WHEEZE DETECTION IN THE RESPIRATORY SOUNDS USING HILBERT-HUANG TRANSFORM

被引:0
作者
Sayli, Omer [1 ]
机构
[1] Kocaeli Univ, Biyomed Muhendisligi Bolumu, Teknol Fak, Kocaeli, Turkey
来源
2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2014年
关键词
Hilbert-Huang transform; empirical mode decomposition; respiratory sounds; wheeze detection; CRACKLES;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Wheezes in the respiratory sounds are indicators for a number of diseases. Automatic detection of these signals -which have musical character and one or more dominant frequencies-is very important. In this study investigation of wheeze detection in the respiratory sounds using Hilbert-Huang transform is studied. This method allows analysis of signals which are neither stationary nor linear. Initially Intrinsic Mode Functions are found using Empirical Mode Decomposition. Instantaneous frequencies calculated using Hilbert transform of these signals were found to have distinct values with low variations, and constancy and variation of these instantaneous frequencies were affected by the power of the dominant frequencies in the wheeze.
引用
收藏
页码:2194 / 2197
页数:4
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