4.4 Article

AI-CardioCare: Artificial Intelligence Based Device for Cardiac Health Monitoring

Journal

IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
Volume 52, Issue 6, Pages 1292-1302

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/THMS.2022.3211460

Keywords

Heart; Phonocardiography; Stethoscope; Diseases; Feature extraction; Deep learning; Task analysis; Body auscultation; cardiac disorders; deep neural network; health care system; phonocardiogram

Funding

  1. Department of Science and Technology, India [DST/BDTD/EAG/2017]

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This article proposes an AI-based device for automatic and real-time diagnosis of cardiac diseases. The device acquires heart sound signals through a customized stethoscope and processes the signals using deep learning techniques to classify four major cardiac diseases. By integrating the device with a low-cost single-board processor, it becomes a valuable and affordable diagnostic tool for both medical professionals and personal usage at home.
Cardiac disorders are one of the leading causes of mortality around the globe and early diagnosis of heart diseases can be beneficial for its mitigation. In this article, an artificial intelligence (AI) based device has been proposed, which allows for an automatic and real-time diagnosis of cardiac diseases based on deep learning techniques. The heart sound (phonocardiogram) signal is acquired by a customized designed stethoscope and the signal is processed before analysis using AI methods for the classification of four major cardiac diseases (Aortic Stenosis, Mitral Regurgitation, Mitral Stenosis, and Mitral Valve Prolapse). Two deep learning-based neural networks, one-dimensional (1-D) convolutional neural network (CNN) and spectrogram based 2-D-CNN models from the analysis of these signals has been integrated with a low-cost single-board processor to make a standalone device. All data processing is done in a single hardware setup and user interface is provided allowing the user to control the data accessibility and visibility to generate the diagnostic report. As a result, the developed device has demonstrated to be a valuable low-cost diagnostic tool for both medical professionals and personal usage at home.

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