LAUSR

AbstractPurposeThis paper describes the design, principles, performances, and applications of a novel image-guided master–slave robotic system for vascular intervention (VI), including the performance evaluation and in vivo trials. MethodsBased on the peer-to-peer (P2P) remote communication system, the kinetics analysis, the sliding-mode neural network self-adaptive control model and the feedback system, this new robotic system can accomplish in real time a number of VI operations, including guidewire translation and rotation, balloon catheter translation, and contrast agent injection. The master–slave design prevents surgeons from being exposed to X-ray radiation, which means that they are not required to wear a heavy lead suit. We also conducted a performance evaluation of the new system, which assessed the speed, position tracking, and accuracy, as well as in vivo swine trials. ResultsThe speed and position tracking effects are really good, which contribute to the high level of performance in terms of the translational (error ≤ 0.45%) and rotational (error ≤ 2.6°) accuracy. In addition, the accuracy of the contrast agent injection is less than 0.2 ml. The robotic system successfully performed both the stent revascularization of an arteria carotis and four in vivo trials. The haptic feedback data correspond with the robotic-assisted procedure, and peaks and troughs of data occur regularly.ConclusionsBy means of the performance evaluation and four successful in vivo trials, the feasibility and efficiency of the new robotic system are validated, which should prove helpful for further research.