3D Cardiac Mapping Beat Selection With Dynamic Quality Filtering
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Solution Overview
Problem
Current systems for constructing 3D anatomical maps of heart chambers collect and integrate the first available beat, regardless of quality, leading to redundant data and lack of dynamic filtering, resulting in incomplete and inaccurate mappings.
Innovation Solution
A processor-based algorithm applies multiple dynamic filters to select optimal beats for integration into a 3D mapping system, ensuring only high-quality beats are included, while allowing for dynamic updates and removal of inferior beats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the first available beat is collected and integrated into the mapping, then data acquisition is simplified and processing speed is improved, but mapping accuracy deteriorates due to inclusion of poor quality beats and redundant data
Solution Approach 1:
The system performs preliminary quality assessment of beats before integrating them into the mapping. Multiple beats are pre-collected and evaluated against quality criteria (signal amplitude, morphology consistency, noise levels) to identify optimal beats for inclusion, ensuring high mapping accuracy while maintaining efficient processing through automated pre-screening
Solution Approach 2:
The system implements feedback mechanisms where previously integrated beats serve as reference standards for evaluating subsequent beats. The quality assessment continuously adapts by comparing new beats against established references, dynamically adjusting selection criteria to maintain optimal mapping accuracy while filtering out redundant or poor quality data
2Measurement precision
If multiple beats are collected and dynamically filtered to select optimal beats, then mapping accuracy is improved, but system complexity increases due to multiple filtering criteria and dynamic update mechanisms
Solution Approach 1:
The quality assessment system is segmented into multiple independent filtering modules, each evaluating specific beat characteristics (signal amplitude, morphology, noise levels, temporal consistency). This modular architecture improves mapping accuracy through comprehensive multi-criteria evaluation while managing system complexity by organizing filters as discrete, reusable components with clear interfaces
Solution Approach 2:
The system dynamically adjusts filtering parameters and selection criteria based on the specific characteristics of collected beats and the current state of the mapping. Quality thresholds, weighting factors, and acceptance criteria are adaptively modified to optimize mapping accuracy for different anatomical regions and signal conditions, managing complexity through parameter adaptation rather than structural complexity
3Quantity of substance
If poor quality beats are included in the mapping, then data completeness is improved, but mapping reliability deteriorates due to noise and unrepresentative data
Solution Approach 1:
The system extracts and removes poor quality beats from the dataset before integration into the mapping. Quality assessment criteria identify and exclude beats with excessive noise, abnormal morphology, or unrepresentative characteristics, ensuring that only reliable beats contribute to the final mapping while maintaining sufficient data coverage through selective extraction of high-quality signals
Data Source
AI summary
Systems and methods for optimal selection of beats for a 3D mapping are disclosed. A method in accordance with the present disclosure may be performed on a processor and may comprise receiving a plurality of beats from a catheter. The catheter may be located at a target mapping site, such as a chamber of the heart. A plurality of dynamic filters may be applied to the plurality of collected beats. The optimal beats may be determined and integrated as a beat in the 3D mapping system. This method enables the selection of more beats for a more comprehensive 3D mapping, as well as the selection of more quality beats that are representative of the target anatomy.