Respiratory Sound Analysis for Lung Disease Diagnosis

Lung diseases are the major global health concern, often necessitating accurate and timely diagnosis for effective management and treatment. The World Health Organization (WHO) reported that lung disorders were causing an increasing number of deaths in India, accounting for 11% of all fatalities. A kind of lung illness claimed the lives of 142.09 people out of every 10,000. Through the use of deep learning algorithms and sound wave analysis, this study presents a novel method for detecting lung disease. This approach promises to deliver a non-invasive, economical, and reliable tool for accurate disease diagnosis by utilizing the rich information conveyed in lung sounds. The research entails gathering lung sound recordings from a wide range of people, including healthy controls and people with a variety of respiratory diseases. These recordings have undergone careful curation to create a comprehensive collection that captures the auditory characteristics of lung illnesses. Advanced signal processing techniques are used to extract pertinent data, capturing crucial traits including wheezing, crackles, and patterns of airflow.