Prediction of natural guidewire rotation using an sEMG-based NARX neural network

	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 21.85◦ at 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	复杂系统认知与决策实验室_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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