华南理工大学学报(自然科学版) ›› 2013, Vol. 41 ›› Issue (6): 1-5.doi: 10.3969/j.issn.1000-565X.2013.06.001

• 电子、通信与自动控制 •    下一篇

基于S 变换的罗音信号检测算法

李真真 吴效明   

  1. 华南理工大学 生物科学与工程学院,广东 广州 510006
  • 收稿日期:2012-10-29 修回日期:2012-11-21 出版日期:2013-06-25 发布日期:2013-05-03
  • 通信作者: 李真真(1982-),女,博士后,主要从事生物医学信号处理研究. E-mail:betty@scut.edu.cn
  • 作者简介:李真真(1982-),女,博士后,主要从事生物医学信号处理研究.
  • 基金资助:

     国家自然科学基金资助项目(81070612)

Detection Algorithm of Crackle Signals Based on S Transform

Li Zhen- zhen Wu Xiao- ming   

  1. School of Biological Science and Engineering,South China University of Technology,Guangzhou 510006,Guangdong,China
  • Received:2012-10-29 Revised:2012-11-21 Online:2013-06-25 Published:2013-05-03
  • Contact: 李真真(1982-),女,博士后,主要从事生物医学信号处理研究. E-mail:betty@scut.edu.cn
  • About author:李真真(1982-),女,博士后,主要从事生物医学信号处理研究.
  • Supported by:

     国家自然科学基金资助项目(81070612)

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.

关键词: 信号处理, 信号检测, 罗音信号, 计算机辅助诊断, 特征提取, 时频分析

Abstract:

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

Key words:  signal processing, signal detection, crackle signal, computer- aided diagnosis, feature extraction, time- frequency analysis

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