In this paper, a new wavelet-based hybrid electrocardiogram (ECG) data compression technique is proposed. Firstly, in order to fully utilize the two correlations of heartbeat signals, 1-D ECG data are segmented and aligned to a 2-D data arrays. Secondly, 2-D wavelet transform is applied to the constructed 2-D data array. Thirdly, the set partitioning hierarchical trees (SPIHT) method and the vector quantization (VQ) method are modified, according to the individual characteristic of different coefficient subband and the similarity between the subbands. Finally, a hybrid compression method of the modified SPIHT and VQ is employed to the wavelet coefficients. Records selected from the MIT/BIH arrhythmia database are tested. The experimental results show that the proposed method is suitable for various morphologies of ECG data, and that it achieves high compression ratio with the characteristic features well preserved.
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