Atrial Signal Extraction from QRS Complexes Using Singularity Segmentation
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Solution Overview
Problem
Current diagnostic tools for cardiac rhythm disorders, such as atrial fibrillation, lack precision in locating and distinguishing between active and passive rotors, leading to inadequate cardiac ablation procedures and recurrence of atrial tachyarrhythmia.
Innovation Solution
A system and method for extracting atrial signals from electrical signals using electrographic flow techniques, which involve processing body surface and intracardiac electrograms to generate flow maps that identify the sources of cardiac rhythm disorders with enhanced precision, allowing for targeted ablation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current diagnostic tools (TOPERA system) are used to localize AF drivers, then the system provides rotor identification, but the spatial and temporal resolution is insufficient to detect singularities associated with active rotor generation
Solution Approach 1:
The patent segments the electrogram signal into discrete components by identifying singularities (points of infinite gradient) in the time derivative of unipolar EGMs. This segmentation allows precise localization of rotor sources by breaking down the continuous signal into discrete event markers, thereby improving spatial and temporal resolution without requiring overly complex hardware
Solution Approach 2:
The patent transitions from analyzing only the amplitude dimension of EGM signals to incorporating the temporal derivative dimension. By calculating the time derivative and identifying singularities in this new dimension, the system achieves higher precision in detecting rotor generation events, effectively adding a temporal rate-of-change dimension to the analysis
2Reliability
If TOPERA FIRM technology is used for rotor ablation, then rotor locations are identified, but the results are inferior to non-specific ablation and require parallel PVI for therapeutic success
Solution Approach 1:
The patent performs preliminary identification of singularity locations and classification of rotors as active or passive before ablation. By pre-characterizing the arrhythmia sources with higher precision, the system enables more targeted and effective ablation procedures, improving success rates and reducing the need for additional procedures like PVI
Solution Approach 2:
The patent implements a feedback mechanism where singularity detection and rotor classification inform subsequent ablation targeting. The system continuously monitors EGM signals, identifies singularities, classifies rotor types, and uses this information to guide ablation therapy, creating a closed-loop system that improves reliability and efficiency
3Adaptability or versatility
If Omnipolar Mapping is used to measure conduction velocity and direction, then beat-by-beat conduction is assessed, but the method remains incapable of dealing successfully with complex data sets during AF episodes
Solution Approach 1:
The patent extracts the essential feature of singularity points from complex EGM datasets during AF episodes. By focusing only on the critical singularity events rather than attempting to process all conduction data, the system maintains measurement precision while gaining the ability to successfully handle complex arrhythmia datasets
Solution Approach 2:
The patent changes the analytical parameter from continuous conduction velocity measurement to discrete singularity detection. This parameter transformation allows the system to handle complex AF datasets effectively by identifying key temporal markers rather than attempting to resolve all conduction variations, thereby improving adaptability without sacrificing essential measurement accuracy
Data Source
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AI summary
Disclosed are various examples and embodiments of systems, devices, components and methods configured to extract atrial signals from electrical signals acquired from a patient suffering from atrial fibrillation. The electrical signals acquired from the patient may be intra-cardiac signals or body surface electrode signals, or both. At least portions of QRS or QRS-T complexes corresponding to determined initial synchronization times are used to generate Fast Fourier Transforms (FFTs) corresponding to the extracted QRS complexes. A series of steps follow to generate isolated atrial signals corresponding to each electrical signal by subtracting generated reconstructed signals corresponding to each such electrical signal therefrom.