Knowledge Commons of Institute of Automation,CAS
A Multilayer and Multimodal-Fusion Architecture for Simultaneous Recognition of Endovascular Manipulations and Assessment of Technical Skills | |
Xiaohu,Zhou1; Xiaoliang.Xie1; Zhenqiu,Feng1; Zengguang,Hou1,2,3; Guibin,Bian1; Ruiqi,Li3; Zhenliang,Ni3; Shiqi,Liu1; Yan-Jie Zhou3 | |
发表期刊 | IEEE TRANSACTIONS ON CYBERNETICS |
2020-07 | |
卷号 | PP期号:99页码:1-13 |
摘要 | The clinical success of the percutaneous coronary intervention (PCI) is highly dependent on endovascular manipulation skills and dexterous manipulation strategies of interventionalists. However, the analysis of endovascular manipulations and related discussion for technical skill assessment are limited. In this study, a multilayer and multimodal-fusion architecture is proposed to recognize six typical endovascular manipulations. The synchronously acquired multimodal motion signals from ten subjects are used as the inputs of the architecture independently. Six classification-based and two rule-based fusion algorithms are evaluated for performance comparisons. The recognition metrics under the determined architecture are further used to assess technical skills. The experimental results indicate that the proposed architecture can achieve the overall accuracy of 96.41%, much higher than that of a single-layer recognition architecture (92.85%). In addition, the multimodal fusion brings significant performance improvement in comparison with singlemodal schemes. Furthermore, the K-means-based skill assessment can obtain an accuracy of 95% to cluster the attempts made by different skill-level groups. These hopeful results indicate the great possibility of the architecture to facilitate clinical skill assessment and skill learning. |
关键词 | Endovascular manipulations multilayer and multimodal-fusion architecture (MMFA) percutaneous coronary intervention (PCI), technical skill assessment |
WOS记录号 | WOS:000778931500052 |
七大方向——子方向分类 | 多模态智能 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/41470 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
作者单位 | 1.the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 2.the Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100190, China 3.the School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Xiaohu,Zhou,Xiaoliang.Xie,Zhenqiu,Feng,et al. A Multilayer and Multimodal-Fusion Architecture for Simultaneous Recognition of Endovascular Manipulations and Assessment of Technical Skills[J]. IEEE TRANSACTIONS ON CYBERNETICS,2020,PP(99):1-13. |
APA | Xiaohu,Zhou.,Xiaoliang.Xie.,Zhenqiu,Feng.,Zengguang,Hou.,Guibin,Bian.,...&Yan-Jie Zhou.(2020).A Multilayer and Multimodal-Fusion Architecture for Simultaneous Recognition of Endovascular Manipulations and Assessment of Technical Skills.IEEE TRANSACTIONS ON CYBERNETICS,PP(99),1-13. |
MLA | Xiaohu,Zhou,et al."A Multilayer and Multimodal-Fusion Architecture for Simultaneous Recognition of Endovascular Manipulations and Assessment of Technical Skills".IEEE TRANSACTIONS ON CYBERNETICS PP.99(2020):1-13. |
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