Motion analysis for objective evaluation of psychomotor skills in Endoscopic Sinus Surgery.

Background: This study aims to digitalize surgical maneuvers in ESS using a motion capture system under standardized conditions provided by 3D printed-sinus models.

Methodology: Forty-seven otolaryngologists performed ESS on 3D printed models manufactured from computed tomography (CT) images of actual patients. Participants were classified to 3 groups according to the objective structured technical skills assessment score. All surgical maneuverers performed during ESS were captured by a motion capture system. The path length, velocity, acceleration, and jerk were calculated for each surgical instrument and compared among the groups. Principle Component Analysis (PCA) was utilized to identify which metrics reflected surgical skill level. In addition, ten registrars repeated the surgical dissection. Their motion metrics were also compared between first training and the repeated training and then subjected to the PCA.

Results: Several metrics such as the angular acceleration and jerk of the cutting forceps were identified by PCA as possible indicators distinguishing the different skill levels for the ESS maneuvers. PCA analysis in the repetitive training also found the angular metrics of the upturned-cutting forceps correlating to their skill improvement.

Conclusions: Combined with the validated 3D-printed sinus models, the motion capture system provided the objective evaluation of the surgical performances of ESS.