Literature DB >> 11059165

ECG signal compression using analysis by synthesis coding.

Y Zigel1, A Cohen, A Katz.   

Abstract

In this paper, an elecrocardiogram (ECG) compression algorithm, called analysis by synthesis ECG compressor (ASEC), is introduced. The ASEC algorithm is based on analysis by synthesis coding, and consists of a beat codebook, long and short-term predictors, and an adaptive residual quantizer. The compression algorithm uses a defined distortion measure in order to efficiently encode every heartbeat, with minimum bit rate, while maintaining a predetermined distortion level. The compression algorithm was implemented and tested with both the percentage rms difference (PRD) measure and the recently introduced weighted diagnostic distortion (WDD) measure. The compression algorithm has been evaluated with the MIT-BIH Arrhythmia Database. A mean compression rate of approximately 100 bits/s (compression ratio of about 30:1) has been achieved with a good reconstructed signal quality (WDD below 4% and PRD below 8%). The ASEC was compared with several well-known ECG compression algorithms and was found to be superior at all tested bit rates. A mean opinion score (MOS) test was also applied. The testers were three independent expert cardiologists. As in the quantitative test, the proposed compression algorithm was found to be superior to the other tested compression algorithms.

Entities:  

Mesh:

Year:  2000        PMID: 11059165     DOI: 10.1109/10.871403

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

1.  Wavelet-based watermarking and compression for ECG signals with verification evaluation.

Authors:  Kuo-Kun Tseng; Xialong He; Woon-Man Kung; Shuo-Tsung Chen; Minghong Liao; Huang-Nan Huang
Journal:  Sensors (Basel)       Date:  2014-02-21       Impact factor: 3.576

Review 2.  A Comparative Analysis of Methods for Evaluation of ECG Signal Quality after Compression.

Authors:  Andrea Němcová; Radovan Smíšek; Lucie Maršánová; Lukáš Smital; Martin Vítek
Journal:  Biomed Res Int       Date:  2018-07-18       Impact factor: 3.411

3.  An adaptive framework for real-time ECG transmission in mobile environments.

Authors:  Kyungtae Kang
Journal:  ScientificWorldJournal       Date:  2014-07-03
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.