ECG signal decomposition using Fourier analysis

This paper explores the Fourier decomposition method to approximate the decom-position of electrocardiogram (ECG) signals into their component waveforms, such as the QRS-complex and T-wave. We compute expansion coefficients using the & ell;(1) Fourier transform and the traditional & ell;(2) Fourier transform. Numerical examples are pre-sented, and the analysis focuses on ECG signals as a real-world application, comparing the performance of the & ell;(1) and & ell;(2) Fourier transforms. Our results demonstrate that the & ell;(1) Fourier transform significantly enhances the separation of ECG signal components, such as the QRS-complex and T-wave. This improvement is attributed to a notable reduction in the Gibbs phenomenon introduced by the Fourier-series expansion when using the & ell;(1) Fourier transform, as opposed to the traditional & ell;(2) Fourier transform.