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Discrimination of normal and abnormal heart sounds using probability assessment

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F16%3A00474793" target="_blank" >RIV/68081731:_____/16:00474793 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.22489/CinC.2016.233-260" target="_blank" >http://dx.doi.org/10.22489/CinC.2016.233-260</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.22489/CinC.2016.233-260" target="_blank" >10.22489/CinC.2016.233-260</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Discrimination of normal and abnormal heart sounds using probability assessment

  • Original language description

    According to the “2016 Physionet/CinC Challenge”, we propose an automated method identifying normal or abnormal phonocardiogram recordings. Method: Invalid data segments are detected (saturation, blank and noise tests). The record is transformed into amplitude envelopes in five frequency bands. Systole duration and RR estimations are computed, 15-90 Hz amplitude envelope and systole/RR estimations are used for detection of the first and second heart sound (S1 and S2). Features from accumulated areas surrounding S1 and S2 as well as features from the whole recordings were extracted and used for training. During the training process, we collected probability and weight values of each feature in multiple ranges. For feature selection and optimization tasks, we developed C# application PROBAfind, able to generate the resultant Matlab code. Results: The method was trained with 3153 Physionet Challenge recordings (length 8-60 seconds, 6 databases). The results of the training set show the sensitivity, specificity and score of 0.93, 0.97 and 0.95, respectively. The method was evaluated on a hidden Challenge dataset with sensitivity and specificity of 0.77 and 0.91, respectively. These results led to an overall score of 0.84.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20601 - Medical engineering

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Computing in Cardiology (CinC) 2016

  • ISBN

    978-1-5090-0896-4

  • ISSN

    2325-8861

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    801-804

  • Publisher name

    Computing in Cardiology

  • Place of publication

    Vencouver

  • Event location

    Vencouver

  • Event date

    Sep 11, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000405710400201