Remote Monitoring and Analysis of Human Lung Sound

Respiratory illness is recognized internationally as one of the commonest medical disorders affecting the world's populous countries. The identification of continuous abnormal lung sounds, like adventitious breath sounds in the total breathing cycle is of great importance in the diagnosis of obstructive airways pathologies. To this vein, the current work introduces an efficient method for the detection of wheezes, crackles, stridor, pleural rub and bronchial breath sounds as well as the remote monitoring of such sounds. In this work wheezes have been detected using Frequency Duration Dependant Threshold (FDDT) algorithm which is better than the other algorithms in respect to the fact they are based on human auditory modeling and does not have any ambiguity while deciding whether a particular signal is wheeze or not.