Detail publikace

Wavelet-based Compression of ECG Signals

Originální název

Wavelet-based Compression of ECG Signals

Anglický název

Wavelet-based Compression of ECG Signals

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

BibTex


@inproceedings{BUT11301,
  author="Ivo {Provazník} and Jiří {Kozumplík}",
  title="Wavelet-based Compression of ECG Signals",
  annote="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.",
  address="IEEE",
  booktitle="Proceedings of the 18th Annual International Conference of the IEEE EMBS",
  chapter="11301",
  institution="IEEE",
  year="1996",
  month="january",
  pages="1210",
  publisher="IEEE",
  type="conference paper"
}