Efficient electrocardiogram signal compression algorithm using dual encoding technique

Khalida Shaaban Rijab, Mohammed Abdul Redha Hussien

Abstract


In medical practices, the storage space of electrocardiogram (ECG) records is a major concern. These records can contain hours of recording, necessitating a large amount of storage space. This problem is commonly addressed by compressing the ECG signal. The proposed work deal with the ECG signal compression method for ECG signals using discrete wavelet transform (DWT). The DWT appeared as powerful tools to compact signals and shows a signal in another time-frequency representation. It is very appropriate in the elimination & removal of redundancy. The ECG signals are decomposed using DWT. After that, the coefficients that result from DWT are threshold depending on the energy packing efficiency (EPE) of the signal. The compression is achieved by the quantization and dual encoding techniques (run-length encoding & Huffman encoding). The dual encoding technique compresses data significantly. The result of the proposed method shows better performance with compression ratios and good quality reconstructed signals. For example, the compression ratio (CR)=20.6, 10.7 and 11.1 with percent root mean square difference (PRD)=1%, 0.9% and 1% for using different DWT (Haar, db2 and FK4) Respectively.

Keywords


Compression; Discrete wavelet transform; DWT threshold; Electrocardiogram; Huffman encoding; Quantization; Run length encoding

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DOI: http://doi.org/10.11591/ijeecs.v25.i3.pp1529-1538

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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