Capacitive coupling between the heart and the tissue and its mathematical representation in forward problem

This dataset is from our study that challenges the conventional interpretation of electrocardiogram (ECG) measurements, suggesting a paradigm shift in our understanding. Traditionally, ECGs are seen as reflections of the electric potential on the body's surface, but we propose an alternative hypothesis: ECGs may represent the gradient of the electric potential rather than the potential itself. To investigate this, we use computational methods based on the boundary element method (BEM) within the SCIRun numerical package. We formulate the forward problem, relating potential on the heart's surface to that on the body's surface, considering both Dirichlet-Neumann and Neumann-Neumann boundary conditions. While Dirichlet-Neumann is common in ECG modeling, we introduce a "mix" method approximating the Neumann-Neumann problem. Computational experiments show that this "mix" method offers superior numerical accuracy compared to the traditional approach. We explore capacitive coupling between the heart and surrounding tissue, finding it does not limit describing cardiac potentials within tissue bulk using volume conductor theory. This insight reshapes our understanding of ECGs, suggesting they may be more closely related to potential gradients than potentials themselves. This paradigm shift highlights the importance of investigating the inverse ECG modeling problem, where potential are subject to constraint. In conclusion, this research challenges conventional ECG interpretation, calling for further study into the inverse problem's implications for improving electrophysiological imaging accuracy. These advances could enhance the diagnostic impact of ECG-based approaches, deepening our understanding of cardiac electrophysiology.