Prediction of natural guidewire rotation using an sEMG-based NARX neural network
Zhou, Xiao-Hu; Bian, Gui-Bin; Xie, Xiao-Liang; Hou, Zeng-Guang; Hao, Jian-Long
2017
会议名称Neural Networks (IJCNN), 2017 International Joint Conference on
会议日期2017
会议地点Anchorage Alaska USA
摘要For the treatment of cardiovascular diseases, clinical
success of percutaneous coronary intervention is highly dependent on natural technical skills and dexterous manipulation
strategies of surgeons. However, the increasing used robotic surgical systems have been designed without considering manipulation
techniques, especially surgical behaviors and motion patterns.
This has driven research towards exploitation of natural manipulation skills in recent years. In this paper, natural guidewire
manipulations are analyzed and predicted using an sEMG-based
nonlinear autoregressive neural network with exogenous inputs.
The relationship between natural endovascular manipulation and
guidewire rotation is built through the network. Two experiments
at different rotational speed were performed to verify the effectiveness and robustness of the applied model. The experimental
results show that the average predictive root mean error of five
subjects is 15.61
at the low speed and 21.85at the high speed.
These favorable results could be of interest to improve existing
robotic surgical systems.

文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/19998
专题复杂系统管理与控制国家重点实验室_先进机器人
推荐引用方式
GB/T 7714
Zhou, Xiao-Hu,Bian, Gui-Bin,Xie, Xiao-Liang,et al. Prediction of natural guidewire rotation using an sEMG-based NARX neural network[C],2017.
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