Solid Angle Charge Modeling for Electrophysiology Simulation

The patent segments the calculation domain into discrete calculation cells with simplified geometries (e.g., cubic cells). By dividing the complex electrophysiological system into many small, simple cells, the method avoids the need to directly handle complex interfaces and singularities while maintaining calculation accuracy through the collective representation of charge distributions across all cells.

The patent introduces an intermediary computational framework that uses solid angle calculations as a mediator between the physical charge distributions and the computational model. Instead of directly calculating potentials at singular interfaces, the method uses solid angles subtended by calculation cell faces at charge locations as an intermediary quantity that naturally handles interface problems without singularities.

Complex geometries are represented by segmenting them into assemblies of simple calculation cells (e.g., cubic cells arranged in grids). This segmentation allows accurate representation of complex shapes through the collective arrangement of simple elements, while each individual cell maintains simple geometry that is computationally efficient to handle.

The patent uses simplified cubic calculation cells as computational copies that represent more complex physical structures. Instead of directly modeling complex geometries with their inherent computational difficulties, the method uses arrays of simple cubic cells that copy the essential geometric and electrical properties needed for accurate electrophysiological modeling.

The patent extracts and eliminates unnecessary calculation cells from the model. By analyzing which cells actually contribute to the charge distribution and potential calculations, the method removes cells that would not affect the results, thereby reducing the total number of cells needed while maintaining modeling accuracy.

The patent changes the computational parameters by using solid angle calculations instead of traditional potential-based methods. This parameter change allows for more efficient computation where fewer cells are needed to achieve the same accuracy, as the solid angle method naturally converges faster and requires less computational effort per cell.