Abstract
The electrocardiogram (ECG) signal is the recording of the electrical activity of the human heart. The compression of the ECG signal is highly beneficial for the purpose of wireless transmission as well as storage. A new algorithm for ECG signal compression is proposed in this paper. The algorithm is based on the observation that the ECG signal in the steady state is very stable with highly correlated successive pulses. Thus, the algorithm performs differential encoding between each new pulse and a stored reference pulse. This idea is inspired by the video compression techniques where the inter-frame changes are very limited. Therefore, high signal compression ratio can be obtained. The performance of the introduced technique is evaluated and compared to the state-of-the-art techniques. The performance is characterized by the compression ratio (CR) and the percentage of root mean square difference (PRD). The algorithm achieved a CR of 105 with PRD below 1.3%. Moreover, the comparison with other existing ECG compression methods demonstrated the superiority of the proposed algorithm.
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Soliman, M., El-Rafei, A., El-Nozahi, M., Ragai, H. (2018). Adaptive Differential Pulse Coding for ECG Signal Compression. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_16
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DOI: https://doi.org/10.1007/978-3-319-68195-5_16
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