中文摘要：

呼吸音中的罗音信号随机性强,变异性大,同时又蕴含了丰富的疾病信息.为从呼吸音中有效地检测出罗音,文中引入S变换,提出了一种基于S变换的罗音信号检测算法.首先从呼吸音信号S变换的时频谱图中提取罗音的时频特征,降维后采用局部峰值判别法检测罗音.实验结果表明,该算法的罗音信号检测正确率达93.70%,检测性能优于其他算法,说明该检测算法是有效的.

英文摘要：

Crackle signals in respiratory sounds are of strong randomness and high variability and they contain lots of disease information.In order to detect crackle signals,the S transform is introduced and a detection algorithm based on S transform is proposed.In this algorithm,time-frequency features of crackle signals are extracted from the S-transform time-frequency spectrum of respiratory sound signals.Then,after a dimension reduction,local peaks are picked out to detect crackles.Experimental results show that the proposed algorithm is effective because it is of an accuracy up to 93.70%,which is higher than that of some other detection algorithms.