A software-based tool for video motion tracking in the surgical skills assessment landscape

Sandeep Ganni*, Sanne M.B.I. Botden, Magda Chmarra, Richard Goossens, Jack Jakimowicz

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

25 Citations (Scopus)
55 Downloads (Pure)

Abstract

Background: The use of motion tracking has been proved to provide an objective assessment in surgical skills training. Current systems, however, require the use of additional equipment or specialised laparoscopic instruments and cameras to extract the data. The aim of this study was to determine the possibility of using a software-based solution to extract the data. Methods: 6 expert and 23 novice participants performed a basic laparoscopic cholecystectomy procedure in the operating room. The recorded videos were analysed using Kinovea 0.8.15 and the following parameters calculated the path length, average instrument movement and number of sudden or extreme movements. Results: The analysed data showed that experts had significantly shorter path length (median 127 cm vs. 187 cm, p = 0.01), smaller average movements (median 0.40 cm vs. 0.32 cm, p = 0.002) and fewer sudden movements (median 14.00 vs. 21.61, p = 0.001) than their novice counterparts. Conclusion: The use of software-based video motion tracking of laparoscopic cholecystectomy is a simple and viable method enabling objective assessment of surgical performance. It provides clear discrimination between expert and novice performance.

Original languageEnglish
Pages (from-to)2994-2999
Number of pages6
JournalSurgical Endoscopy and Other Interventional Techniques
Volume32
Issue number6
DOIs
Publication statusPublished - 2018

Keywords

  • Laparoscopic cholecystectomy
  • Laparoscopic skills
  • Motion tracking
  • Objective assessment
  • Training
  • Video-based assessment

Fingerprint

Dive into the research topics of 'A software-based tool for video motion tracking in the surgical skills assessment landscape'. Together they form a unique fingerprint.

Cite this