Cardiac Activation Reconstruction via Divergence Criteria
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Solution Overview
Problem
Current systems fail to accurately identify and reconstruct cardiac activation information in complex heart rhythm disorders, such as atrial fibrillation, ventricular tachycardia, and ventricular fibrillation, due to overlapping electrical waves and far-field activations, making it difficult to determine the source of the disorder and target it for effective treatment.
Innovation Solution
A method that involves accessing neighboring cardiac signals, eliminating far-field activations using divergence criteria, and constructing a clinical representation of local activations to accurately determine activation onset times and identify the source of the disorder, allowing for precise targeting and treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional signal processing methods are used to analyze cardiac signals in complex rhythm disorders, then the analysis process is simplified, but the accuracy of identifying local activation onsets deteriorates due to overlapping electrical waves and far-field activations
Solution Approach 1:
The method segments cardiac signals by comparing neighboring electrogram signals to identify points of change where local activations occur. By dividing the continuous cardiac signal into discrete activation events based on divergence criteria, the system can distinguish local activations from far-field activations and overlapping waves, improving measurement precision without requiring overly complex processing
Solution Approach 2:
The invention introduces an intermediary computational step that compares pairs of neighboring electrogram signals to detect points of change. This intermediary process of comparing adjacent signals serves as a mediator to identify local activation onsets, enabling accurate detection even in the presence of complex overlapping electrical waves and far-field activations
2Productivity
If ablation therapy is performed without accurate identification of the earliest activation location, then treatment can be delivered quickly, but the efficacy of treating complex rhythm disorders deteriorates
Solution Approach 1:
The system performs preliminary identification of the earliest activation location and construction of a clinical representation before ablation therapy is delivered. By pre-identifying the precise target location through signal analysis and divergence criteria, the system enables rapid subsequent delivery of ablation energy to the correct site, achieving both high productivity and reliability
3Quantity of substance
If multiple sensors are used to capture cardiac electrical activity, then more comprehensive data is obtained, but the difficulty of distinguishing local from far-field activations increases
Solution Approach 1:
The method segments and compares signals from multiple neighboring sensors to identify points of change. By systematically comparing each sensor's signal with its neighbors and applying divergence criteria, the system can distinguish local activations (which appear as points of change in multiple neighboring signals) from far-field activations, making the discrimination process more manageable despite the large quantity of data
Solution Approach 2:
The invention merges information from multiple neighboring electrogram signals through comparison and analysis. By combining the data from multiple sensors and identifying consistent points of change across neighboring signals, the system enhances the ability to distinguish local from far-field activations, transforming the challenge of multiple data sources into an advantage for accurate localization
Data Source
AI summary
Reconstruction of cardiac information associated with a heart rhythm disorder includes accessing a plurality of neighboring cardiac signals and eliminating far-field activations from the neighboring cardiac signals using one or more divergence criteria that define local activations, where the divergence criteria is associated with divergence among the plurality of neighboring cardiac signals. The local activations in the plurality of neighboring cardiac signals may be used to construct a clinical representation of the heart rhythm disorder.