Dynamic Multiaction Recognition and Expert Movement Mapping for Closed Pelvic Reduction

doi:10.1109/TII.2022.3220872

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Dynamic Multiaction Recognition and Expert Movement Mapping for Closed Pelvic Reduction
	Pan, Ming-Zhang 1; Deng, Ya-Wen 1; Li, Zhen 2,3; Chen, Yuan 1; Liao, Xiao-Lan 1; Bian, Gui-Bin 3
刊名	IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
	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.
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关键词	NEURAL-NETWORKS
WOS研究方向	Automation & Control Systems ; Computer Science ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001030673600011
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
内容类型	期刊论文
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.Guangxi Univ, Sch Mech Engn, Nanning 530004, Peoples R China 2.Tongji Univ, Sch Elect & Informat Engn, Shanghai 200092, 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.