Signal domain in respiratory sound analysis: Methods, application and future development

Abstract

The development of digital signal processing technology encourages researchers to develop better methods for automatic lungs sound recognition system than the existing ones. Lung sounds were originally assessed manually according to doctor's expertise. Signal processing techniques are intended to reduce subjectivity factor. Signal processing techniques for lung sound recognition are developed by researchers based on their point of view to the lung sounds. Several researchers developed signal processing methods in a time domain. Meanwhile, other researchers developed signal processing techniques in a frequency domain or combined some signal domains. This paper describes the sensor used, the dataset used and the characteristics of extraction techniques as well as the classifier in the system developed by the previous researchers. In the final section, we describe some possible development of the future potential application of lung sound analysis.