Classification of Normal and Abnormal Heart Sounds for Automatic Diagnosis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F17%3APU124094" target="_blank" >RIV/00216305:26220/17:PU124094 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/8076089" target="_blank" >https://ieeexplore.ieee.org/document/8076089</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TSP.2017.8076089" target="_blank" >10.1109/TSP.2017.8076089</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of Normal and Abnormal Heart Sounds for Automatic Diagnosis

Popis výsledku v původním jazyce

Body auscultation is an easy and non-invasive method for detection of diseases in human body. The conventional method is a bit time consuming and requires professionals for diagnosis. Automatic diagnosis of diseases using heart sound can be of great help in the rural areas where professional help is not available. The proposed work presents an automatic and efficient method of diagnosis and classification using heart sound. Mel Frequency Cepstral Coefficient (MFCC) features are extracted from heart sounds for diagnosis. Supervised classification method is used to separate the normal and abnormal heart sound for detection of diseases. The proposed method was tested on a comprehensive database of heart sounds and achieved accuracy of 97.50 % during classification process. The experiment results indicates that the proposed method is efficient for classification of healthy/unhealthy heart sounds and computationally cheap making it suitable for real time applications.

Název v anglickém jazyce

Classification of Normal and Abnormal Heart Sounds for Automatic Diagnosis

Popis výsledku anglicky

Body auscultation is an easy and non-invasive method for detection of diseases in human body. The conventional method is a bit time consuming and requires professionals for diagnosis. Automatic diagnosis of diseases using heart sound can be of great help in the rural areas where professional help is not available. The proposed work presents an automatic and efficient method of diagnosis and classification using heart sound. Mel Frequency Cepstral Coefficient (MFCC) features are extracted from heart sounds for diagnosis. Supervised classification method is used to separate the normal and abnormal heart sound for detection of diseases. The proposed method was tested on a comprehensive database of heart sounds and achieved accuracy of 97.50 % during classification process. The experiment results indicates that the proposed method is efficient for classification of healthy/unhealthy heart sounds and computationally cheap making it suitable for real time applications.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

40th Anniversary of International Conference on Telecommunications and Signal Processing (TSP)

ISBN

978-1-5090-3981-4

ISSN

1805-5435

e-ISSN

—

Počet stran výsledku

5

Strana od-do

753-757

Název nakladatele

Neuveden

Místo vydání

Barcelona, Španělsko

Místo konání akce

Barcelona

Datum konání akce

5. 7. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000425229000160