Permutation of Deep Learning Approaches to Perceive Heart Problems Using Audio Signals

International Journal of Electrical and Electronics Engineering

© 2025 by SSRG - IJEEE Journal

Volume 12 Issue 6

Year of Publication : 2025

Authors : K. Vetriselvi, G. Karthikeyan

10.14445/23488379/IJEEE-V12I6P112

How to Cite?

K. Vetriselvi, G. Karthikeyan, "Permutation of Deep Learning Approaches to Perceive Heart Problems Using Audio Signals," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 6, pp. 146-157, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I6P112

Abstract:

Heart disease, which is widely known as the “Silent Killer,” kills many people worldwide, and it is now affecting younger people in India. Prevention of fatal outcomes starts with early detection, but traditional machine learning models widely used are inadequate in providing accurate results. So, deep learning techniques are implemented for better solutions. Deep learning models are applied in this research to forecast heart disease by examining heart sound signals. This research uses a machine learning approach with Modified LSTM and a transfer learning technique by feeding spectrograms. Three important steps during detection are normalization, feature extraction, and classification, which are used to analyse heart sounds precisely. Three pre-trained models, Enhanced Inception V3, Elevated CNN and Facelifted ResNet 50, are assessed against a sequence classifier. Facelifted ResNet 50 can detect heart disease by abnormal heartbeat sounds such as artifact, extras, extrasystole and murmur with 98% accuracy. The unique aspect is using transfer learning classifiers based on spectrograms and compared with sequence model Modified LSTM to diagnose patients. This method promotes better detection of cardiovascular diseases and helps introduce intelligent medical technologies.

Keywords:

Audio signals, Cardiovascular syndrome, Convolutional Neural Network, Inception V3, Long Short-Term Memory, Residual Network 50 model, Silent killer.

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