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Related Experiment Videos

Quality driven gold washing adaptive vector quantization and its application to ECG data compression.

S G Miaou1, H L Yen

  • 1Department of Electronic Engineering, Chung Yuan Christian University, Taiwan, R.O.C. miaou@wavelet.el.cycu.edu.tw

IEEE Transactions on Bio-Medical Engineering
|March 18, 2000
PubMed
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This study introduces an adaptive algorithm for gold washing adaptive vector quantization (GW-AVQ) data compression. It automatically adjusts the distortion threshold (dth) to achieve desired signal quality, improving ECG compression efficiency.

Area of Science:

  • Signal Processing
  • Data Compression
  • Biomedical Engineering

Background:

  • Gold washing adaptive vector quantization (GW-AVQ) is a data compression technique.
  • Its performance relies heavily on a manually set distortion threshold (dth).
  • Manual dth setting is often inefficient and requires trial-and-error.

Purpose of the Study:

  • To develop an automated algorithm for setting the distortion threshold (dth) in GW-AVQ.
  • To ensure GW-AVQ achieves a user-specified quality criterion, such as percent root mean square difference (PRD) for ECG signals.
  • To validate the algorithm's effectiveness across diverse ECG data and compression frameworks.

Main Methods:

  • An algorithm was developed to automatically adjust the dth based on a target PRD.

Related Experiment Videos

  • The algorithm was tested with both direct GW-AVQ and wavelet-based GW-AVQ.
  • Four diverse ECG datasets from the MIT/BIH database were used for validation.

    • Main Results:

    • The proposed algorithm successfully achieved user-specified PRD for all tested ECG data.
    • The method demonstrated robustness regardless of initial dth selection or wavelet transform usage.
    • An average PRD of 6% and a compressed data rate of 410 bits/s were achieved with excellent visual quality.

    Conclusions:

    • The developed algorithm effectively automates dth selection for GW-AVQ.
    • This automation enhances the robustness and efficiency of ECG data compression.
    • The approach is particularly beneficial for subband coding requiring multiple GW-AVQ codebooks and dth values.