基于机器学习的肺音分类技术的研究进展

Advances in Computer-based Lung Sounds Classification Method

肺音(Lung Sound)信号是人体呼吸系统与外界在换气过程中产生的一种生理声信号,其因含有大量的生理和病理信息而具有很高的研究价值。近年来,频发的雾霾天气等环境问题所带来的呼吸道疾病发病率的提高,也使得对肺部疾病诊断的快速性与准确性的需求大幅提升。肺部听诊以其迅捷便利和无创等优良特性重新引发人们的广泛关注,而自动肺音诊断技术的发展无疑会对肺部疾病诊断带来重要的帮助。电子听诊器以及其他信号采集技术等硬件方面的发展进一步促进了现代肺音信号的分析和识别技术的研究与进步。主要介绍了肺音的概念、基于计算机的肺音信号处理和模式识别技术,并对近年来基于机器学习的肺音分类技术的发展状况进行了总结与列举;最后,对肺音分类技术的研究和应用发展趋势进行了展望。

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.