The effect of electrocardiogram signal compression using beat reordering and SPIHT on automatic sleep stage classification

Sani M. Isa, Ary Noviyanto, Wisnu Jatmiko, Aniati Murni Arymurthy

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

In this paper, we investigate the effect of electrocardiogram (ECG) compression to the automatic sleep stage classification based on ECG signal. An effective ECG signal compression method based on two-dimensional wavelet transform which employs set partitioning in hierarchical trees (SPIHT) and beat reordering technique used to compress the ECG signal from MIT-BIH polysomnographic database. This method utilizes the redundancy between adjacent samples and adjacent beats. Beat reordering rearranges beat order in 2D (2 dimension) ECG array based on the similarity between adjacent beats. The experimental results show that the proposed method yields relatively low distortion at high compression rate. The experimental results also show that the accuracy of sleep stage classification using reconstructed ECG signal from proposed method is comparable to the original signal.

Original languageEnglish
Pages (from-to)888-896
Number of pages9
JournalProcedia Engineering
Volume41
DOIs
Publication statusPublished - 1 Jan 2012
Event2nd International Symposium on Robotics and Intelligent Sensors 2012, IRIS 2012 - Kuching, Sarawak, Malaysia
Duration: 4 Sep 20126 Sep 2012

Keywords

  • ECG compression
  • Set partitioning in hierarchical trees (SPIHT)
  • Sleep stage classification
  • Wavelet transform

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