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Assessing Medical Training Skills via Eye and Head Movements
LATIFZADEH, Kayhan; LEIVA, Luis A.; Čopič Pucihar, Klen et al.
2025In UMAP '25: Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization
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Keywords :
eye movements; head movements; simulation training
Abstract :
[en] We examined eye and head movements to gain insights into skill development in clinical settings. A total of 24 practitioners participated in simulated baby delivery training sessions. We calculated key metrics, including pupillary response rate, fixation duration, or angular velocity. Our findings indicate that eye and head tracking can effectively differentiate between trained and untrained practitioners, particularly during labor tasks. For example, head-related features achieved an F1 score of 0.85 and AUC of 0.86, whereas pupil-related features achieved F1 score of 0.77 and AUC of 0.85. The results lay the groundwork for computational models that support implicit skill assessment and training in clinical settings by using commodity eye-tracking glasses as a complementary device to more traditional evaluation methods such as subjective scores.
Disciplines :
Computer science
Author, co-author :
LATIFZADEH, Kayhan  ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
LEIVA, Luis A.  ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Čopič Pucihar, Klen ;  University of Primorska, Koper, Slovenia and Stellenbosch University, Stellenbosch, South Africa
Kljun, Matjaž ;  University of Primorska, Koper, Slovenia and Stellenbosch University, Stellenbosch, South Africa
Devetak, Iztok ;  University of Ljubljana, Ljubljana, Slovenia
Steblovnik, Lili ;  University Medical Centre Ljubljana, Ljubljana, Slovenia
External co-authors :
yes
Language :
English
Title :
Assessing Medical Training Skills via Eye and Head Movements
Publication date :
13 June 2025
Event name :
The 33rd ACM Conference on User Modeling, Adaptation and Personalization (UMAP '25)
Event date :
June 16 - 19, 2025
Main work title :
UMAP '25: Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization
Publisher :
Association for Computing Machinery, New York, United States - New York
Pages :
1 - 10
Peer reviewed :
Peer reviewed
European Projects :
HE - 101071147 - SYMBIOTIK - Context-aware adaptive visualizations for critical decision making
Funders :
Horizon 2020 FET program
Slovenian Research Agency
European Innovation Council Pathfinder program
CogniCom program of the University of Primorska
European Union
Funding text :
This research is supported by the European Innovation Council Pathfinder program (SYMBIOTIK project, grant 101071147), the Slovenian Research Agency (grants N2-0354, BI-NO/25-27-007, P5-0433, IO-0035, J5-50155, J7-50096), and the CogniCom (grant 0013103) program of the University of Primorska. Authors would like to thank all medical and technical support staff of the Medical Simulation Unit of the University Medical Center Ljubljana.
Data Set :
Available on ORBilu :
since 19 June 2025

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