Open AccessDiagnostic quality assured ECG signal compression with selection of appropriate mother wavelet for minimal distortion
Author(s) -
Kumar Jha Chandan,
Kolekar Maheskumar H.
Publication year - 2019
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2018.5217
Subject(s) - wavelet , distortion (music) , data compression , wavelet transform , computer science , algorithm , compression (physics) , compression ratio , pattern recognition (psychology) , signal compression , artificial intelligence , signal (programming language) , mathematics , speech recognition , image processing , image (mathematics) , engineering , telecommunications , bandwidth (computing) , amplifier , materials science , automotive engineering , composite material , programming language , internal combustion engine
This study presents a diagnostic quality assured electrocardiogram (ECG) signal compression algorithm which uses discrete wavelet transform with the selection of appropriate mother wavelet. Since distortion of reconstructed ECG signal depends on the type of mother wavelet used for decomposition. Therefore, appropriate mother wavelet is selected first which produces minimal distortion. Small valued wavelet transform coefficients are discarded using dead‐zone quantisation. Further integer conversion of coefficients is performed to improve compression at the cost of very less error. The processed transform coefficients obtained at this stage contain approximate coefficients and detail coefficients, where approximate coefficients consist very less repetition of data instances while detail coefficients are much repetitive. The repetition of detail coefficients is exploited by run–length encoding which represents the data as run and length. Compression performance of the proposed algorithm is evaluated using single‐channel ECG records taken from the Massachusetts Institute of Technology‐Beth Israel Hospital (MIT‐BIH) arrhythmia database, MIT‐BIH ECG compression test database and Physikalisch‐Technische Bundesanstalt (PTB) diagnostic ECG database. Compression results exhibit better performance than other existing techniques. Subjective evaluation of reconstructed ECG signals is also performed which ensures effective working of the proposed algorithm on the different morphology of ECG signals.