Detail publikačního výsledku

Classification of Normal and Abnormal Heart Sounds for Automatic Diagnosis

MISHRA, M.; SINGH, A.; DUTTA, M.; BURGET, R.; MAŠEK, J.

Originální název

Classification of Normal and Abnormal Heart Sounds for Automatic Diagnosis

Anglický název

Classification of Normal and Abnormal Heart Sounds for Automatic Diagnosis

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

Body auscultation;Heart Sounds;Mel Frequency Cepstral Coefficient;Classification;Support Vector Machine

Klíčová slova v angličtině

Body auscultation;Heart Sounds;Mel Frequency Cepstral Coefficient;Classification;Support Vector Machine

Autoři

MISHRA, M.; SINGH, A.; DUTTA, M.; BURGET, R.; MAŠEK, J.

Rok RIV

2018

Vydáno

05.07.2017

Místo

Barcelona, Španělsko

ISBN

978-1-5090-3981-4

Kniha

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

ISSN

1805-5435

Periodikum

International Conference on Telecommunications and Signal Processing (TSP)

Stát

Česká republika

Strany od

753

Strany do

757

Strany počet

5

URL

https://ieeexplore.ieee.org/document/8076089

BibTex

@inproceedings{BUT137841,
  author="Mohan {Mishra} and Anushikha {Singh} and Malay Kishore {Dutta} and Radim {Burget} and Jan {Mašek}",
  title="Classification of Normal and Abnormal Heart Sounds for Automatic Diagnosis",
  booktitle="40th Anniversary of International Conference on Telecommunications and Signal Processing (TSP)",
  year="2017",
  journal="International Conference on Telecommunications and Signal Processing (TSP)",
  pages="753--757",
  address="Barcelona, Španělsko",
  doi="10.1109/TSP.2017.8076089",
  isbn="978-1-5090-3981-4",
  issn="1805-5435",
  url="https://ieeexplore.ieee.org/document/8076089"
}