An Augmented Reality-Based Interaction Scheme for Robotic Pedicle Screw Placement

Viktor Vörös, Ruixuan Li, Ayoob Davoodi, Gauthier Wybaillie, Emmanuel Vander Poorten, Kenan Niu

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)
38 Downloads (Pure)

Abstract

Robot-assisted surgery is becoming popular in the operation room (OR) for, e.g., orthopedic surgery (among other surgeries). However, robotic executions related to surgical steps cannot simply rely on preoperative plans. Using pedicle screw placement as an example, extra adjustments are needed to adapt to the intraoperative changes when the preoperative planning is outdated. During surgery, adjusting a surgical plan is non-trivial and typically rather complex since the available interfaces used in current robotic systems are not always intuitive to use. Recently, thanks to technical advancements in head-mounted displays (HMD), augmented reality (AR)-based medical applications are emerging in the OR. The rendered virtual objects can be overlapped with real-world physical objects to offer intuitive displays of the surgical sites and anatomy. Moreover, the potential of combining AR with robotics is even more promising; however, it has not been fully exploited. In this paper, an innovative AR-based robotic approach is proposed and its technical feasibility in simulated pedicle screw placement is demonstrated. An approach for spatial calibration between the robot and HoloLens 2 without using an external 3D tracking system is proposed. The developed system offers an intuitive AR–robot interaction approach between the surgeon and the surgical robot by projecting the current surgical plan to the surgeon for fine-tuning and transferring the updated surgical plan immediately back to the robot side for execution. A series of bench-top experiments were conducted to evaluate system accuracy and human-related errors. A mean calibration error of 3.61 mm was found. The overall target pose error was 3.05 mm in translation and 1.12∘ in orientation. The average execution time for defining a target entry point intraoperatively was 26.56 s. This work offers an intuitive AR-based robotic approach, which could facilitate robotic technology in the OR and boost synergy between AR and robots for other medical applications.
Original languageEnglish
Article number273
JournalJournal of imaging
Volume8
Issue number10
DOIs
Publication statusPublished - 6 Oct 2022
Externally publishedYes

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