Infinite-Dimensional Adaptive Boundary Observer for Inner-Domain Temperature Estimation of 3D Electrosurgical Processes using Surface Thermography Sensing

TL;DR

This paper introduces a novel 3D adaptive observer framework for estimating subsurface tissue temperatures during electrosurgery, utilizing surface thermography data and a new parameter estimation method to improve real-time temperature monitoring.

Contribution

It presents a new decoupled parameter adaptation approach and a model tailored for robotic surgery, enabling real-time diffusivity estimation and temperature observation.

Findings

Demonstrated effective temperature estimation in simulation

Validated diffusivity estimation with real ex vivo tissue data

Achieved satisfactory observer performance in realistic scenarios

Abstract

We present a novel 3D adaptive observer framework for use in the determination of subsurface organic tissue temperatures in electrosurgery. The observer structure leverages pointwise 2D surface temperature readings obtained from a real-time infrared thermographer for both parameter estimation and temperature field observation. We introduce a novel approach to decoupled parameter adaptation and estimation, wherein the parameter estimation can run in real-time, while the observer loop runs on a slower time scale. To achieve this, we introduce a novel parameter estimation method known as attention-based noise-robust averaging, in which surface thermography time series are used to directly estimate the tissue's diffusivity. Our observer contains a real-time parameter adaptation component based on this diffusivity adaptation law, as well as a Luenberger-type corrector based on the sensed surface temperature. In this work, we also present a novel model structure adapted to the setting of robotic surgery, wherein we model the electrosurgical heat distribution as a compactly supported magnitude- and velocity-controlled heat source involving a new nonlinear input mapping. We demonstrate satisfactory performance of the adaptive observer in simulation, using real-life experimental ex vivo porcine tissue data.