NDLI: Analysis of Doppler Ultrasound Blood Flow Signals of Wrist Radial Artery for Discriminating Healthy People from 3 Kinds of Patients

Content Provider	IEEE Xplore Digital Library
Author	Kuanquan Wang Chao Xu Dongyu Zhang Naimin Li
Copyright Year	2008
Description	Author affiliation: Bio-Comput. Res. Center, Harbin Inst. of Technol., Harbin (Kuanquan Wang; Chao Xu; Dongyu Zhang; Naimin Li)
Abstract	Doppler ultrasound blood flow signal (DUBFS) is a non-stationary signal that is widely used in the study of the clinical diagnosis of cardiovascular diseases. According to the theory of pulse diagnosis of traditional Chinese medicine, in this paper, a feature extraction method based on Hilbert_Huang transform is proposed in order to investigate the relationship between the DUBFS of wrist radial artery and the pathological changes of certain organs. The extracted features have applied in classification experiments on 4 groups of data, which are healthy persons, gastritis patients, cholecystitis patients and nephritis patients, respectively. Experimental results with high recognition rates demonstrate that Hilbert_Huang transform is an effective method of time-frequency analysis for DUBFS, and extracted features by proposed method have promising discriminating ability between the healthy people and 3 kinds of patients.
Starting Page	87
Ending Page	89
File Size	417818
Page Count	3
File Format	PDF
ISBN	9780769531656
ISSN	10637125
DOI	10.1109/CBMS.2008.57
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-17
Publisher Place	Finland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal analysis Ultrasonic imaging Blood flow Wrist Arteries Feature extraction Data mining Clinical diagnosis Cardiovascular diseases Medical diagnostic imaging diagnosis Doppler Ultrasound Blood Flow Signal Hilbert_Huang transform time-frequency analysis
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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