Modeling Electrocardogram (ECG) Waveforms Using Group Theory and Symmetry Elements

Abstract

We present a what we believe to be a novel approach for generating electrocardiogram (ECG) waveforms using group theory and the algebraic structure of abstract symmetry elements from point groups up to order 10. Unlike traditional ECG modeling, which relies on physiological simulation or differential equations with predefined boundary conditions, our approach uses algebraic structures without predefined boundary conditions. This method allows us to explore the underlying algebraic symmetry of ECG signals, offering a perspective on biological signal representation. The flexibility and abstract nature of this framework opens potential applications for interdisciplinary research in mathematical biology, signal processing, and computational biology.