IJIRIS: International Journal of Innovative Research in Information Security E-ISSN: 2349-7017 Volume 10, Issue 02, February 2024 P-ISSN: 2349-7009 https://www.ijiris.com/archives __________________________________________________________________________________________________ IJIRIS © 2014-24, AM Publications -All Rights Reserved https://doi.org/10.26562/ijiris Page-85 Lung Function Monitoring Using Machine Learning Prathap K PG Scholar, Dept of Medical Electronics, Sengunthar Engineering College (Autonomous), Tiruchengode.,Tamil Nadu, INDIA prathap24122000@gmail.com Prof.Muhammadu sathik Raja Professor, Dept of Medical Electronics, Sengunthar Engineering College (Autonomous), Tiruchengode. Tamil Nadu, INDIA scewsadik@gmail.com Prof.K.Jamuna Professor, Dept of Medical Electronics, Sengunthar Engineering College (Autonomous), Tiruchengode. Tamil Nadu, INDIA jamunak.er@gmail.com Publication History Manuscript Reference No: IJIRIS/RS/Vol.10/Issue02/FBIS10089 Research Article | Open Access | Double-Blind Peer-Reviewed | Article ID: IJIRIS/RS/Vol.10/Issue02/FBIS10089 Received: 24, January 2024|Revised:12, February 2024 | Accepted: 18, February 2024 Published Online: 29,February 2024 Volume 2024 | Article ID FBIS10089 http://www.ijiris.com/volumes/Vol10/iss-02/10.FBIS10089.pdf Article Citation: Prathap,Muhammadu,Jamuna(2024).Lung Function Monitoring Using Machine Learning. International Journal of Innovative Research in Information Security (IJIRIS), Volume 10, Issue 02, Pages 85-88 doi: https://doi.org/10.26562/ijiris.2024.v1002.10 BibTex key: Prathap@2024Lung Copyright: ©2024 This is an open access article distributed under the terms of the Creative Commons Attribution License; which Permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Abstract: This project aims to develop a system equipped with machine learning algorithm capable of continuously monitoring respiratory conduct. The system utilizes machine learning to interpret pulmonary function tests, lift the management of respiratory diseases, and potentially deliver improvements in the diagnosis and treatment of various disease states in pulmonary and critical care medicine. Additionally, the system automatically predicts lung function based on acoustic signals from coughing and wheezing, enabling noninvasive monitoring of asthma severity. The project also seeks to forecast lung age and improve the current dataset of audio samples to enhance the accuracy and reliability of the results. The application of machine learning in pulmonary function testing holds significant potential for remote monitoring of high risk patients and the early detection and treatment of lung diseases. Keywords: Machine learning, Pulmonary disease, Lung volumes, Predictive analysis, Trained data INTRODUCTION The management of respiratory diseases, such as asthma and chronic obstructive pulmonary disease (COPD), is a critical aspect of pulmonary as well as as a critical care medicine. Accurate monitoring of lung function is essential for early detection and treatment of these diseases. Traditional methods, such as spirometry, are invasive and often require specialized equipment, limiting their accessibility and frequency of use. This project aims to develop a system that leverages machine learning algorithms to monitor lung function using non-invasive methods, such as analyzing acoustic signals from coughing and wheezing. This approach has the potential to enable continuous monitoring, allowing for early detection and treatment of respiratory diseases, and ultimately improving patient outcomes. STRUCTURE OF THE LUNGS The lungs are pair of organs located in the chest that are responsible for breathing. They are made up of a spongy tissue that contains millions of small air sacs called alveoli, which are besieged by capillaries. Oxygen from the air we inhale passes via the walls of the alveoli and into the capillaries, while carbon dioxide from the bloodstream passes into the alveoli to be exhaled. The lungs are divided into curves - the right lung has three curves while the left lung has two curves, to make room for the heart. The lungs are enfolded by a membrane called the pleura, which helps to conserve and support them. The trachea (windpipe) leads from the mouth and nose to the bronchi, which branch into smaller bronchioles which eventually lead to the alveoli. The lungs are also supported by a network of muscles and bones, including the diaphragm, which is the main muscle responsible for breathing. LUNG FUNCTION Lung function refers to the ability of the lungs to move air in and out of the body and exchange gases (oxygen and carbon dioxide) with the bloodstream. It is a measure of the efficiency of the respiratory system. There are several ways to measure lung function, including spirometry, which is a simple and non-invasive test that measures how much air you can breathe in and out, how quickly you can exhale, and how much air is left in your lungs after exhaling.