Respiratory sound analysis - Hong, Jing Yee (2019)
Respiratory-related issues such as wheezing is one of the most common illnesses in Singapore, affecting approximately 20 per cent of children and 5 per cent of adults [1]. In the past, the most common method used to diagnose abnormal respiratory behaviour is using a noncomputerized instrument, stethoscope. However, the use of these instruments was deemed to be time-consuming and inaccurate diagnosis. Over the years, the advancement in technology have prompted the advancement of computerized respiratory sound analysis, which have been proven to be an integral asset tool to analyse and detect the abnormalities and disorders in the lungs. The use of computerized respiratory sound analysis is also able to increase accuracy in the diagnosis to a large extent. This report provides a comprehensive study and review of a computer-based respiratory sound analysis technique, known as the “Entropy-Based Wheeze Detection (EBWD)” method, which helps to detect and identify wheezing in lungs automatically. This detection method makes use of “entropy” to recognise and detect the pattern of frequency spectrum of the wheezing signal as well as wheeze detection, by using only a couple of entropy-based features. Sound files of wheezing and normal breath are being recorded and used for the testing of the proposed method. Sound files below 70Hz are filtered and later further processed using MATLAB. The accuracy of this method is later validated through the calculations of entropy difference and entropy ratio, using lung sounds of wheezing and normal breathing.