TY - GEN
T1 - Analysis of doppler ultrasound blood flow signals of wrist radial artery for discriminating healthy people from 3 kinds of patients
AU - Wang, Kuanquan
AU - Xu, Chao
AU - Zhang, Dongyu
AU - Li, Naimin
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/51849162472
U2 - 10.1109/CBMS.2008.57
DO - 10.1109/CBMS.2008.57
M3 - Conference contribution
AN - SCOPUS:51849162472
SN - 9780769531656
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
SP - 87
EP - 89
BT - Proceedings of the 21st IEEE International Symposium on Computer-Based Medical Systems, CBMS 2008
T2 - 21st IEEE International Symposium on Computer-Based Medical Systems, CBMS 2008
Y2 - 17 June 2008 through 19 June 2008
ER -
