Phonocardiogram Signal Processing for Automatic Diagnosis of Congenital Heart Disorders through Fusion of Temporal and Cepstral Features

Phonocardiogram Signal Processing for Automatic Diagnosis of Congenital Heart Disorders through Fusion of Temporal and Cepstral Features

Congenital heart disease (CHD) is a heart disorder associated with the devastating indications that result in increased mortality, increased morbidity, increased healthcare expenditure, and decreased quality of life. Ventricular Septal Defects (VSDs) and Arterial Septal Defects (ASDs) are the most c...

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Bibliographic Details
Main Authors: Sumair Aziz, Muhammad Umar Khan, Majed Alhaisoni, Tallha Akram, Muhammad Altaf
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Sensors
Subjects:
phonocardiogram
machine learning
empirical mode decomposition
feature extraction
mel-frequency cepstral coefficients
support vector machines
Online Access:https://www.mdpi.com/1424-8220/20/13/3790

Internet

https://www.mdpi.com/1424-8220/20/13/3790

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