New parameters for respiratory sound classification

被引：0
|
作者：
Bahoura, M [1 ]
Pelletier, C [1 ]
机构：
[1] Univ Quebec, DMIG, Rimouski, PQ G5L 3A1, Canada
来源：
CCECE 2003: CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, VOLS 1-3, PROCEEDINGS: TOWARD A CARING AND HUMANE TECHNOLOGY | 2003年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a new approach based on cepstral analysis is proposed to classify respiratory sounds. The sound signal is divided into segments, which are characterized by a reduced number of cepstral coefficients. Those segments are then classified as whether containing wheezes or normal respiratory sounds, by using the Vector Quantization (VQ) method. This approach is tested and compared to other kind of features extraction like the autoregressive representation and the wavelet transform.
引用
收藏
页码：1457 / 1460
页数：4
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