DocumentCode :
2132941
Title :
A novel method for feature extraction of crackles in lung sound
Author :
Li Zhenzhen ; Wu Xiaoming ; Du Minghui
Author_Institution :
Sch. of Biosci. & Bioeng., South China Univ. of Technol., Guangzhou, China
fYear :
2012
fDate :
16-18 Oct. 2012
Firstpage :
399
Lastpage :
402
Abstract :
Crackles are an important kind abnormal lung sound for detection in lung sound analysis. Focused on characteristic morphology of crackles in time-domain, a novel time-domain processing method is proposed to extract features of crackles based on the newly rising theories of Fractional Hilbert Transform. After applying the transformation of Fractional Hilbert Transform with various fractional values, exclusive timedomain features are merged and can be used as validated detection features. Experiments show great application feasibilities for such kind of wave detections. Later we use correlation functions to construct an elementary detection system, and system simulation results support the effectiveness of our work. Discussions on detection errors are followed.
Keywords :
Hilbert transforms; acoustic signal detection; acoustic signal processing; feature extraction; lung; medical signal detection; medical signal processing; time-domain analysis; abnormal lung sound; crackles; detection errors; elementary detection system; feature extraction; fractional Hilbert transform; lung sound analysis detection; morphology; system simulation; time-domain processing method; wave detections; Biomedical signal processing; crackle detection; lung sound analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-1183-0
Type :
conf
DOI :
10.1109/BMEI.2012.6512982
Filename :
6512982
Link To Document :
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