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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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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
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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