An Intelligent System for Skills Assessment in Surgical Training

The technical skill level of a surgeon has a significant effect on patients’ surgical outcomes. In the current proficiency-based training of technical surgical skills, an accredited medical educator views the procedure to provide feedback, which is time-consuming, labor-intensive, and subjective. This research developed an automated system to facilitate the work of senior surgeons. More specifically, we introduced data surgical gloves with gold nanowires motion sensors embedded to track the motion of the trainees. We also proposed several machine learning algorithms to analyze recorded signals from the data gloves to automatedly and objectively evaluate the surgical skills with high accuracy.