Literature DB >> 26857834

Simball Box for Laparoscopic Training With Advanced 4D Motion Analysis of Skills.

Kristine Hagelsteen1, Dan Sevonius2, Anders Bergenfelz2, Mikael Ekelund2.   

Abstract

Background Laparoscopic skills training and evaluation outside the operating room is important for all surgeons learning new skills. To study feasibility, a video box trainer tracking 4-dimensional (4D) metrics was evaluated as a laparoscopic training tool. Method Simball Box is a video box trainer with authentic surgical instruments and camera with video recording, equipped with 4D motion analysis registered through trocars using machine vision technology. Residents attending a 3-day laparoscopy course were evaluated performing a laparoscopic surgical knot at start, middle, and end. Metrics were obtained. Feedback data were presented in reference to expert/tutorial performance. Results Ten right-handed residents were included. Median time (range) to finish the task was 359 (253-418), 129 (95-166), and 95 (52-156) seconds; 655%, 236%, and 174% of tutorial performance, with significance pre-/midcourse (P < .0001), pre-/postcourse (P < .0001), and mid-/postcourse (P = .0050). Combined median total instrument motion decreased pre-/midcourse from 1208 (845-1751) to 522 cm (411-810 cm); P = .042 to 405 cm (246-864 cm) postcourse; pre-/postcourse P < .0001; 673%, 291%, 225% of tutorial performance. Total angular distance in radians (range) was 150 (87-251), 65 (42-116), and 50 (33-136) with significance pre-/midcourse (P = .022) and pre-/postcourse (P = .0002). Right-handed average speed (cm/s) increased: 1.94 (1.11-2.27) pre-, 2.39 (1.56-2.83) mid-, 2.60 (1.67-3.19) postcourse with significance pre-/midcourse (P = .022) and pre-/postcourse (P = .002). Average acceleration (mm/s(2)) and motion smoothness (µm/s(3)) failed to show any difference. Conclusion For laparoscopic training and as a promising evaluation device, Simball Box obtained metrics mirroring progression well.
© The Author(s) 2016.

Keywords:  assessment; box trainer; evaluation; laparoscopy; medical education; motion tracking; simulation; skills; surgical education

Mesh:

Year:  2016        PMID: 26857834     DOI: 10.1177/1553350616628678

Source DB:  PubMed          Journal:  Surg Innov        ISSN: 1553-3506            Impact factor:   2.058


  3 in total

1.  Development and validation of a sensor- and expert model-based training system for laparoscopic surgery: the iSurgeon.

Authors:  Karl-Friedrich Kowalewski; Jonathan D Hendrie; Mona W Schmidt; Carly R Garrow; Thomas Bruckner; Tanja Proctor; Sai Paul; Davud Adigüzel; Sebastian Bodenstedt; Andreas Erben; Hannes Kenngott; Young Erben; Stefanie Speidel; Beat P Müller-Stich; Felix Nickel
Journal:  Surg Endosc       Date:  2016-09-07       Impact factor: 4.584

2.  Objective classification of psychomotor laparoscopic skills of surgeons based on three different approaches.

Authors:  Fernando Pérez-Escamirosa; Antonio Alarcón-Paredes; Gustavo Adolfo Alonso-Silverio; Ignacio Oropesa; Oscar Camacho-Nieto; Daniel Lorias-Espinoza; Arturo Minor-Martínez
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-10-11       Impact factor: 2.924

3.  A system for real-time multivariate feature combination of endoscopic mitral valve simulator training data.

Authors:  Reinhard Fuchs; Karel M Van Praet; Richard Bieck; Jörg Kempfert; David Holzhey; Markus Kofler; Michael A Borger; Stephan Jacobs; Volkmar Falk; Thomas Neumuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2022-03-16       Impact factor: 3.421

  3 in total

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