Intra-cardiac Pattern Matching for Arrhythmia Signal Differentiation
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Solution Overview
Problem
Conventional methods for mapping heart chamber regions that generate arrhythmias struggle to accurately distinguish arrhythmia signals from similar morphologies, leading to inaccurate visualization and identification of arrhythmia mechanisms, as they often rely solely on cycle length differentiation and are insensitive to mechanical changes caused by catheter movement.
Innovation Solution
The method involves selecting a pattern of interest from intra-cardiac electrogram signals, generating a template based on this pattern, and applying weights to subsequent signals for correlation analysis, allowing for the differentiation of arrhythmia signals based on morphology and sequence of activation, while filtering out mechanically induced beats and changes caused by catheter movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional methods rely solely on cycle length differentiation, then the mapping process is simple, but the accuracy of distinguishing arrhythmia signals from similar morphologies deteriorates
Solution Approach 1:
The patent segments the arrhythmia detection process into multiple stages: (1) identifying candidate beats based on cycle length, (2) extracting morphological features from EGM signals, (3) comparing extracted features against stored templates, and (4) classifying beats as arrhythmia or non-arrhythmia. This segmentation allows the system to achieve high accuracy by analyzing multiple signal characteristics rather than relying on cycle length alone, while maintaining manageable complexity through systematic processing steps.
Solution Approach 2:
The patent transitions from one-dimensional cycle length analysis to multi-dimensional signal analysis by extracting multiple morphological features from EGM signals, including but not limited to: peak amplitude, slope, area under the curve, and temporal characteristics. This dimensional expansion enables the system to distinguish between arrhythmia signals and similar morphologies that have identical cycle lengths, significantly improving measurement precision without excessive complexity increase.
2Quantity of substance
If signals from ectopic beats and mechanical stimulation are included in the map, then the quantity of captured signals increases, but the accuracy of the local activation map deteriorates
Solution Approach 1:
The patent extracts and removes non-arrhythmia signals from the dataset by classifying them as ectopic beats or mechanically induced artifacts. The system identifies these unwanted signals through morphological feature analysis and template comparison, then excludes them from the final activation map. This extraction process ensures that only genuine arrhythmia signals contribute to the map, maintaining high reliability while still capturing a comprehensive quantity of relevant cardiac events.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously compares extracted morphological features against stored templates of known arrhythmia patterns. When a signal deviates from expected arrhythmia morphology or shows characteristics of ectopic beats or mechanical stimulation, the feedback loop triggers reclassification or exclusion from the map. This feedback ensures that the quantity of signals included in the final map maintains high reliability.
3Measurement precision
If the system uses template-based morphological comparison, then the ability to identify arrhythmia mechanisms improves, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-storing templates of known arrhythmia morphologies and their associated features before actual signal analysis. These templates are created from previously identified arrhythmia events and include normalized morphological characteristics. During real-time analysis, the system simply extracts features and compares them against these pre-prepared templates, significantly reducing computational complexity while maintaining high precision in arrhythmia mechanism identification.
Solution Approach 2:
The patent changes parameters by normalizing morphological features to standardized ranges and transforming raw EGM signals into dimensionless feature vectors. This parameter transformation allows for efficient comparison against templates using simple thresholding and distance metrics rather than complex pattern recognition algorithms. The normalization process maintains measurement precision by preserving relative morphological relationships while reducing computational burden through simplified comparison operations.
Data Source
AI summary
Methods, apparatuses, and systems for intra-cardiac pattern matching are disclosed. A unipolar pattern intra-cardiac (IC) electromyography (EGM) signals is received for an area of a heart from a plurality of activity channels corresponding to a plurality of electrodes of a catheter. A window of interest (WOI) of the IC EGM signals is received representing an entire cycle length for a single heartbeat. A pattern of interest (POI) is selected to include a portion of WOI corresponding to an arrhythmia activation. A template POI is generated representative of the arrhythmia activation. Subsequent electrical activity is received, weights are applied and the subsequent electrical activity is compared with the template POI. A correlation score is generated and compared with a threshold correlation score.