Electrophysiology Map Generation Using Signal Morphology Filtering
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Solution Overview
Problem
Current electrophysiology mapping systems face challenges in generating high-quality, dense, and rapid maps, especially in cardiac diagnostic and therapeutic procedures, due to the inclusion of unwanted data points that can compromise map accuracy.
Innovation Solution
A method and system for generating electrophysiology maps by defining template and unwanted electrophysiological signals, comparing signal morphologies, and removing data points with unwanted morphologies, using techniques such as morphology matching scores and Pearson Correlation Coefficients to ensure only relevant data points are included in the map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If inclusion criteria are used to automatically add electrophysiology data points, then map generation speed increases, but unwanted data points may be included reducing map accuracy
Solution Approach 1:
The system performs preliminary classification of data points by comparing signal morphology against template and unwanted morphologies before inclusion in the map. This pre-screening process ensures that only data points matching the desired template morphology are added, while those matching unwanted morphology are excluded, thus maintaining high accuracy without compromising generation speed.
Solution Approach 2:
The system uses feedback from morphology comparison results to control data point inclusion. By continuously comparing each data point's signal morphology against defined templates and unwanted patterns, the system provides real-time feedback that determines whether to include or exclude each point, ensuring high map accuracy while maintaining automated rapid generation.
2Measurement precision
If manual review of electrophysiology data points is performed, then map accuracy improves, but map generation time increases
Solution Approach 1:
The system performs self-service by automatically classifying and filtering electrophysiology data points through morphology comparison algorithms. The computer system independently compares each data point against template and unwanted morphologies without requiring manual review, thereby achieving high map accuracy while eliminating the time loss associated with manual inspection.
Solution Approach 2:
The system replaces the mechanical process of manual data point review with an automated computational system. The morphology comparison algorithm substitutes human manual inspection, providing equivalent or superior accuracy while dramatically reducing the time required for map generation.
3Manufacturing precision
If multiple inclusion criteria are applied to filter data points, then map quality improves, but the complexity of the mapping system increases
Solution Approach 1:
The system improves map quality by changing the parameter used for data point classification from simple inclusion/exclusion criteria to signal morphology parameters. By comparing morphological characteristics against template and unwanted patterns, the system achieves high map quality through a focused set of morphology-based criteria rather than multiple complex inclusion rules.
Solution Approach 2:
The system applies local quality by focusing classification efforts on the specific morphological characteristics of electrophysiology signals. Rather than applying multiple broad inclusion criteria across all data points, the system concentrates on comparing local signal morphology features against defined templates, achieving high map quality with a targeted approach that reduces overall system complexity.
Data Source
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AI summary
A method of generating an electrophysiology map of a portion of a patient's anatomy includes receiving a plurality of electrophysiology data points, each including an associated electrophysiological signal. A template electrophysiology data point and one or more unwanted electrophysiology data points are selected from the plurality of electrophysiology data points. The electrophysiological signal associated with the template electrophysiology data point is defined as a template electrophysiological signal, while the electrophysiological signal(s) associated with the unwanted electrophysiology data point(s) is/are defined as unwanted electrophysiological signal(s). For any given electrophysiology data point, if the morphology of its associated electrophysiological signal is more similar to the morphology of an unwanted electrophysiological signal than to the morphology of the template electrophysiological signal, the given electrophysiology data point is rejected/excluded from an electrophysiology map.