Vascular Environment Identification Based on Multi-dimensional Data Fusion for Interventional Surgical Robots

Dong Yang, Wei Wei, Jiaqian Li, Nan Xiao

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Vascular interventional surgery is the most commonly used method for the treatment of cardio-vascular and cerebrovascular diseases. Master-slave interventional surgical robot is a promising technology, which can further improve the accuracy and safety of surgery. However, imperfect measurement of catheter force remains a surgical risk. Inspired by the function of insect antennae, a thin-film force sensing device was installed in the catheter head. Combined with the pressure sensor in the catheter clamping device, the LSTM network was used to predict and classify the curvature of the current passing vessel, and the recognition accuracy was 97%. In the process of robotic surgery, real-time feedback of current pressure information and vascular curvature information can enhance the doctor's judgment of the operation state and improve the safety of surgery.

源语言英语
主期刊名2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022
出版商Institute of Electrical and Electronics Engineers Inc.
1738-1744
页数7
ISBN(电子版)9781665481090
DOI
出版状态已出版 - 2022
活动2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022 - Jinghong, 中国
期限: 5 12月 20229 12月 2022

出版系列

姓名2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

会议

会议2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022
国家/地区中国
Jinghong
时期5/12/229/12/22

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引用此

Yang, D., Wei, W., Li, J., & Xiao, N. (2022). Vascular Environment Identification Based on Multi-dimensional Data Fusion for Interventional Surgical Robots. 在 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022 (页码 1738-1744). (2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ROBIO55434.2022.10011932