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Electrocardiogram coder using wavelet transform of average beat and residuals
Published in CRC Press/Balkema
Pages: 65 - 70
Electrocardiography (ECG) is the most popular noninvasive technique for primary stage investigation on cardiac functions. ECG data compression finds wide application in patient monitoring and heart rhythm analysis. In this paper, we present an efficient compression method for single lead Electrocardiogram (ECG) signals based on the Discrete Wavelet Transform (DWT). Since the ECG consecutive beats exhibit sufficient redundant information, DWT was applied on an average beat estimate, computed over 10 beats and the residuals of the corresponding original beats. Selections of the significant coefficients from the average beat as well as the residuals were based on Energy Packing Efficiency (EPE). Finally, the selected coefficients for the average beat were quantized at 8-bit, and the residuals with 5-bit and compressed by a delta coder. The significance maps were encoded by binary coder and run length encoder. The algorithm was validated with one min. mitdb data under Physionet at 360 Hz sampling to obtain an average Compression Ratio (CR) of 8.65, PRD of 2.32, PRDN of 4.30. The reconstructed signals were clinically validated by cardiologists. © 2017 Taylor & Francis Group.
About the journal
JournalComputational Science and Engineering - Proceedings of the International Conference on Computational Science and Engineering, ICCSE2016
PublisherCRC Press/Balkema
Open AccessNo