Measuring the Quality of Learning in a Human–Robot Collaboration: A Study of Laparoscopic Surgery

Abstract

Robot-Assisted Laparoscopic Surgery (RALS) is now prevalent in operating rooms. This situation requires future surgeons to learn Classic Laparoscopic Surgery (CLS) and RALS simultaneously. Therefore, along with the investigation of the differences in performance between the two techniques, it is essential to study the impact of training in RALS on the skills mastered in CLS. In this article, we study comanipulated RALS (Co-RALS), one of the two designs for RALS, where the human and the robot share the execution of the task. We use a rarely used in Human–Robot Interaction measuring tool: gaze tracking and time recording to measure for the acquisition of skills in CLS when training in Co-RALS or in CLS and time recording to compare the learning curves between Co-RALS and CLS. These metrics allow us to observe differences in Co-RALS and CLS. Training in Co-RALS develops slightly better but not significantly better hand–eye coordination skills and significantly better timewise performance compared with training in CLS alone. Co-RALS enhances timewise performance in laparoscopic surgery on specific types of tasks that require precision rather than depth perception skills compared with CLS. The results obtained enable us to further define the Human–Robot Interaction quality in Co-RALS.