Robotic Assisted Puncture Intervention with Respiratory Status Monitoring

EasyChair Preprint 9869, version 2

Abstract

We propose a robotic-assisted abdominal puncture intervention with respiratory status monitoring in this paper. We constructed the collected respiratory data as point cloud data and established a respiratory state monitoring model using a deep learning point cloud classification network. We divided the respiratory signal in the normal state into four phases: inspiration, peak inspiration, expiration, and the valley of expiration, and we used the peak respiratory phase as the robot's needle insertion moment. Experiments with simulated robot-assisted puncture interventions show the proposed scheme is feasible in a robot-assisted puncture intervention system.

Keyphrases: PointNet, Respiratory Status Monitoring, Robotic Assited Puncture

@booklet{EasyChair:9869,
  author    = {Xiaodong Wang and Shijia Chen and Chichi Li and Peng Chen and Jianjun Zhu and Cheng Wang and Jun Xu and Gao-Jun Teng},
  title     = {Robotic Assisted Puncture Intervention with Respiratory Status Monitoring},
  howpublished = {EasyChair Preprint 9869},
  year      = {EasyChair, 2023}}