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World Journal of Urology

, Volume 35, Issue 6, pp 957–965

First Online: 26 September 2016Received: 21 July 2016Accepted: 21 September 2016DOI: 10.1007-s00345-016-1944-x

Cite this article as: Jarc, A.M., Stanley, A.A., Clifford, T. et al. World J Urol 2017 35: 957. doi:10.1007-s00345-016-1944-x


PurposeIn this study, we examine three-dimensional 3D proctoring tools i.e., semitransparent ghost tools overlaid on the surgeon’s field of view on realistic surgical tasks. Additionally, we develop novel, quantitative measures of whether proctors exploit the additional capabilities offered by ghost tools.

MethodsSeven proctor–trainee pairs completed realistic surgical tasks such as tissue dissection and suturing in a live porcine model using 3D ghost tools on the da Vinci Xi Surgical System. The usability and effectiveness of 3D ghost tools were evaluated using objective measures of proctor performance based on proctor hand movements and button presses, as well as post-study questionnaires.

ResultsProctors exploited the capabilities of ghost tools, such as 3D hand movement p < 0.001, wristedness p < 0.001, finger pinch gestures p < 0.001, and bimanual hand motions p < 0.001. The median ghost tool excursion distances across proctors in the x-, y-, and z-directions were 57.6, 31.9, and 50.7, respectively. Proctors and trainees consistently evaluated the ghost tools as effective across multiple categories of mentoring. Trainees found ghost tools more helpful than proctors across all categories p < 0.05.

ConclusionsProctors exploit the augmented capabilities of 3D ghost tools during clinical-like training scenarios. Additionally, both proctors and trainees evaluated ghost tools as effective mentoring tools, thereby confirming previous studies on simple, inanimate tasks. Based on this preliminary work, advanced mentoring technologies, such as 3D ghost tools, stand to improve current telementoring and training technologies in robot-assisted minimally invasive surgery.

KeywordsTelementoring Proctor Surgeon training Ghost tools Performance metrics Augmented reality Electronic supplementary materialThe online version of this article doi:10.1007-s00345-016-1944-x contains supplementary material, which is available to authorized users.

Author: Anthony M. Jarc - Andrew A. Stanley - Thomas Clifford - Inderbir S. Gill - Andrew J. Hung


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