Heart sounds analysis using probability assessment

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F17%3A00480378" target="_blank" >RIV/68081731:_____/17:00480378 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1088/1361-6579/aa7620" target="_blank" >http://dx.doi.org/10.1088/1361-6579/aa7620</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1361-6579/aa7620" target="_blank" >10.1088/1361-6579/aa7620</a>

Result language

angličtina

Original language name

Heart sounds analysis using probability assessment

Original language description

This paper describes a method for automated discrimination of heart sounds recordings according to the Physionet Challenge 2016. The goal was to decide if the recording refers to normal or abnormal heart sounds or if it is not possible to decide (i.e. 'unsure' recordings). Approach: Heart sounds S1 and S2 are detected using amplitude envelopes in the band 15-90Hz. The averaged shape of the S1/S2 pair is computed from amplitude envelopes in five different bands (15-90 Hz, 55-150 Hz, 100-250 Hz, 200-450 Hz, 400800 Hz). A total of 53 features are extracted from the data. The largest group of features is extracted from the statistical properties of the averaged shapes, other features are extracted from the symmetry of averaged shapes, and the last group of features is independent of S1 and S2 detection. Generated features are processed using logical rules and probability assessment, a prototype of a new machine-learning method. Main results: The method was trained using 3155 records and tested on 1277 hidden records. It resulted in a training score of 0.903 (sensitivity 0.869, specificity 0.937) and a testing score of 0.841 (sensitivity 0.770, specificity 0.913). The revised method led to a test score of 0.853 in the follow-up phase of the challenge. Significance: The presented solution achieved 7th place out of 48 competing entries in the Physionet Challenge 2016 (official phase). In addition, the PROBAfind software for probability assessment was introduced.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20601 - Medical engineering

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)

Publication year

2017

Confidentiality

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

Name of the periodical

Physiological Measurement

ISSN

0967-3334

e-ISSN

—

Volume of the periodical

38

Issue of the periodical within the volume

8

Country of publishing house

GB - UNITED KINGDOM

Number of pages

16

Pages from-to

1685-1700

UT code for WoS article

000406783300006

EID of the result in the Scopus database

2-s2.0-85026772546