CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
An HMM-based recognition framework for endovascular manipulations
Zhou, Xiao-Hu; Bian, Gui-Bin; Xie, Xiao-Liang; Hou, Zeng-Guang
2017
Conference NameEngineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE
Conference Date2017
Conference Placejeju korea
AbstractRobotic 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

Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19995
Collection复杂系统管理与控制国家重点实验室_先进机器人
Recommended Citation
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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