抽象的
该研究描述了一种使用数字信号处理技术定量表征咳嗽声音的方法。提出了哮喘和非哮喘咳嗽声音之间的差异。分析了来自12个哮喘和5个非哮喘受试者的咳嗽。在自由运行的运动测试之前和之后,以5 kHz的采样率向咳嗽声音和流量进行数字化。单个咳嗽分为两种或三个阶段,对应于初始的光泽开口爆发,更安静的中间阶段,(有时)最终关闭爆发。然后调用标准信号处理技术以表征前两个阶段的光谱和时间形状。因子分析表明,两个相的光谱形状是独立的,每个阶段的频谱形状在很大程度上被频谱中的“峰值”的程度,以及通过低频和高频之间的能量平衡。咳嗽波形的初始突发和零交叉速率的持续时间(表示在每个前两相期间的“光谱平衡”)比对于非哮喘咳嗽较小。较少的哮喘咳嗽含有最后的爆发。两组之间的判别分析给出了20-30%的分类错误率。 The peak flow recorded during the cough was significantly smaller for asthmatics, and correlated very well with the peak flow recorded during forced expiration. Thus, significant differences exist between asthmatic and non-asthmatic cough sounds. An effective representation of the temporal structure of the cough sound is required to successfully characterize the cough.