Image-based laparoscopic camera steering versus conventional steering: a comparison study

Paul J.M. Wijsman, Lennert Molenaar, Frank J. Voskens, Cas D.P. van ’t Hullenaar, Ivo A.M.J. Broeders*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
10 Downloads (Pure)

Abstract

In the last 2 decades, multiple robotic camera holders have been developed to improve camera steering during laparoscopic surgery. A new image-based steering method has been developed for more intuitive camera control. In this article, the efficiency and user experience of image-based steering were compared to conventional steering methods. Four participants (two senior surgical registrars, one junior surgical registrar and a technical medicine student) were enrolled in this study. All participants performed multiple camera steering exercises with three different steering modalities in randomized order: image-based, joystick and manual camera steering. Steering of the laparoscope was evaluated by execution time and with the SMEQ and NASA-TLX questionnaires to analyze user experience. A total of 267 camera steering exercises were performed. The analyzed data showed a significantly shorter execution time for manual camera steering compared to image-based robotic steering (p = 0.001) and joystick robotic steering (p = 0.001). The participants reported the lowest user experience with joystick camera steering. The results of the questionnaires showed no significant difference in all subscales of user experience for image-based and manual camera steering. Manual camera steering resulted in significantly higher perceived physiological workload scores (M = 30.0, IQR = 27.5) compared to image-based (M = 10, IQR = 5.0) and joystick camera steering (M = 15.0, IQR = 10.0). Manual control of the laparoscope remains the fastest steering method at the expense of a high physical workload. Using image-based camera steering is a viable alternative to the current joystick control of robotic camera holders, as it improves speed and user experience. The study results suggest that optimisation of robotic camera steering with algorithms based on image analysis is a promising technology.

Original languageEnglish
Pages (from-to)1157-1163
Number of pages7
JournalJournal of robotic surgery
Volume16
Issue number5
Early online date21 Jan 2022
DOIs
Publication statusPublished - Oct 2022

Keywords

  • Computer vision
  • Image analysis
  • Laparoscopic camera holder
  • Laparoscopic camera steering
  • UT-Hybrid-D

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