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In order to solve the problem of huge data in remote holter recording, ensure the accuracy of ECG data reconstruction and reduce compression power consumption, an algorithm that combines compressive sensing compression with shift differential bit compression is proposed. Shift difference bit compression is a lossless compression algorithm, which improves the compression ratio without affecting the reconstruction accuracy. Block sparse Bayesian model is used to reconstruct ECG signals, the reconstruction accuracy meets the needs of physicians for diagnosis. Experiments show that the maximum compression ratio obtained by this method is 11, the minimum value is 4.81, and the computational complexity of the compression end is O(N). This satisfies the requirements of remote dynamic ECG recorders.