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Quality Assessment and Classification of Heart Sounds Using PCG Signals Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Fully Automated Identification of Heart Sounds for the Analysis of Cardiovascular Pathology

Authors : Ghafoor Sidra, Nasim Ammara, Hassan Taimur, Hassan Bilal, Ahmed Ramsha

Published in: Applications of Intelligent Technologies in Healthcare

Publisher: Springer International Publishing

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Abstract

Cardiac disorders are spreading rapidly all over the world, and as per the World Health Organization (WHO), 17.5 million people die each year due to cardiovascular diseases (CVD). So there is a dire need to develop cost-effective, time-efficient, and fully automated solutions to diagnose cardiovascular abnormalities. Many researchers have worked on detecting CVD from electrocardiogram (ECG) signals. ECG signals give reliable information about cardiac pathology; however phonocardiogram (PCG) signal provides an easy, cost-effective, objective, and comprehensive information about cardiovascular abnormalities by measuring heartbeats. This paper presents a fully automated robust clinical decision support system that can identify cardiovascular pathology by analyzing heart sounds from PCG signals. The proposed system was tested on 55 PCG signals from which 24 samples contained healthy and 31 samples contained abnormal heart sounds. The proposed system correctly classified healthy and diseased samples with the accuracy, sensitivity, and negative predictive value (NPV) of 87.2%, 96.7%, and 94.7%, respectively.

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Metadata
Title
Fully Automated Identification of Heart Sounds for the Analysis of Cardiovascular Pathology
Authors
Ghafoor Sidra
Nasim Ammara
Hassan Taimur
Hassan Bilal
Ahmed Ramsha
Copyright Year
2019
Book
Applications of Intelligent Technologies in Healthcare

Print ISBN: 978-3-319-96138-5

Electronic ISBN: 978-3-319-96139-2

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-96139-2_12