Knowledge Commons of Institute of Automation,CAS
An HMM-based recognition framework for endovascular manipulations | |
Zhou Xiao-Hu; Bian Gui-Bin; Xie Xiao-Liang; Hou Zeng-Guang | |
2017 | |
会议名称 | 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), |
会议日期 | 2017 |
会议地点 | Jeju Korea |
摘要 | Robotic surgical systems are becoming increasingly popular for the treatment of cardiovascular diseases. However, most of them have been designed without considering techniques and skills of natural surgical manipulations, which are key factors to clinical success of percutaneous coronary intervention. This paper proposes an HMM-based framework to recognize six typical endovascular manipulations for surgical skill analysis. A simulative surgical platform is built for endovascular manipulations assessed by five subjects (1 expert and 4 novices). The performances of the proposed framework are evaluated by three experimental schemes with the optimal model parameters. The results show that endovascular manipulations are recognized with high accuracy and reliable performance. Furthermore, the acceptable results can also be applied to the design of next generation vascular interventional robots.
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其他摘要 |
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收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23502 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
作者单位 | Institute of Automation Chinese Academy of Sciences |
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 | Zhou Xiao-Hu,Bian Gui-Bin,Xie Xiao-Liang,et al. An HMM-based recognition framework for endovascular manipulations[C],2017. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
An HMM-Based Recogni(2804KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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