Research on Lung Sounds Classification Based on Deep Learning
ZHANG Yipeng1,2, CHEN Fuming1, SUN Wenhui1,2, LI Chuantao3, LI Nan1
1. Department of Medical Engineering, The 940th Hospital of PLA Joint Logistic Support Force, Lanzhou Gansu 730050, China;
2. School of Information Engineering, Gansu University of Chinese Medicine, Lanzhou Gansu 730000, China;
3. Aviation Physiology and Psychology Training Team, Naval Medical Center, Naval Medical University, Shanghai 200433, China
Abstract：Pulmonary diseases have a significant impact on human health and life safety, and abnormalities in the lungs are a direct
response to lung diseases. The study of lung sounds is of great significance in clinical diagnosis. With the continuous development of
electronic auscultation technology, the feature extraction and classification techniques of modern lung sounds have also been further
studied. At present, the research of lung sound classification is to combine signal analysis with deep learning algorithm to improve
the practical application of auxiliary electronic stethoscope. This paperaims to elaborate on the concept of lung sounds, analyze the
current development status of lung sound classification, and discuss the shortcomings of lung sound classification technology. The
goal is to an outlook on future research directions and application development trends in the field of lung sound classification.
张乙鹏1,2，陈扶明1 ，孙文慧1,2，李川涛3，李楠1. 基于深度学习的肺音分类研究[J]. 中国医疗设备, 2023, 38(11): 155-160.
ZHANG Yipeng1,2, CHEN Fuming1, SUN Wenhui1,2, LI Chuantao3, LI Nan1. Research on Lung Sounds Classification Based on Deep Learning. China Medical Devices, 2023, 38(11): 155-160.
