Detail publikace

Compression of ECG signals using SPIHT – alternatives to wavelet transform

Originální název

Compression of ECG signals using SPIHT – alternatives to wavelet transform

Anglický název

Compression of ECG signals using SPIHT – alternatives to wavelet transform

Jazyk

en

Originální abstrakt

One of the most effective methods for ECG signal compression is a combination of Wavelet Transform (WT) and Set Partitioning in Hierarchical Trees (SPIHT). WT transforms the signal into coefficients, which are arranged in a pyramidal structure. SPIHT is applied on these coefficients to compress the signal and create a bit stream. The article introduces alternative methods to WT – Pyramidal Median Transform (PMT) and Empirical Mode Decomposition (EMD). The combination of these methods with SPIHT has not been published yet. After SPIHT is applied, the output stream is further compressed by lossless methods (Burrows-Wheeler Transform, Move to Front, Run Length Encoding, and Huffman Encoding). WT, PMT and EMD in combination with SPIHT were tested and compared in terms of efficiency and quality of compression. Neither PMT nor EMD did not show to be as effective as WT.

Anglický abstrakt

One of the most effective methods for ECG signal compression is a combination of Wavelet Transform (WT) and Set Partitioning in Hierarchical Trees (SPIHT). WT transforms the signal into coefficients, which are arranged in a pyramidal structure. SPIHT is applied on these coefficients to compress the signal and create a bit stream. The article introduces alternative methods to WT – Pyramidal Median Transform (PMT) and Empirical Mode Decomposition (EMD). The combination of these methods with SPIHT has not been published yet. After SPIHT is applied, the output stream is further compressed by lossless methods (Burrows-Wheeler Transform, Move to Front, Run Length Encoding, and Huffman Encoding). WT, PMT and EMD in combination with SPIHT were tested and compared in terms of efficiency and quality of compression. Neither PMT nor EMD did not show to be as effective as WT.

BibTex


@inproceedings{BUT127556,
  author="Andrea {Němcová} and Martin {Vítek}",
  title="Compression of ECG signals using SPIHT – alternatives to wavelet transform",
  annote="One of the most effective methods for ECG signal compression is a combination of Wavelet Transform (WT) and Set Partitioning in Hierarchical Trees (SPIHT). WT transforms the signal into coefficients, which are arranged in a pyramidal structure. SPIHT is applied on these coefficients to compress the signal and create a bit stream. The article introduces alternative methods to WT – Pyramidal Median Transform (PMT) and Empirical Mode Decomposition (EMD). The combination of these methods with SPIHT has not been published yet. After SPIHT is applied, the output stream is further compressed by lossless methods (Burrows-Wheeler Transform, Move to Front, Run Length Encoding, and Huffman Encoding). WT, PMT and EMD in combination with SPIHT were tested and compared in terms of efficiency and quality of compression. Neither PMT nor EMD did not show to be as effective as WT.",
  address="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  booktitle="Sborník příspěvků studentské konference Blansko 2016",
  chapter="127556",
  howpublished="online",
  institution="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  year="2016",
  month="august",
  pages="67--70",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  type="conference paper"
}