Electrogram Activation Sequence Analysis for Atrial Fibrillation
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Solution Overview
Problem
Current methods for detecting local rhythms during atrial fibrillation struggle to differentiate between competing activation rhythms, especially in chaotic and complex cases, leading to challenges in accurately assessing the severity and treatment options.
Innovation Solution
The method incorporates additional cost components based on characteristics of activation candidates, such as morphology and cross-channel similarities, to optimize the identification of physiologically valid sequences, using a cost function that considers both the jumps and characteristics of activation candidates, and accounts for clinical use and electrode consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If the complexity of atrial fibrillation increases with more competing rhythms, then the difficulty of detecting local rhythms increases, but the accuracy of rhythm identification deteriorates
Solution Approach 1:
The patent segments the electrogram signal into multiple activation candidates and groups them into potential sequences based on temporal proximity and morphological similarity. This segmentation allows the system to analyze individual activation events separately before integrating them into rhythmic patterns, making it easier to distinguish local activations from far-field potentials even in complex fibrillation scenarios.
Solution Approach 2:
The patent applies local quality by evaluating morphological characteristics of activation candidates specific to each location. By assigning different weights and criteria to activations based on their local morphological features and spatial relationships, the system can identify locally generated activations versus propagated potentials, improving accuracy in complex rhythms.
2Productivity
If more activation candidates are considered in the analysis, then the completeness of rhythm detection improves, but the computational complexity increases
Solution Approach 1:
The patent employs partial action by considering only activation candidates that meet specific criteria (temporal proximity, morphological similarity) rather than analyzing all possible candidates exhaustively. This selective approach maintains detection completeness for relevant rhythms while reducing computational burden by filtering out obviously irrelevant activations.
Solution Approach 2:
The patent performs preliminary grouping of activation candidates into potential sequences before full rhythm analysis. By pre-organizing candidates based on temporal and morphological characteristics, the system reduces the search space for subsequent rhythm identification, improving efficiency while maintaining comprehensive detection.
3Device complexity
If the cost function considers only jump lengths between activations, then the simplicity of the algorithm is maintained, but the ability to distinguish local from far-field potentials deteriorates
Solution Approach 1:
The patent merges multiple cost components into a unified cost function that evaluates both jump lengths and morphological characteristics. By combining temporal distance penalties with morphological similarity weights, the algorithm maintains relative simplicity while gaining the ability to distinguish local activations from far-field potentials through integrated evaluation.
Solution Approach 2:
The patent changes parameters in the cost function by introducing morphological similarity metrics and activation candidate characteristics alongside traditional jump length measurements. This parameter expansion allows the algorithm to capture both temporal and morphological aspects of activations, improving discrimination capability without fundamentally altering the optimization framework.
Data Source
AI summary
A method for analyzing an electrogram (1), via a control system, that has been recorded via a catheter inserted into a human body, which includes multiple electrodes. At least one channel (K) of the electrogram has been recorded by, preferably between, the electrodes. The control system detects activation candidates (3) in a first channel (K_a). Multiple different potential sequences (4) of activation candidates are defined along the time dimension (5) of the first channel. The control system assigns costs including one or more independent cost components to the potential sequences, selects a sequence of dominant activations from the potential sequences of the first channel, selects the sequence of dominant activations that fulfills an optimization criterion based on the costs of the potential sequences, and assigns cost components to activation candidates. The costs of the potential sequences include the cost components of the activation candidates defining the respective potential sequence.