3D Cardiac Surface Mapping for Irregular Electrophysiological Activity Detection
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Solution Overview
Problem
Existing electrocardiographic mapping technologies struggle to accurately detect and visualize regions of irregular electrophysiological activity, such as slow conduction and short duration events, which are crucial for diagnosing and treating cardiac arrhythmias.
Innovation Solution
A system and method that analyzes electrophysiological signals across a three-dimensional cardiac surface to detect wave fronts, determine conduction velocity, identify slow conduction regions, and quantify short duration events, generating graphical maps to visualize these irregularities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional electrocardiographic mapping is used, then basic electrical signals can be recorded, but accurate detection and visualization of irregular electrophysiological activity regions cannot be achieved
Solution Approach 1:
The patent divides the cardiac surface into multiple discrete nodes arranged in a three-dimensional geometric configuration. Each node independently records electrical signals, allowing localized detection of irregularities. This segmentation enables precise spatial mapping of slow conduction and short duration events while maintaining manageable system complexity through modular node-based architecture.
Solution Approach 2:
The patent transitions from traditional two-dimensional electrocardiographic mapping to three-dimensional geometric surface mapping. By adding the spatial dimension and configuring nodes in 3D space, the system achieves superior visualization and localization of irregular electrophysiological regions. This dimensional enhancement allows accurate representation of complex cardiac structures and propagation patterns without proportionally increasing operational complexity.
2Loss of information
If comprehensive spatial mapping is performed across the entire cardiac surface, then detailed visualization of irregular regions can be achieved, but data processing time and computational resources increase
Solution Approach 1:
The patent pre-configures the three-dimensional geometric surface with distributed nodes before data acquisition. This preliminary setup establishes the complete spatial mapping framework in advance, allowing simultaneous multi-point recording across the entire cardiac surface. By having the detection network ready beforehand, the system captures comprehensive electrophysiological data without sequential measurement delays, reducing overall processing time while maintaining complete spatial coverage.
Solution Approach 2:
The patent implements continuous simultaneous recording at all distributed nodes across the three-dimensional cardiac surface. Multiple electrical signals are acquired in parallel throughout the measurement period, ensuring uninterrupted detection of wave fronts and irregularities. This continuous parallel operation maximizes data completeness while minimizing total measurement and processing time compared to sequential scanning methods.
3Productivity
If threshold-based detection is used for conduction velocity, then slow conduction regions can be identified, but precision in locating borderline cases deteriorates
Solution Approach 1:
The patent compares conduction velocity measurements at each node against predetermined thresholds to identify slow conduction regions. The system provides feedback by mapping which nodes exceed the threshold, allowing rapid identification of irregular regions. This feedback mechanism maintains both productivity through quick threshold-based screening and precision by enabling further analysis of borderline cases through the detailed three-dimensional node data already collected.
Data Source
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AI summary
For example, one or more non-transitory computer-readable media includes executable instructions to perform a method. The method includes defining a plurality of spatial regions distributed across a geometric surface. At least one wave front that propagates across the geometric surface is detected based on electrical data representing electrophysiological signals for each of a plurality of nodes distributed on the geometric surface over at least one time interval. An indication of conduction velocity of the wave front is determined for at least one spatial region of the plurality of spatial regions during the time interval based on a duration that the wave front resides within the at least one spatial region. Slow conduction activity is identified for the at least one spatial region based on comparing the indication of conduction velocity relative to a threshold. Conduction data is stored in memory to represent each slow conduction event.