Literature DB >> 28900815

Wavelet-based Encoding Scheme for Controlling Size of Compressed ECG Segments in Telecardiology Systems.

Asiya M Al-Busaidi1, Lazhar Khriji2, Farid Touati3, Mohd Fadlee Rasid4, Adel Ben Mnaouer5.   

Abstract

One of the major issues in time-critical medical applications using wireless technology is the size of the payload packet, which is generally designed to be very small to improve the transmission process. Using small packets to transmit continuous ECG data is still costly. Thus, data compression is commonly used to reduce the huge amount of ECG data transmitted through telecardiology devices. In this paper, a new ECG compression scheme is introduced to ensure that the compressed ECG segments fit into the available limited payload packets, while maintaining a fixed CR to preserve the diagnostic information. The scheme automatically divides the ECG block into segments, while maintaining other compression parameters fixed. This scheme adopts discrete wavelet transform (DWT) method to decompose the ECG data, bit-field preserving (BFP) method to preserve the quality of the DWT coefficients, and a modified running-length encoding (RLE) scheme to encode the coefficients. The proposed dynamic compression scheme showed promising results with a percentage packet reduction (PR) of about 85.39% at low percentage root-mean square difference (PRD) values, less than 1%. ECG records from MIT-BIH Arrhythmia Database were used to test the proposed method. The simulation results showed promising performance that satisfies the needs of portable telecardiology systems, like the limited payload size and low power consumption.

Entities:  

Keywords:  Compression; Discrete wavelet transform; ECG; Payload packets; Running length encoding

Mesh:

Year:  2017        PMID: 28900815     DOI: 10.1007/s10916-017-0817-1

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  15 in total

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Authors:  A L Goldberger; L A Amaral; L Glass; J M Hausdorff; P C Ivanov; R G Mark; J E Mietus; G B Moody; C K Peng; H E Stanley
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Authors:  S M Ahmed; A Al-Shrouf; M Abo-Zahhad
Journal:  Med Eng Phys       Date:  2000-01       Impact factor: 2.242

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Authors:  Z Lu; D Y Kim; W A Pearlman
Journal:  IEEE Trans Biomed Eng       Date:  2000-07       Impact factor: 4.538

4.  Wavelet-based ECG compression by bit-field preserving and running length encoding.

Authors:  Hsiao-Lung Chan; You-Chen Siao; Szi-Wen Chen; Shih-Fan Yu
Journal:  Comput Methods Programs Biomed       Date:  2007-12-27       Impact factor: 5.428

5.  An ECG signals compression method and its validation using NNs.

Authors:  Catalina Monica Fira; Liviu Goras
Journal:  IEEE Trans Biomed Eng       Date:  2008-04       Impact factor: 4.538

6.  KLT-based quality controlled compression of single-lead ECG.

Authors:  T Blanchett; G C Kember; G A Fenton
Journal:  IEEE Trans Biomed Eng       Date:  1998-07       Impact factor: 4.538

7.  Wavelet and wavelet packet compression of electrocardiograms.

Authors:  M L Hilton
Journal:  IEEE Trans Biomed Eng       Date:  1997-05       Impact factor: 4.538

8.  An optimized compression algorithm for real-time ECG data transmission in wireless network of medical information systems.

Authors:  Gyoun-Yon Cho; Seo-Joon Lee; Tae-Ro Lee
Journal:  J Med Syst       Date:  2014-12-04       Impact factor: 4.460

9.  R-peaks detection based on stationary wavelet transform.

Authors:  M Merah; T A Abdelmalik; B H Larbi
Journal:  Comput Methods Programs Biomed       Date:  2015-06-16       Impact factor: 5.428

10.  Wavelet transform for real-time detection of action potentials in neural signals.

Authors:  Adam Quotb; Yannick Bornat; Sylvie Renaud
Journal:  Front Neuroeng       Date:  2011-07-15
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  1 in total

1.  Time-frequency localization using three-tap biorthogonal wavelet filter bank for electrocardiogram compressions.

Authors:  Ashish Kumar; Rama Komaragiri; Manjeet Kumar
Journal:  Biomed Eng Lett       Date:  2019-06-28
  1 in total

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