Towards Autonomous Robotic Electrosurgery via Thermal Imaging

Abstract

Electrosurgery is a surgical technique that can improve tissue cutting by reducing cutting force and bleeding. However, electrosurgery adds a risk of thermal injury to surrounding tissue. Expert surgeons estimate desirable cutting velocities based on experience but have no quantifiable reference to indicate if a particular velocity is optimal. Furthermore, prior demonstrations of autonomous electrosurgery have primarily used constant tool velocity, which is not robust to changes in electrosurgical tissue characteristics, power settings, or tool type. Thermal imaging feedback provides information that can be used to reduce thermal injury while balancing cutting force by controlling tool velocity. We introduce Thermography for Electrosurgical Rate Modulation via Optimization (ThERMO) to autonomously reduce thermal injury while balancing cutting force by intelligently controlling tool velocity. We demonstrate ThERMO in tissue phantoms and compare its performance to the constant velocity approach. Overall, ThERMO improves cut success rate by a factor of three and can reduce peak cutting force by a factor of two. ThERMO responds to varying environmental disturbances, reduces damage to tissue, and completes cutting tasks that would otherwise result in catastrophic failure for the constant velocity approach.