Evaluation of contactless human-machine interface for robotic surgical training

Area of Science:

• Robotics
• Surgical Simulation
• Human-Computer Interaction

Background:

• Teleoperated robotic systems are vital in surgery, necessitating specialized training.
• Current robotic surgical simulators are costly and require dedicated interfaces.

Purpose of the Study:

• To evaluate a low-cost, contactless optical sensor (Leap Motion) for controlling the RAVEN-II robot.
• To compare its performance against a traditional contact-based device (Sigma.7) in a peg manipulation task.

Main Methods:

• Utilized the Leap Motion sensor for robotic control in a surgical training task.
• Employed metric-based analysis and unsupervised spatiotemporal trajectory clustering for performance assessment.
• Compared contactless (Leap Motion) versus contact-based (Sigma.7) manipulation.

Main Results:

• Contactless control showed limitations in manipulability compared to the contact-based device.
• Metric-based evaluation favored the mechanical control.
• Trajectory clustering revealed distinct signatures related to each human-machine interface.

Conclusions:

• Contactless optical sensing is feasible for controlling surgical instruments, enabling dexterous laparoscopic training.
• While not surpassing high-standard mechanical interfaces, this approach shows potential for developing future robotic surgical training systems.