Hierarchical Bayesian Modeling for FVC Prediction in Pulmonary Fibrosis and Low-Cost Spirometer Incorporating Internet of Things

Lung disease remains a significant public health concern in India, with a rising prevalence attributed to various environmental and lifestyle factors. Recent statistics reveal that chronic obstructive pulmonary disease (COPD) affects approximately 57.8 million people in India, while pulmonary fibrosis accounts for a substantial portion of respiratory-related morbidity and mortality nationwide. Despite the growing prevalence, accurate lung function diagnosis and monitoring remain challenging, particularly in resource-constrained settings. This study presents a novel approach utilizing hierarchical Bayesian modelling in conjunction with low-cost IoT-based spirometry technology for predicting forced vital capacity (FVC) in pulmonary fibrosis patients. Leveraging real-time data from the Indian population,[7] [8] where respiratory diseases are prevalent, our research underscores the critical need for reliable and accessible spirometry measurements for effective disease management. We begin by elucidating the epidemiological landscape of lung disease in India, highlighting the alarming rates of COPD and pulmonary fibrosis. Recent studies suggest that when integrated into clinical practice, spirometry data can significantly improve diagnostic accuracy and treatment outcomes for respiratory conditions. Leveraging data from the Indian population, where respiratory diseases are prevalent, our research underscores the critical need for reliable and accessible spirometry measurements for effective disease management. Our proposed methodology integrates the YFS201 flow sensor with an ESP8266 microcontroller, providing a cost-effective solution for real-time measurement of airflow. Through hierarchical Bayesian modeling, we demonstrate the capability of our approach to accurately predict FVC in pulmonary fibrosis patients, thereby facilitating early detection and personalized treatment strategies. By incorporating spirometry data into clinical practice, our research aims to empower healthcare professionals in India and beyond to make informed decisions, optimize patient care, and mitigate the burden of lung disease.