Evaluating Human-Robot Interfaces for Maneuvering Surgical Laparoscopes using Robotic Scope Assistant Systems

Abstract

Robotic scope assistant systems allow surgeons to adjust the operative field view during surgery by robotically maneuvering laparoscopes. A Human-Robot Interface (HRI) is used for issuing commands to these systems, with an interaction mode mapping these commands to laparoscope movements. Optimizing the HRI and interaction mode can streamline laparoscope positioning as well as reduce cognitive workload, helping the surgeon focus on the surgical procedure. Comparing and assessing various HRIs and interaction modes is essential for efficient laparoscope maneuvering. This study evaluates HRIs based on head-motion, eye-motion, hand-motion, and voice-input operating under three interaction modes (namely: discrete, continuous, and threshold). The participants performed a user study comparing different HRIs under two simulated surgical scenarios (one in a real environment and the other in a virtual environment). The results indicated that head and eye-based HRIs performed well in continuous interaction mode, while the voice-based interface suffered from a delay. Conversely, hand-based HRIs demonstrated superior performance in both scenarios across all evaluation parameters. The study provides a benchmark for the comparison of different HRIs and provides insights into the effectiveness, limitations, and potential advantages of different HRIs.