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Assessment of ECG signal quality after compression

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F19%3A00494536" target="_blank" >RIV/68081731:_____/19:00494536 - isvavai.cz</a>

  • Výsledek na webu

    <a href="http://dx.doi.org/10.1007/978-981-10-9038-7_31" target="_blank" >http://dx.doi.org/10.1007/978-981-10-9038-7_31</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-981-10-9038-7_31" target="_blank" >10.1007/978-981-10-9038-7_31</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Assessment of ECG signal quality after compression

  • Popis výsledku v původním jazyce

    Highly efficient lossy compression algorithms for ECG signals are connected with distortion of the signals, lossy compression is a compromise between compression efficiency and signal quality. It is recommended to express this relation using rate-distortion curve. To decide whether the signal is suitable for further analysis, it is necessary to assess its quality after reconstruction. Although there exist many methods for quality assessment, neither of them is standardized or unified. The methods usually do not offer any information about their acceptable values. This paper introduces 10 new methods for signal quality assessment and their limits. Four methods are simple (entropy, mean, median, spectra similarity), two are based on delineation of ECG (SiP, SiPA), and four combine dynamic time warping, delineation, and calculation of distance (DTWdist, DTWpmfp1, DTWpmfp2, pmfp). These methods are tested on the whole standard CSE database using compression algorithm based on wavelet transform and set partitioning in hierarchical trees. The signals were compressed with various efficiency expressed by average value length (avL). Two ECG experts divided the compressed signals into three quality groups: perfect quality, good quality, not evaluable ECG. Owing to the experts’ ECG classification, we set the range of avL for each quality group. Based on this, we determined corresponding ranges of new methods’ values. Based on the trend of rate-distortion curve, its sensitivity, variability, their ratio at important boundary avL = 0.8 bps, and computational demand of the methods, we recommend four methods for further use.

  • Název v anglickém jazyce

    Assessment of ECG signal quality after compression

  • Popis výsledku anglicky

    Highly efficient lossy compression algorithms for ECG signals are connected with distortion of the signals, lossy compression is a compromise between compression efficiency and signal quality. It is recommended to express this relation using rate-distortion curve. To decide whether the signal is suitable for further analysis, it is necessary to assess its quality after reconstruction. Although there exist many methods for quality assessment, neither of them is standardized or unified. The methods usually do not offer any information about their acceptable values. This paper introduces 10 new methods for signal quality assessment and their limits. Four methods are simple (entropy, mean, median, spectra similarity), two are based on delineation of ECG (SiP, SiPA), and four combine dynamic time warping, delineation, and calculation of distance (DTWdist, DTWpmfp1, DTWpmfp2, pmfp). These methods are tested on the whole standard CSE database using compression algorithm based on wavelet transform and set partitioning in hierarchical trees. The signals were compressed with various efficiency expressed by average value length (avL). Two ECG experts divided the compressed signals into three quality groups: perfect quality, good quality, not evaluable ECG. Owing to the experts’ ECG classification, we set the range of avL for each quality group. Based on this, we determined corresponding ranges of new methods’ values. Based on the trend of rate-distortion curve, its sensitivity, variability, their ratio at important boundary avL = 0.8 bps, and computational demand of the methods, we recommend four methods for further use.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    20601 - Medical engineering

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2019

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    IFMBE Proceedings

  • ISBN

    978-981-10-9037-0

  • ISSN

    1680-0737

  • e-ISSN

  • Počet stran výsledku

    5

  • Strana od-do

    169-173

  • Název nakladatele

    Springer

  • Místo vydání

    Singapore

  • Místo konání akce

    Prague

  • Datum konání akce

    3. 6. 2018

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku

    000449742700031