ECG Signal Compression Using A Proposed Inverse Technique

Abstract

In this paper, a new electrocardiogram (ECG) data compression algorithm is proposed. The algorithm mainly performs a preprocessing operation to convert the 1-D ECG into 2-D array. This preprocessing operation includesdetecting the QRS complex, and then alignment and period sorting are used to convert the ECG signal into a matrix. Normalization is performed to scale the values of the matrix and make a gray scale image due to the 2-D ECG. Then, the algorithm applies decimation for ECG compression. The reconstruction of the original ECG signals can be performed using inverse interpolation techniques such as the linear minimum mean square error (LMMSE), the maximum entropy, and the regularization theory.