Diagnosing The Breathing Sounds as COPD or Asthma

Abstract

The aim of this research is to classify recorded chest sounds to distinguish among Asthma, Bronchiolitis, Bronchiectasis, COPD, Pneumonia and URTI diseases versus Healthy sound. That is, this paper introduces and challenges a seven- class problem using one of the few publicly available collection of sounds, the Respiratory Sound database from Kaggle. The performance of several deep learning algorithms has been compared and the Convolutional Neural Network architecture resulted in the most successful model. Unlike previous papers which worked on a subset of this database, this work proposes a more comprehensive seven-class challenge to distinguish among all diseases sampled in the database. The performance of several deep-learning algorithms has been compared and the best model is described in detail.