Infinite-Dimensional Adaptive Boundary Observer for Inner-Domain Temperature Estimation of 3D Electrosurgical...

Area of Science:

• Biomedical Engineering
• Surgical Technology
• Thermodynamics

Background:

• Accurate subsurface temperature determination is critical for safe and effective electrosurgery.
• Current methods may lack precision in dynamic surgical environments.
• Robotic surgery demands advanced real-time monitoring solutions.

Purpose of the Study:

• To develop a novel 3D adaptive observer for estimating subsurface organic tissue temperatures during electrosurgery.
• To integrate real-time surface temperature data from infrared thermography for enhanced observation and parameter estimation.
• To adapt the framework for the specific demands of robotic surgery settings.

Main Methods:

• A 3D adaptive observer framework utilizing pointwise 2D surface temperature readings.
• A novel decoupled parameter adaptation and estimation approach.
• Attention-based noise-robust averaging for real-time diffusivity estimation.
• A Luenberger-type corrector for temperature field observation.
• A new nonlinear input mapping for modeling electrosurgical heat distribution in robotic surgery.

Main Results:

• Demonstrated satisfactory performance of the adaptive observer in simulations.
• Validated the approach using ex vivo porcine tissue data.
• Achieved real-time parameter estimation and observer loop operation on different time scales.

Conclusions:

• The novel 3D adaptive observer framework enables accurate subsurface temperature determination in electrosurgery.
• The decoupled estimation and adaptation strategy enhances real-time monitoring capabilities.
• The framework shows promise for integration into robotic surgery systems for improved thermal management.