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DOI: 10.14569/IJACSA.2025.0160287
PDF

IoMT-Enabled Noninvasive Lungs Disease Detection and Classification Using Deep Learning-Based Analysis of Lungs Sounds

Author 1: Muhammad Sajid
Author 2: Wareesa Sharif
Author 3: Ghulam Gilanie
Author 4: Maryam Mazher
Author 5: Khurshid Iqbal
Author 6: Muhammad Afzaal Akhtar
Author 7: Muhammad Muddassar
Author 8: Abdul Rehman

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 2, 2025.

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Abstract: Noninvasive and accurate methods for diagnosing respiratory diseases are essential to improving healthcare consequences. The Internet of Medical Things (IoMT) is critical in driving developments in this field. This work presents an IoMT-enabled approach for lung disease detection and classification, using deep learning techniques to analyze lung sounds. The proposed approach uses three datasets: the Respiratory Sound, the Coronahack Respiratory Sound, and the Coswara Sound. Traditional machine learning models, including the Extra Tree Classifier and AdaBoost Classifier, are used to benchmark performance. The Extra Tree Classifier achieved 94.12%, 95.23%, and 94.21% across the datasets, while the AdaBoost Classifier showed improvements with 95.42%, 96.33%, and 94.76%. The proposed deep neural network (DNN) achieves accuracies of 98.92%, 99.33%, and 99.36% for the same datasets. This study explores the transformative potential of the Internet of Medical Things (IoMT) in augmenting diagnostic precision and advancing the field of respiratory healthcare.

Keywords: Deep learning; respiratory sound; coronahack respiratory sound and coswara sound; IoMT

Muhammad Sajid, Wareesa Sharif, Ghulam Gilanie, Maryam Mazher, Khurshid Iqbal, Muhammad Afzaal Akhtar, Muhammad Muddassar and Abdul Rehman, “IoMT-Enabled Noninvasive Lungs Disease Detection and Classification Using Deep Learning-Based Analysis of Lungs Sounds” International Journal of Advanced Computer Science and Applications(IJACSA), 16(2), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160287

@article{Sajid2025,
title = {IoMT-Enabled Noninvasive Lungs Disease Detection and Classification Using Deep Learning-Based Analysis of Lungs Sounds},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160287},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160287},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {2},
author = {Muhammad Sajid and Wareesa Sharif and Ghulam Gilanie and Maryam Mazher and Khurshid Iqbal and Muhammad Afzaal Akhtar and Muhammad Muddassar and Abdul Rehman}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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