Abstract: Lung sound signal is a physiological acoustic signal generated in the ventilation process between the human respiratory system and outside.It contains a wealth of physiological and pathological information and has great value in research.In recent years,environmental problems,like air pollution and the weather with fog and haze,have led to a rise in the incidence of respiratory disease.To meet the growing demand for fast and accurate diagnosis of lung disease,auscultation has attracted more attention with its convenience and safety,yet it shows limitations as it depends on the experience and the hearing capacity of the physician and the limited frequency response of the stethoscope.With the development of automated lung sound diagnostic techniques and hardware,lung sound classification by computer makes up for the defect in traditional auscultation.This paper introduced the concept of lung sounds,computer-based lung sound signal processing and pattern recognition techniques,and summarized the recent development of machine learning-based lung sounds classification techniques.Finally,the research and application development trend of lung sounds classification techniques were discussed.

Key words: Lung sound,Classification techniques,Machine learning