An ECG compression approach based on a segment dictionary and Bezier approximations



This paper proposes a methodology for ECG data compres-sion based on signal segmentation in R-R segments. An ECG can be seen as a quasi-periodic signal, where it is pos-sible to find many similarities between heart beats. These similarities are explored by the proposed compression scheme through the use of a segment dictionary combined with an efficient form of progressive error codification. The dictionary is able to incorporate new patterns, in order to assure the algorithm adapts to changes in signal morphol-ogy.
Experimental results reveal that high compression ra-tios are possible for highly regular signals, with irregular signals still achieving acceptable results.


ECG Compression


15th European Signal Processing Conference (EUSIPCO-2007), September 2007

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Year 2010 : 2 citations

 • Daniel TCHIOTSOP*, Silviu IONITA, ECG Data Communication Using Chebyshev Polynomial Compression Methods, University of Pitesti, Romania, 2010.

 • Ridha Iskandar, I Wayan Simri W, Compression of ECG Signal Using Neural Network Predictor and Huffman Coding, Gunadarma University, 2010.