Automation of power adaptation for electrosurgery

Well-selected power with accurate delivery is of importance in electrosurgery to generate proper temperature at the cutting site, and thus, reduce undesired collateral tissue damages. The power reference setpoint is determined either based on temperature or impedance. Bao et al. [1] present PI controller for power adaptation using commercially low-cost industrial-scale digital signal processor (DSP). In this thesis different control algorithms for cutting and coagulation modes for power tracking are explored. The plant models are based on data obtained from electrosurgery experiments on live pigs. The controllers explored are: Linear Quadratic Regulator (LQR), General Predictive Control (GPC), and Direct methods. In LQR and GPC the reference current is updated in real-time to ensure power tracking using linear models. Moreover, the moving window approach is used to achieve faster adaptation. Further to assess the non-linearity in the plant model, wavelet based Non-linear Autoregressive model with Exogenous inputs are derived. To sample and precisely reconstruct signals of hundreds of kilohertz it is proposed to use Xilinx field-programmable gate array (FPGA). The implementation steps and results from these analyses are presented.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2024

Author dc:creator

• Prakash, Praveen

Contributors dc:contributor

• Bentsman, Joseph

• Electrosurgery
• Power Adaptation
• Power Tracking
• Control
• Cutting
• Coagulation
• Fpga
• Gpc
• Generalized Predictive Control

Statement dc:rights

• Copyright 2024 Praveen Prakash

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/124683

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F124683