ECG Signal Compression using Discrete Sinc Interpolation

This paper presents a novel ECG data compression algorithm based on discrete sinc interpolation (DSI) technique. The compression and decompression of ECG data is achieved using discrete sinc interpolation (DSI), which is realized by an efficient discrete fourier transform (DFT). The proposed algorithm is evaluated using MIT-BIH Arrhythmia Database (sampled at 360Hz with 11 bits resolution). The performance of the proposed DSI based algorithm is compared with the performance of the widely used ECG data compression algorithms such as AZTEC, FAN, Hilton and Djohan algorithms. It is observed that higher compression ratio (CR) is achieved with a relatively lower Percentage RMS Difference (PRD) by DSI algorithm. The diagnostic distortion is measured in terms of average absolute error (AAE), which is lower in case of the DSI algorithm compared to the AZTEC and FAN algorithm.