Enhancing Convolutional Neural Networks for Cardiovascular Disease Detection: A Comparative Analysis of Data Augmentation Strategies Using Heart Sound Signals

Registration ID: IJNRD_219124

Published ID: IJNRD2404851

DOI: Click Here to Get

Dr.shalbha Chaudhary , Ms.Navita Bansal

Cardiovascular diseases (CVDs,) Convolutional Neural Networks (CNNs), Phonocardiogram (PCG), Data Augmentation, Heart sound detection

Effectively overseeing and swiftly identifying cardiovascular diseases (CVDs) are crucial for decreasing associated death rates. Identifying cardiovascular diseases (CVDs) can pose difficulties, especially when symptoms are not present. This has led to a rise in research dedicated to developing automated systems that can detect CVDs at an early stage. Lately, there has been a notable enthusiasm in utilising convolutional neural networks (CNNs) that have been trained on heart sound information, particularly the phonocardiogram (PCG). Convolutional neural networks (CNNs) generally require a large amount of annotated training data to achieve maximum performance. However, there is a scarcity of annotated datasets for phonocardiogram (PCG) that can differentiate between normal and abnormal cases. In order to address this difficulty, it is crucial to improve the classification performance of Convolutional Neural Networks (CNNs), which will allow for training on smaller PCG databases. This paper investigates two data augmentation (DA) techniques: window slicing with spectrogram, which entails dividing a single PCG into numerous signals turned into spectrogram data; and a synthetic spectrogram-based generative adversarial network, which generates synthetic data. The effectiveness of these data augmentation approaches is proven through studies on heart sound detection, accompanied by a comprehensive analysis of the results, including measures of accuracy, sensitivity, and specificity.

Published Paper   E-Certificate

Dr.shalbha Chaudhary & Ms.Navita Bansal (April-2024). Enhancing Convolutional Neural Networks for Cardiovascular Disease Detection: A Comparative Analysis of Data Augmentation Strategies Using Heart Sound Signals. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), i405-i418. https://ijnrd.org/papers/IJNRD2404851.pdf

Volume 9 Issue 4, April-2024

Pages : i405-i418

Paper Reg. ID: IJNRD_219124

Published Paper Id: IJNRD2404851

Downloads: 000121977

Research Area: Engineering

Country: ghaziabad, Uttar pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404851.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404851

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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