An eye-tracking based robotic scrub nurse: proof of concept

Area of Science:

• Robotics in Surgery
• Human-Robot Interaction
• Surgical Simulation

Background:

• Assistive robotic devices (ARD) enhance surgical outcomes by providing additional dexterity.
• Conventional laparoscopy has limitations that ARD can overcome.
• An eye-tracking based robotic scrub nurse (RSN) was developed for mobile, hands-free intra-operative assistance.

Purpose of the Study:

• To evaluate the efficacy and acceptance of an eye-tracking based RSN in a simulated surgical environment.
• To compare the RSN system's performance against a human scrub nurse (HSNt).
• To assess surgeon workload, technology acceptance, and team communication.

Main Methods:

• Surgeons performed simulated colon resections and anastomosis using eye-tracking glasses (ETG) and RGB-D sensors.
• The RSN system assisted in instrument selection and transfer based on surgeon gaze.
• Data collected included task load (NASA-TLX), technology acceptance (Van der Laan's), performance metrics, and communication.

Main Results:

• No significant differences in mental, physical, or temporal demands were found between RSN and HSNt assistance.
• Surgeons reported higher frustration with the RSN system but also positive usefulness and satisfaction.
• No significant difference in operating time was observed between the two assistance methods.

Conclusions:

• The eye-tracking based RSN enables mobile, hands-free human-robot interaction during surgery.
• The RSN platform is non-inferior to HSNt and accepted by surgical and HSN test users.
• Initial findings support the potential of RSN for enhancing surgical procedures.