ECG Signal Compression for Diverse Transforms

Abstract

Biological signal compression and especially ECG has an important role in the diagnosis, prognosis and survival analysis of heart diseases. Various techniques have been proposed over the years addressing the signal compression. Compression of digital electrocardiogram (ECG) signals is desirable for three reasons- economic use of storage data, reduction of the data transmission rate and transmission bandwidth conversation. ECG signal. In this paper a comparative study of Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT), Discrete Cosine compression is used for telemedicine field and re Transform (DCT) and Wavelet Transform (WT) transform based approach is carried out. Different ECG signals are tested from MIT-BIH arrhythmia database using MATLAB software. The experimental results are obtained for Percent Root Mean Square Difference (PRD), Signal to Noise ratio (SNR) and Compression ratio (CR). The result of ECG signal compression shows better compression performance in DWT compared to DFT, FFT and DCT.

Keywords: Electrocardiogram (ECG), Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT), Wavelet Transform (WT).