innovation Team ; Beijing Science Fund for Distinguished Young Scholars |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53918]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Bian, Gui-Bin |
| 作者单位 | 1.Tongji Univ, Sch Elect & Informat Engn, Shanghai 200092, Peoples R China 2.Guangxi Univ, Sch Mech Engn, Nanning 530004, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pan, Ming-Zhang,Deng, Ya-Wen,Li, Zhen,et al. Dynamic Multiaction Recognition and Expert Movement Mapping for Closed Pelvic Reduction[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,2023,19(8):8667-8678. |
| APA | Pan, Ming-Zhang,Deng, Ya-Wen,Li, Zhen,Chen, Yuan,Liao, Xiao-Lan,&Bian, Gui-Bin.(2023).Dynamic Multiaction Recognition and Expert Movement Mapping for Closed Pelvic Reduction.IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,19(8),8667-8678. |
| MLA | Pan, Ming-Zhang,et al."Dynamic Multiaction Recognition and Expert Movement Mapping for Closed Pelvic Reduction".IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 19.8(2023):8667-8678. |
入库方式： OAI收割
来源：自动化研究所
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