3D Grid Cardiac Mapping Reduces Computational Burden
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Solution Overview
Problem
Conventional cardiac mapping systems face inefficiencies in data processing and computational burdens due to the need to discard unnecessary data points, leading to waste and inefficiencies, especially when capturing thousands of data points during procedures.
Innovation Solution
The use of statistical techniques to determine mapping values on a three-dimensional anatomy mesh, aggregating events and applying methods to mitigate outliers, allowing for the capture of a large number of data points while improving computational efficiencies by maintaining statistics at discrete nodes of a Cartesian grid and projecting them onto the anatomy surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional systems test each EGM against adjacent EGMs to reject outliers, then mapping accuracy is improved, but computational burden increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-sorting EGMs based on their spatial locations before processing. This pre-arrangement allows the system to efficiently identify adjacent EGMs without complex real-time calculations, thereby maintaining mapping accuracy while reducing computational burden during the actual outlier detection process
Solution Approach 2:
The patent segments the continuous spatial data into discrete adjacent pairs of EGMs based on sorted locations. By dividing the processing into manageable segments (adjacent pairs), the system can apply simple comparison operations to each pair rather than performing complex global calculations, thus reducing overall computational complexity while maintaining accuracy
2Loss of information
If all captured data points are processed, then mapping completeness is improved, but processing time increases
Solution Approach 1:
The patent extracts and processes only the essential features from each EGM (spatial location and electrical signal characteristics) while discarding redundant information. By taking out only the necessary data elements needed for mapping, the system maintains mapping completeness while significantly reducing the time required to process the full dataset
Solution Approach 2:
The patent applies partial action by processing a representative subset of EGMs through the full analysis pipeline while using spatial sorting to efficiently handle the remaining points. This approach achieves sufficient mapping completeness without the excessive time cost of processing every single data point with full computational rigor
3Productivity
If conventional methods discard points not on endocardium surface, then processing efficiency is improved, but data waste increases
Solution Approach 1:
The patent changes the parameter used for identifying valid mapping points from strict geometric surface membership to a more flexible criterion based on spatial proximity and statistical consistency. This parameter change allows the system to maintain high processing efficiency while utilizing a larger portion of captured data points, thereby reducing data waste
Data Source
AI summary
A system for facilitating display of cardiac mapping information includes a catheter having one or more electrodes that measure electrical signals in the heart, and a processing unit. The processing unit receives the electrical signals from the catheter and receives an indication of a measurement location corresponding to each signal. The processing unit extracts a set of features from the signals, where each feature includes a value corresponding to a metric. A three-dimensional grid is constructed, wherein each node of the grid corresponds to a physical point in three-dimensional space. The system identifies a set of electrical signals in a neighborhood associated with a node; determines, based on the set of features extracted from the set of electrical signals, a node value; associates the node value with the node; and facilitates presentation of a map corresponding to a cardiac surface based on the node value.