A Review of Classification Techniques Based on Neural Networks for Pulmonary Obstructive Diseases

Abstract

The automatic analysis of respiratory sound is of enormous challenge. The success of the Automatic Classification of pulmonary obstructive diseases can carry a radical change in the medical field. The extracted features of adventitious respiratory sound are classified; the ability of classifier provides the best results. Neural Networks have come out to be a promising classifier for respiratory disorders. The paper reviews works of classification of adventitious and vascular sounds by methods like Neural Networks, KNN, ANN, SNN, CNN, and others. CNN technique recently applied to classification of respiratory sound is analyzed. Due to a large number of ongoing researches in the field of classification of respiratory diseases by signal processing techniques, there is a great need to summaries results at a place. It is concluded that CNN has emerged out as one of the better technique for the classification of respiratory sounds.