2D Scatter Plot for EGM Characteristic Metrics
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Solution Overview
Problem
Conventional cardiac mapping systems face challenges in efficiently processing and interpreting large volumes of intracardiac electrograms (EGMs), leading to increased examination time and cost, and often result in misleading maps due to electrical artifacts or inappropriate feature selection.
Innovation Solution
A method and system for processing cardiac information by receiving activation waveforms and window parameters, determining confidence values and correlations for each signal section, and generating representations of local cycle lengths, duty cycles, and confidence values, which can be overlaid on cardiac maps for improved diagnostic assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional 3D mapping techniques are used to capture electrograms at multiple points, then comprehensive electrical activity data is obtained, but the examination time and cost increase significantly
Solution Approach 1:
The patent extracts and displays only the most relevant EGM characteristics (such as dominant frequency, activation time, or voltage amplitude) in a simplified 2D scatter plot format, rather than presenting all captured electrogram data. This extraction of essential features maintains diagnostic reliability while dramatically reducing the time required to review mapping data.
Solution Approach 2:
Instead of requiring clinicians to manually inspect thousands of raw EGM waveforms to assess electrical activity, the system inverts the approach by automatically analyzing the EGMs and presenting key characteristics in an intuitive visual format. This inversion transforms a time-consuming manual review process into an automated analysis that delivers comprehensive data interpretation rapidly.
2Measurement precision
If manual inspection of captured electrograms is performed for diagnostic assessment, then detailed EGM categorization is achieved, but examination time and cost increase
Solution Approach 1:
The system performs automatic EGM analysis and categorization without requiring manual clinician inspection. The processing unit automatically extracts characteristics, categorizes electrograms, and generates the 2D scatter plot representation, enabling the system to serve its own diagnostic function independently while maintaining high measurement precision.
Solution Approach 2:
The patent transforms raw EGM waveforms into standardized parameter representations (such as dominant frequency, amplitude, or timing parameters) that can be automatically analyzed and categorized. This parameter transformation enables precise automated categorization without manual inspection, converting complex waveforms into quantifiable metrics that maintain diagnostic accuracy.
3Productivity
If scalar values are extracted from each EGM to construct voltage or activation maps, then the need to inspect captured EGMs is reduced, but complex and useful information in the EGMs is condensed or lost
Solution Approach 1:
The patent displays multiple EGM characteristics simultaneously in a 2D scatter plot format, where each point represents a measurement location and its position encodes different parameters (such as dominant frequency on one axis and activation time on another). This dimensional representation preserves complex multi-parameter information that would be lost in traditional scalar maps, allowing comprehensive information display without requiring manual EGM inspection.
4Reliability
If conventional mapping systems generate detailed cardiac maps, then overall activity patterns are depicted, but the maps may be misleading due to electrical artifacts or inappropriate feature selection
Solution Approach 1:
The 2D scatter plot displays local EGM characteristics at each measurement location without imposing a global map interpretation that could be influenced by artifacts. Each point in the scatter plot represents independent local measurements, allowing clinicians to assess activity patterns while maintaining the ability to identify and exclude artifact-contaminated individual measurements, thereby preserving map accuracy.
Data Source
AI summary
At least some embodiments of the present disclosure is directed to a system for processing cardiac information. The system comprises a processing unit configured to: receive an activation waveform comprising a set of activation waveform data of a plurality of signal sections collected at a plurality of locations; receive a range of window size. For each of the plurality of signal sections, the processing unit is further configured to: determine a set of confidence values, by iterating through a plurality of window sizes in the range of window size. For each of the plurality of signal sections, the processing unit is further configured to determine one of a plurality of local cycle lengths for the each of the plurality of signal sections based on the selected window size. And generate a representation of the plurality of local cycle lengths.