A new hybrid two-stage electrocardiogram (ECG) signals compression method based on the Modified Discrete Cosine Transform (MDCT) and Discrete Wavelet Transform (DWT) is proposed. The ECG signal is partitioned in blocks and the MDCT is applied to each block to decorrelate the spectral information. Then, the DWT is applied to each MDCT block of the signal. Removing spectral redundancy is achieved by compressing the subordinate components more than the dominant components. The resulting wavelet coefficients are then threshold and compressed using energy packing and binary-significant map coding technique for storage space saving. Experimenting on an ECG records from the MIT-BIH database is performed with various combinations of the MDCT and wavelet filters at different transformation levels, and quantization intervals. The decompressed signals are evaluated using percentage root mean square error (PRD) and zero-mean root mean square error (PRD1) measures. The results showed that the proposed method provides low bit-rate and high quality of the reconstructed signal. It offers a compressed ratio (CR) in between 12.6 and 21.5 average PRD of 5.89%, which would be suitable for most monitoring and diagnoses applications. Experiments with ECG signals used in results from the literature showed that the proposed method compares favorably with various state-of-the-art ECG compressors.