Applications of rank-reduction to ECG analysis

The authors demonstrate application of SVD-based subspace techniques to electrocardiography. SVD, a high resolution spectrum estimation tool, is used to decompose the ECG data matrix into orthogonal subspaces. Due to the energy-preserving orthogonal transformations in the SVD, these subspaces correspond to the signal and noise components contained in the ECG data. Projection of the data onto the desired subspace eliminates the noise and the unwanted signal components.