Published Technical Disclosure Archive

Enhanced Multi-Channel RF Ablation System with Advanced Signal Generation

Publication ID: 24-11857245_0001_PTD
Published: November 07, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Enhanced Multi-Channel RF Ablation System with Advanced Signal Generation,” Published Technical Disclosure No. 24-11857245_0001_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857245_0001_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,245.

Summary of the Inventive Concept

An improved multi-channel RF ablation system that utilizes advanced signal generation techniques, including machine learning and neural networks, to optimize the ablation process, providing enhanced safety, efficiency, and effectiveness.

Background and Problem Solved

The original patent for multi-channel RF ablation (U.S. Pat. No. 9,005,193) has limitations in terms of signal generation and application. The present inventive concept addresses these limitations by introducing advanced signal generation techniques, such as machine learning and neural networks, to optimize the ablation process and provide improved safety, efficiency, and effectiveness.

Detailed Description of the Inventive Concept

The enhanced multi-channel RF ablation system comprises a controller that generates a plurality of control signals having different respective frequencies and amplitudes, using machine learning or neural networks to predict optimal ablation parameters. The system also includes a plurality of electrodes configured to apply composite signals to a subject, produced by adding the control signals to respective ablation signals having a common frequency and phase. This advanced signal generation technique enables real-time optimization of the ablation process, reducing the risk of complications and improving treatment outcomes.

Novelty and Inventive Step

The use of machine learning and neural networks to generate control signals and optimize the ablation process is a novel and non-obvious advancement over the original patent, providing a significant improvement in safety, efficiency, and effectiveness.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept may include the use of other advanced signal generation techniques, such as adaptive filtering or real-time impedance monitoring, to further optimize the ablation process. Additionally, the system may be modified to accommodate different types of electrodes or ablation signals, expanding its applicability to various medical procedures.

Potential Commercial Applications and Market

The enhanced multi-channel RF ablation system has significant commercial potential in the medical device industry, particularly in the treatment of cardiac arrhythmias and other electrophysiology applications. The system's improved safety, efficiency, and effectiveness make it an attractive solution for hospitals and medical centers, with a potential market size of millions of dollars.

CPC Classifications

SectionClassGroup
A A61 A61B18/1206
A A61 A61B18/1492
A A61 A61B2018/00351
A A61 A61B2018/00577
A A61 A61B2018/00702
A A61 A61B2018/00732
A A61 A61B2018/00767
A A61 A61B2018/00791
A A61 A61B2018/00827
A A61 A61B2018/00875
A A61 A61B2018/00892
A A61 A61B2018/128
A A61 A61B2018/1273

Field of Art

Medical device technology, specifically radiofrequency (RF) ablation systems for cardiac and tissue treatment, requiring advanced electrical engineering, signal processing, and medical device design expertise

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer with expertise in RF energy delivery, signal modulation techniques, electrical medical device design, and advanced signal processing algorithms, holding a master's or doctoral degree with 3-5 years of specialized experience

Obviousness Rationale

A PHOSITA would recognize that applying machine learning and neural network techniques to optimize multi-channel RF ablation signal generation represents a predictable extension of existing signal modulation technologies. The source patent establishes a foundational framework for multi-frequency ablation signals, which naturally invites computational optimization techniques. The proposed variations leverage well-established machine learning approaches to enhance an existing technical process, demonstrating an obvious combination of known elements with predictable results.

Obvious Combinations & Variations

Source Patent Element
Multi-channel ablation with control signals having different frequencies and amplitudes
PTD Variation
Adding machine learning algorithms to generate and optimize control signal parameters
Obviousness Reasoning
Machine learning for signal optimization is a known technique in signal processing, representing a predictable application of computational methods to improve existing technical systems
Source Patent Element
Composite signals produced by adding control signals to ablation signals
PTD Variation
Implementing neural networks to predict optimal ablation signal characteristics
Obviousness Reasoning
Neural network prediction for signal parameters is a standard engineering approach for refining complex signal generation processes, offering incremental technical improvement
Source Patent Element
Electrode-based RF ablation with multiple signal channels
PTD Variation
Real-time feedback loops and adaptive signal generation techniques
Obviousness Reasoning
Adaptive signal generation through feedback mechanisms is a well-established control engineering technique, representing an obvious extension of existing multi-channel ablation technologies
Source Patent Element
Ablation signals with common frequency and phase
PTD Variation
Dynamic frequency and phase adjustment using machine learning algorithms
Obviousness Reasoning
Computational refinement of signal parameters is a predictable application of advanced signal processing techniques to existing RF ablation methodologies
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857245 and the disclosed technical variations, a person of ordinary skill in the art would find the proposed multi-channel RF ablation system with machine learning-based signal generation to be an obvious combination of prior art techniques, rendering potential patent claims in this domain anticipated and non-patentable under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,857,245
TitleMulti-channel RF ablation
Assignee(s)Biosense Webster (Israel) Ltd.