Abstract
A compression algorithm based on Empirical Mode Decomposition (EMD) is described in order to investigate the performance of EMD in biomedical signals, and especially in the case of electrocardiogram (ECG). The proposed algorithm is computationally simple to treat non-stationary and nonlinear data without pre- or post-processing. In order to evaluate the performance of the proposed compression algorithm, MIT-BIH arrhythmia database is applied, and the compress ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), root mean square (RMS), signal to noise ratio (SNR), and quality score (QS) values are obtained. When compared, good fidelity parameters are yielded with high CR as compared to wavelet transform (WT).
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