Abstract
Background. Evaluation of microsurgical proficiency is conventionally subjective, time consuming, and unreliable. Eye movement-based metrics have been promising not only in detection of surgical expertise but also in identifying actual cognitive stress and workload. We investigated if pupil dilations and blinks could be utilized in parallel to accurately classify microsurgical proficiency and its moderating features, especially task-related stress. Methods. Participants (n = 11) were divided into groups based on prior experience in microsurgery: novices (n = 6) with no experience and trained microsurgeons (n = 5). All participants conducted standardized suturing tasks with authentic instruments and a surgical microscope. A support vector machine classifier was used to classify features of microsurgical expertise based on percentage changes in pupil size. Results. A total of 109 successful sutures with 1090 segments were recorded. Classification of expertise from sutures achieved accuracies between 74.3% and 76.0%. Classification from individual segments based on these same features was not feasible. Conclusions. Combined gaze metrics are applicable for classifying surgical proficiency during a defined task. Pupil dilation is also sensitive to external stress factors; however, the usefulness of blinks is impaired by low blink rates. The results can be translated to surgical education to improve feedback and should be investigated individually in the context of actual performance and in real patient operations. Combined gaze metrics may be ultimately utilized to help microsurgeons monitor their performance and workload in real time-which may lead to prevention of errors.