Wavelet transform and Huffman coding based electrocardiogram compression algorithm: Application to telecardiology

We present in this work an algorithm for electrocardiogram (ECG) signal compression aimed to its transmission via telecommunication channel. Basically, the proposed ECG compression algorithm is articulated on the use of wavelet transform, leading to low/high frequency components separation, high ord...

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Bibliographic Details
Main Authors: Chouakri, S A, Djaafri, O, Taleb-Ahmed, A
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Anomalies
Arrhythmia
Channels
Coding
Compressing
Compression ratio
Compression tests
Decoding
Discrete Wavelet Transform
Electrocardiography
Huffman codes
Inverse
Kurtosis
Mathematical models
Physics
Samples
Signal quality
Statistical methods
Visual perception
Visual signals
Wavelet transforms
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Summary:We present in this work an algorithm for electrocardiogram (ECG) signal compression aimed to its transmission via telecommunication channel. Basically, the proposed ECG compression algorithm is articulated on the use of wavelet transform, leading to low/high frequency components separation, high order statistics based thresholding, using level adjusted kurtosis value, to denoise the ECG signal, and next a linear predictive coding filter is applied to the wavelet coefficients producing a lower variance signal. This latter one will be coded using the Huffman encoding yielding an optimal coding length in terms of average value of bits per sample. At the receiver end point, with the assumption of an ideal communication channel, the inverse processes are carried out namely the Huffman decoding, inverse linear predictive coding filter and inverse discrete wavelet transform leading to the estimated version of the ECG signal. The proposed ECG compression algorithm is tested upon a set of ECG records extracted from the MIT-BIH Arrhythmia Data Base including different cardiac anomalies as well as the normal ECG signal. The obtained results are evaluated in terms of compression ratio and mean square error which are, respectively, around 1:8 and 7%. Besides the numerical evaluation, the visual perception demonstrates the high quality of ECG signal restitution where the different ECG waves are recovered correctly.
ISSN:1742-6596
1742-6588
1742-6596
DOI:10.1088/1742-6596/454/1/012086