Meshless ECGI System Using Method of Fundamental Solutions
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Solution Overview
Problem
Current noninvasive electrocardiographic imaging (ECGI) techniques, such as BEM ECGI, are time-consuming, require significant memory resources, and are limited by the need for complex mesh optimization, making them less applicable in clinical settings due to high skill requirements and difficulties in accommodating complex heart geometries.
Innovation Solution
The development of a meshless ECGI system using the Method of Fundamental Solution (MFS) that translates body surface electrical potentials to the epicardial cardiac surface without requiring surface meshes, reducing computation time and memory usage while maintaining accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Boundary Element Method (BEM) is used for noninvasive ECGI, then electrocardiographic imaging can be performed, but the computation time is excessive and memory resources are heavily consumed
Solution Approach 1:
The patent extracts the essential computational function from the mesh-based BEM approach by removing the surface meshing step entirely. The Method of Fundamental Solutions (MFS) uses only boundary points (source points and field points) without requiring the construction of triangular surface elements, thereby eliminating the time-consuming mesh generation and optimization processes while preserving the ability to reconstruct epicardial potentials accurately.
Solution Approach 2:
The patent changes the fundamental computational parameters by transitioning from a mesh-based discretization (with elements and nodes) to a point-based fundamental solution approach. This parameter change eliminates the need for mesh quality optimization and reduces the computational complexity from O(N²) to O(N), where N is the number of boundary points, thereby dramatically reducing computation time while maintaining accuracy.
2Measurement precision
If manual mesh optimization is performed to maintain accuracy in reconstructing epicardial cardiac surface potentials, then reconstruction accuracy is improved, but the process becomes even more time-consuming and requires high skill level
Solution Approach 1:
The MFS approach is self-service in that it automatically achieves accurate reconstructions without requiring manual mesh optimization. The method inherently handles complex geometries through its point-based fundamental solution formulation, eliminating the need for skilled operators to perform time-consuming mesh quality assessments and adjustments. The system serves itself by directly computing potentials from boundary points without intermediate mesh processing steps.
3Measurement precision
If BEM surface meshes are used, then electrocardiographic imaging can be performed, but the method exhibits difficulty in accommodating complex heart geometries (particularly concave geometries)
Solution Approach 1:
The patent inverts the traditional approach by not trying to force the geometry into a mesh structure, but rather by directly applying fundamental solutions at boundary points that naturally conform to any geometry. This inversion of the problem-solving approach allows the method to easily accommodate complex and concave heart geometries without the mesh distortion and accuracy loss that plagues traditional BEM approaches.
4Measurement precision
If 3D surface meshing is performed to compute the coefficient matrix for translating body surface potentials to epicardial potentials, then the imaging can be performed, but large memory resources are required
Solution Approach 1:
The patent extracts the essential computational function from the mesh-based approach by removing the surface meshing step entirely. The Method of Fundamental Solutions (MFS) uses only boundary points (source points and field points) without requiring the construction of triangular surface elements, thereby eliminating the time-consuming mesh generation and optimization processes while preserving the ability to reconstruct epicardial potentials accurately.
Data Source
Figure 1~2(b)
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AI summary
Noninvasive systems and methods are provided for determining electrical activity for a heart of a living being. A processor is configured to meshlessly compute data that represents heart electrical activity from a set of noninvasively measured body surface electrical potentials. This is accomplished using data that describes a geometric relationship between a plurality of locations corresponding to where the body surface electrical potentials were measured and the heart.