Arrhythmia Driver Connectivity Analysis via Wave Front Trajectories
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Solution Overview
Problem
Current methods for detecting and analyzing arrhythmia drivers in cardiac arrhythmia are inadequate in identifying connected trajectories and characterizing their connectivity associations, which are crucial for guiding treatment and therapy.
Innovation Solution
A system and method that analyze electrical data to identify wave front lines, determine trajectories, and characterize connectivity associations between them using spatial and temporal criteria, generating graphical maps to visualize these connections and guide treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used for detecting arrhythmia drivers, then the detection process is simple, but the ability to identify connected trajectories and characterize their connectivity associations is inadequate
Solution Approach 1:
The patent segments the complex task of arrhythmia driver detection into distinct modules: wave front line identification, trajectory determination, connectivity detection, and connectivity characterization. Each module handles a specific aspect of the analysis, making the overall system more manageable and precise in identifying connected trajectories and their associations.
2Loss of information
If detailed trajectory analysis is performed to identify connected trajectories, then the characterization of arrhythmia drivers is improved, but the computational complexity and data processing requirements increase
Solution Approach 1:
The patent extracts and focuses specifically on the connectivity aspects of trajectories by implementing a dedicated connectivity detection module. This module isolates the relevant information about trajectory connections and characterizes them separately, ensuring that important connectivity information is not lost while managing data processing complexity through focused analysis.
3Measurement precision
If wave front lines and trajectories are analyzed across multiple time intervals, then the accuracy of arrhythmia driver identification is improved, but the time required for analysis increases
Solution Approach 1:
The patent performs preliminary analysis by identifying wave front lines and trajectories across multiple time intervals in advance, storing this information for subsequent connectivity analysis. This preliminary action allows the system to have precise location data ready before the final arrhythmia driver identification, improving precision while managing analysis time through staged processing.
Data Source
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AI summary
One or more non-transitory computer-readable media have instructions executable by a processor and programmed to perform a method. The method includes analyzing the electrical data to locate one or more wave front lines over a given time interval. The electrical data represents electrophysiological signals distributed across a cardiac envelope for one or more time intervals. A respective trajectory is determined for each wave end of each wave front line that is located across the cardiac envelope over the given time interval. A set of connected trajectories are identified based on a duration that the trajectories are connected to each other by a respective wave front line during the given time interval. A connectivity association is characterized for the trajectories in the set of connected trajectories.