TY - GEN
T1 - Differentiating Surgeons' Expertise solely by Eye Movement Features
AU - Hosp, Benedikt
AU - Yin, Myat Su
AU - Haddawy, Peter
AU - Watcharopas, Ratthapoom
AU - Sa-Ngasoongsong, Paphon
AU - Kasneci, Enkelejda
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/10/18
Y1 - 2021/10/18
N2 - Medical schools are increasingly seeking to use objective measures to assess surgical skills. This extends even to perceptual skills, which are particularly important in minimally invasive surgery. Eye tracking provides a promising approach to obtaining such objective metrics of visual perception. In this work, we report on results of a cadaveric study of visual perception during shoulder arthroscopy. We present a model for classifying surgeons into three levels of expertise using only eye movements. The model achieves a classification accuracy of 84.44% using only a small set of selected features. We also examine and characterize the changes in visual perception metrics between the different levels of expertise, forming a basis for development of a system for objective assessment.
AB - Medical schools are increasingly seeking to use objective measures to assess surgical skills. This extends even to perceptual skills, which are particularly important in minimally invasive surgery. Eye tracking provides a promising approach to obtaining such objective metrics of visual perception. In this work, we report on results of a cadaveric study of visual perception during shoulder arthroscopy. We present a model for classifying surgeons into three levels of expertise using only eye movements. The model achieves a classification accuracy of 84.44% using only a small set of selected features. We also examine and characterize the changes in visual perception metrics between the different levels of expertise, forming a basis for development of a system for objective assessment.
KW - diagnostic
KW - eye
KW - machine learning
KW - model
KW - surgeon
KW - tracking
UR - http://www.scopus.com/inward/record.url?scp=85122257496&partnerID=8YFLogxK
U2 - 10.1145/3461615.3485437
DO - 10.1145/3461615.3485437
M3 - Conference contribution
AN - SCOPUS:85122257496
T3 - ICMI 2021 Companion - Companion Publication of the 2021 International Conference on Multimodal Interaction
SP - 371
EP - 375
BT - ICMI 2021 Companion - Companion Publication of the 2021 International Conference on Multimodal Interaction
PB - Association for Computing Machinery, Inc
T2 - 23rd ACM International Conference on Multimodal Interaction, ICMI 2021
Y2 - 18 October 2021 through 22 October 2021
ER -