Computational Fibrillation Source Localization From 12-Lead ECG
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Solution Overview
Problem
Current methods for identifying the location of ventricular fibrillation (VF) and atrial fibrillation (AF) sources are invasive, costly, and time-consuming, often requiring expensive equipment like 64-electrode basket catheters and body surface vests, posing risks to patients.
Innovation Solution
A non-invasive system using twelve-lead electrocardiogram sensors and computational modeling to generate and compare heart representations, allowing for the identification of fibrillation sources through correlation analysis and machine learning algorithms, utilizing patient-specific and general computational heart models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive procedures with 64-electrode basket catheters are used to identify fibrillation sources, then measurement precision is improved, but device complexity and patient risk increase
Solution Approach 1:
The patent creates a computational model that copies and simulates the electrical behavior of the patient's heart using non-invasive ECG data. Instead of physically inserting complex catheter systems, the invention generates a virtual replica of cardiac electrical activity that can be analyzed to locate fibrillation sources, thereby achieving measurement precision without the device complexity and patient risk of invasive procedures
Solution Approach 2:
The patent replaces the mechanical invasive catheter-based measurement system with a computational modeling system that processes non-invasive ECG signals. The mechanical insertion of 64-electrode basket catheters is substituted by algorithmic analysis of surface ECG data through computational heart models, eliminating the need for complex physical devices while maintaining diagnostic capability
2Measurement precision
If invasive basket catheters and body surface vests are used for mapping arrhythmias, then fibrillation source identification is improved, but loss of time and procedure cost increase
Solution Approach 1:
The patent performs preliminary computational modeling and simulation before invasive procedures would be needed. By pre-processing non-invasive ECG data through computational heart models to identify potential fibrillation sources, the system prepares diagnostic information in advance, reducing the need for time-consuming invasive mapping procedures and allowing clinicians to plan targeted interventions more efficiently
3Measurement precision
If body surface vests with multiple electrodes are used, then measurement precision is improved, but ease of operation deteriorates due to pad placement interference
Solution Approach 1:
The patent extracts the essential diagnostic information from a simplified 12-lead ECG configuration, removing the need for complex body surface vests with numerous electrodes. By isolating and analyzing the critical electrical activation patterns from standard ECG leads through computational modeling, the system achieves arrhythmia mapping capability without the operational complexity of placing multiple surface electrodes that would interfere with defibrillator pad positioning
Data Source
AI summary
A system for computational localization of fibrillation sources is provided. In some implementations, the system performs operations comprising generating a representation of electrical activation of a patient's heart and comparing, based on correlation, the generated representation against one or more stored representations of hearts to identify at least one matched representation of a heart. The operations can further comprise generating, based on the at least one matched representation, a computational model for the patient's heart, wherein the computational model includes an illustration of one or more fibrillation sources in the patient's heart. Additionally, the operations can comprise displaying, via a user interface, at least a portion of the computational model. Related systems, methods, and articles of manufacture are also described.