Abstract: A compression algorithm based on empirical mode decomposition(EMD)was described in order to investigate the performance of EMD in biomedical signals， and especially in the case of electrocardiogram(ECG). The proposed algorithm was 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 was applied， and some important parameters were obtained， such as 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. Experimental results indicated that the proposed algorithm has a better compress ratio and fidelity， which proved the feasibility of the proposed algorithm.

Key words: EMD(empirical mode decomposition), ECG(electrocardiogram), compression algorithm, MITBIH arrhythmia database, wavelet decomposition