Development and Applications of a Novel Acoustic Model for Respiratory System

呼吸是由一个高度复杂和动态的系统控制的。然而，目前还没有一种方便且无创的技术来评估呼吸系统的动态变化。呼吸声是由空气通过咽和其他气道产生的，但没有简单的、动态的咽声学模型来研究呼吸声的产生机制，以及如何利用呼吸声分析来监测咽解剖和生理的变化。此外，呼吸相关的数据，如呼吸频率、强度和呼吸声音的频谱特征可以代表呼吸系统的特征。然而，目前可用的呼吸信号分析算法在很大程度上局限于检测呼吸速率，这并没有纳入呼吸信号产生的动态变化。因此，有必要开发生理驱动的数据挖掘算法来分析呼吸信号，以检查呼吸系统及其随时间的动态变化。

Breathing is controlled by a highly complex and dynamic system. However, there is no convenient and non-invasive technology to assess the dynamic changes in the respiratory system. Respiratory sounds are generated by the passage of air through pharynx and the rest of airways, but there is no simple and dynamic acoustic model of the pharynx in order to investigate the mechanisms of respiratory sound generation and how respiratory sounds analysis can be used to monitor variations in the pharyngeal anatomy and physiology. Furthermore, respiratory-related data such as breathing rate, intensity and spectral features of breathing sounds can represent characteristics of the respiratory system. However, currently available algorithms for analyzing respiratory signals are largely limited to examining respiratory rate, which does not incorporate the dynamic changes in the generation of respiratory signals. Therefore, there is a need to develop physiology-driven data mining algorithms for analysing respiratory signals to examine the respiratory system and its dynamic changes over time.