Towards Autonomous Robotic Electrosurgery via Thermal Imaging

2025-09-23

AI Summary

In electrosurgical procedures, maintaining a constant tool velocity fails to accommodate dynamic variations in tissue properties, power settings, and instrument types, often resulting in exacerbated thermal injury or cutting failure. To address this, we propose ThERMO—a novel method that introduces infrared thermography into electrosurgical speed regulation for the first time. ThERMO establishes a closed-loop velocity modulation system driven by real-time temperature feedback, enabling concurrent optimization of thermal accumulation and mechanical loading. The approach integrates infrared thermal sensing, dynamic temperature modeling, and an adaptive control algorithm, supporting autonomous decision-making and online adjustment under environmental disturbances. In tissue-mimicking phantom experiments, ThERMO triples cutting success rate compared to constant-velocity control, reduces peak cutting force by 50%, and eliminates catastrophic failures entirely—significantly enhancing safety and robustness in autonomous robotic electrosurgery.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Natural Language Processing: Safety and Robustness
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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.

Problem

• Autonomous electrosurgery lacks optimal velocity control for tissue cutting
• Constant tool velocity approach is not robust to changing surgical conditions
• Thermal injury risk exists without quantifiable feedback during electrosurgery

Innovation

• Autonomous tool velocity control via thermal imaging
• Optimization-based rate modulation for electrosurgery
• Real-time response to varying tissue characteristics