ECG Signal Compression by Predictive Coding and Set Partitioning in Hierarchical Trees (SPIHT)

In this paper we present a method for multi-lead ECG signal compression using Predictive Coding combined with Set Partitioning In Hierarchical Trees (SPllIT). We utilize linear prediction between the beats to exploit the high correlation among those beats. This method can optimize the redundancy between adjacent samples and adjacent beats. Predictive coding is the next step after beat reordering step. The purpose of using predictive coding is to minimize amplitude variance of 2D ECG array so the compression error can be minimize. The experiments from selected records from MIT-UllI arrhythmia database shows that the proposed method is more efficient for ECG signal compression compared with original SPllIT and relatively have lower distortion with the same compression ratios compared to the other wavelet transformation techniques.