Electrosurgical Generator Control Using Real Tissue Impedance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current electrosurgery systems require computationally intensive calculations to determine tissue impedance, which is resource-intensive and complex, making real-time control challenging.
Innovation Solution
The use of averaging filters to calculate root mean square (RMS) voltage, RMS current, and average power, allowing for the determination of tissue impedance with lower computational complexity, enabling efficient control of electrosurgical energy application using commonly available microprocessors and signal processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex computations (e.g., Goertzel algorithm) are used to calculate tissue impedance, then measurement precision is improved, but device complexity and processing power requirements increase
Solution Approach 1:
The patent extracts only the real part of tissue impedance (resistive component) rather than calculating the full complex impedance. This is achieved by using a Hilbert transform-based approach that separates the real and imaginary parts, allowing the controller to use only the real part for power calculations, thereby reducing computational complexity while maintaining measurement precision for the relevant parameter
Solution Approach 2:
The patent replaces complex signal processing algorithms (Goertzel algorithm) with a Hilbert transform-based method that uses averaging filters. This substitution reduces the computational burden on the digital signal processor while achieving the same goal of determining tissue impedance characteristics for power control
2Measurement precision
If complex phase computations and frequency-dependent analyses are performed, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent extracts only the necessary information (real part of impedance) from the voltage and current waveforms using Hilbert transform and averaging filters, eliminating the need for full complex phase computations and frequency-dependent analyses. This extraction approach maintains measurement precision for power control while significantly reducing processing time to enable real-time operation
Solution Approach 2:
The patent applies averaging filters as a preliminary step to the voltage and current waveforms before computing the Hilbert transform. This preliminary filtering reduces noise and stabilizes the signals, which simplifies subsequent processing and enables faster real-time computation of the real impedance part without sacrificing measurement accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces computational complexity, enabling precise real-time control of electrosurgical energy application, improving the efficiency and accuracy of electrosurgery procedures by eliminating the need for complex phase computations and frequency-dependent analyses.
Implementation Method 1
The signal processor determines a root mean square (RMS) voltage, an RMS current, an average power, and a real part of an impedance based on the voltage waveform and the current waveform using a plurality of averaging filters
Implementation Method 2
The tissue's impedance converts the electrical energy (also referred to as electrosurgical energy) associated with the AC into heat, which causes the tissue temperature to rise
Data Source
AI summary
An electrosurgical generator and associated methods determine a real part of the impedance of treated tissue. The electrosurgical generator includes an output stage, a plurality of sensors, and a controller that controls the output stage. The controller includes a signal processor that determines an RMS voltage, an RMS current, an average power, and a real part of the impedance of the treated tissue based on measured voltage and current by using a plurality of averaging filters. The controller controls the output stage to generate electrosurgical energy based on at least the determined real part of the impedance.