Feasibility Study for Gathering Lung Sound Recordings From Pulmonary Fibrosis Patients and Healthy Controls and Classifying Disease Status Using a Combination of Digital Sound Device and Machine Learning

This is a study of chest audio recordings obtained using a sound enhancer, in this case a Bluetooth device, combined with intelligent computer-processing and analysis. It is being carried out amongst pulmonary fibrosis patients and healthy controls of a similar age, with the aim to improve diagnosis of pulmonary fibrosis and remote monitoring of disease progression.

Expert respiratory doctors gain important insights about the health of a patient's lungs by listening to the chest with a stethoscope. Currently, there are insufficient respiratory experts and specialist equipment to meet the patient demand, leading to delays in diagnosis and treatment and a shortage of specialist care following diagnosis.

In this study the investigators are aiming to make that specialist practice much more available by recording lung sounds and developing software to do the intelligent analysis. Initial tests with publicly available recordings of expertly diagnosed respiratory sounds have shown that different lung diseases can be detected with a very high degree of accuracy using new software. Here the investigators want to test that software with a cost-effective digital sound device in a clinical setting. The aim is for respiratory diseases to be diagnosed quickly and easily and also, in future, for patients to be offered the option to monitor how well they are after diagnosis in their own home.