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Surgical Endoscopy

, Volume 33, Issue 7, pp 2249–2256 | Cite as

Eye tracking in surgical education: gaze-based dynamic area of interest can discriminate adverse events and expertise

  • Eric Fichtel
  • Nathan LauEmail author
  • Juyeon Park
  • Sarah Henrickson Parker
  • Siddarth Ponnala
  • Shimae Fitzgibbons
  • Shawn D. Safford
Article
  • 165 Downloads

Abstract

Background

Eye-gaze metrics derived from areas of interest (AOIs) have been suggested to be effective for surgical skill assessment. However, prior research is mostly based on static images and simulated tasks that may not translate to complex and dynamic surgical scenes. Therefore, eye-gaze metrics must advance to account for changes in the location of important information during a surgical procedure.

Methods

We developed a dynamic AOI generation technique based on eye gaze collected from an expert viewing surgery videos. This AOI updated as the gaze of the expert moved with changes in the surgical scene. This technique was evaluated through an experiment recruiting a total of 20 attendings and residents to view 10 videos associated with and another 10 without adverse events.

Results

Dwell time percentage (i.e., gaze duration) inside the AOI differentiated video type (U = 13508.5, p < 0.001) between videos with the presence (Mdn = 16.75) versus absence (Mdn = 19.95) of adverse events. This metric also differentiated participant group (U = 14029.5, p < 0.001) between attendings (Mdn = 15.45) and residents (Mdn = 19.80). This indicates that our dynamic AOIs reflecting the expert eye gaze was able to differentiate expertise, and the presence of unexpected adverse events.

Conclusion

This dynamic AOI generation technique produced dynamic AOIs for deriving eye-gaze metrics that were sensitive to expertise level and event characteristics.

Keywords

Eye tracking Laparoscopic surgery Area of interest Expertise Surgical events 

Notes

Acknowledgements

We are grateful to all the attendings and residents who volunteered to participate in this study.

Funding

This research was supported through a Center for Excellence in Surgical Education, Research and Training (CESERT) Grant of the Association for Surgical Education (#16-01), and a Research Acceleration Program Grant of Carilion Clinic (#65111).

Compliance with ethical standards

Disclosures

Eric Fichtel, Nathan Lau, Sarah Hendrickson Parker, Siddarth Ponnala, Juyeon Park, Shimae Fitzgibbons, and Shawn D. Safford have no conflicts of interest or financial ties to disclose.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Grado Department of Industrial and Systems EngineeringVirginia TechBlacksburgUSA
  2. 2.Virginia Tech Carilion School of Medicine and Carilion ClinicVirginia TechRoanokeUSA
  3. 3.Virginia Tech Carilion Research InstituteVirginia TechRoanokeUSA
  4. 4.Department of Industrial and Systems EngineeringUniversity of Wisconsin-MadisonMadisonUSA
  5. 5.Department of SurgeryMedStar Georgetown University HospitalWashingtonUSA
  6. 6.Department of Surgery, Virginia Tech Carilion School of Medicine and Carilion ClinicVirginia TechRoanokeUSA

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