Wavelet-based compression of ECG signals

Author

Provaznik, Ivo ; Kozumplik, Jiri

Author_Institution

Dept. of Biomed. Eng., Tech. Univ. Brno, Czech Republic

Volume

3

fYear

1996

fDate

31 Oct-3 Nov 1996

Firstpage

1210

Abstract

An example of application of the wavelet transform to electrocardiography is described in the paper. The transform is exploited as a first stage of an ECG signal compression algorithm. The signal is decomposed into particular time-frequency components. Some of the components are removed because of their low influence to signal shape due to nonstationary character of ECG. Resulted components are quantized, composed into one block and compressed by a classical entropic Huffman coder. The wavelet transform with the threshold detector, the quantizer, and the Huffman coder can compress data with average compression ratio CR=9.2 and percentual root mean square difference PRD=3.0%. The lossy compression algorithm was tested on CSE library of rest ECG signals

Keywords

data compression; electrocardiography; encoding; medical signal processing; time-frequency analysis; wavelet transforms; CSE library; ECG signal compression algorithm; classical entropic Huffman coder; compression ratio; electrodiagnostics; lossy compression algorithm; nonstationary character; percentual root mean square difference; quantizer; rest ECG signals; signal shape; threshold detector; time-frequency components; wavelet-based compression; Biomedical engineering; Compression algorithms; Computer science; Discrete wavelet transforms; Electrocardiography; Huffman coding; Signal processing algorithms; Time frequency analysis; Wavelet coefficients; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE

Conference_Location

Amsterdam

Print_ISBN

0-7803-3811-1

Type

conf

DOI

10.1109/IEMBS.1996.652777

Filename

652777