Design and Implementation of a Compact RF Power Sampling Generator for Low-EMI Operation

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Authors: Roland Szand, József Kopják, Gergely Sebestyén
Cited by: 3
References: 11

Abstract

High-frequency electromagnetic interference (EMI) and energy-transfer losses in electrosurgical systems influence cutting quality, the operation of surrounding equipment, and experimental reproducibility in laboratory environments. Previous studies have shown that the RF cable connecting the generator and the active electrode introduces parasitic capacitances and inductive effects that contribute to electromagnetic emission and reduced energy-transfer efficiency. In addition, commercially available electrosurgical generators typically employ fixed control logic and predefined operating modes, which limits the ability to systematically vary electrical parameters for experimental investigations. These constraints become particularly relevant in robotic and laboratory setups, where controlled excitation conditions and compact integration are required.This study investigates the feasibility of a compact laboratory RF generator platform that provides adjustable output voltage, current, and operating frequency. By minimizing the RF output path length and reducing system mass, the prototype can be positioned close to the sample or integrated on a robotic arm, supporting range-finding studies that are not achievable with conventional clinical generators. Initial operation was demonstrated at 511.2 kHz, where the system proved suitable for tissue cutting and produced evaluable signals for evaporation-based mass spectrometry sampling at reduced voltage levels. The results indicate that a parameterizable, compact RF generator platform is well suited for laboratory and robotic research requiring controlled variation of electrical excitation parameters.

Fields of Study & Subjects

Thyroid and Parathyroid Surgery Electromagnetic Fields and Biological Effects Wireless Body Area Networks

Publication details

Journal / source
2026 IEEE 24th World Symposium on Applied Machine Intelligence and Informatics (SAMI)
Publisher
IEEE
Pages
000715–000720
Publication date
29 January 2026