Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Wavelet-based lossy-to-lossless ECG compression in a unified vector quantization framework.

Shaou-Gang Miaou1, Shu-Nien Chao

  • 1Multimedia Computing and Telecommunications Laboratory, Department of Electronic Engineering, Chung Yuan Christian University, Chung-Li, 32023 Taiwan, ROC. miaou@wavelet.el.cycu.edu.tw

IEEE Transactions on Bio-Medical Engineering
|March 12, 2005
PubMed
Summary

This study enhances electrocardiogram (ECG) signal compression by fixing coding inefficiencies in a wavelet-based vector quantization (VQ) method. The improved approach achieves significant gains in lossless compression efficiency for ECG data.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Kalman Filtering and Nonlinear Penalty Regression Approach for Noninvasive Anemia Detection with Palpebral Conjunctiva Images.

Journal of healthcare engineering·2017
Same author

Examining palpebral conjunctiva for anemia assessment with image processing methods.

Computer methods and programs in biomedicine·2017
Same author

A lossless compression method for medical image sequences using JPEG-LS and interframe coding.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2009
Same author

Automatic quality control for wavelet-based compression of volumetric medical images using distortion-constrained adaptive vector quantization.

IEEE transactions on medical imaging·2004
Same author

Wavelet-based ECG compression using dynamic vector quantization with tree codevectors in single codebook.

IEEE transactions on bio-medical engineering·2002
Same author

A data-hiding technique with authentication, integration, and confidentiality for electronic patient records.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2002

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Data Compression

Background:

  • Prior work introduced wavelet-based vector quantization (VQ) for lossy electrocardiogram (ECG) signal compression.
  • Existing methods faced coding inefficiencies, particularly in lossless compression scenarios.

Purpose of the Study:

  • To address and resolve coding inefficiencies in wavelet-based VQ for lossless ECG compression.
  • To extend the existing framework for unified lossy and lossless ECG compression.
  • To improve the coding efficiency of Set Partitioning in Hierarchical Trees (SPIHT) for ECG data.

Main Methods:

  • Implemented wavelet transform (WT) using 9/7 filters for lossy and 5/3 integer filters for lossless compression.
  • Modified the codebook updating mechanism to support lossless compression.

Related Experiment Videos

  • Developed a novel, cost-effective coding strategy to enhance SPIHT efficiency on less significant bit representations of WT coefficients.
  • Utilized ECG records from the MIT/BIH Arrhythmia and European ST-T Databases for testing.

    • Main Results:

    • The proposed unified framework successfully enables both lossy and lossless ECG compression.
    • Experimental results demonstrate significant improvements in coding efficiency for lossless compression.
    • The developed codec shows a 33% improvement over the direct SPIHT approach.
    • A 26% improvement was observed compared to the prior wavelet-based VQ work.

    Conclusions:

    • The enhanced wavelet-based VQ approach offers a unified and efficient framework for ECG compression.
    • The modifications significantly boost coding efficiency, especially for lossless compression tasks.
    • This work provides a more effective method for compressing vital ECG diagnostic data.