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CLC number: TP391

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Received: 2007-03-01

Revision Accepted: 2007-04-28

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Journal of Zhejiang University SCIENCE A 2007 Vol.8 No.8 P.1283~1289

http://doi.org/10.1631/jzus.2007.A1283


Investigation on the automatic parameters extraction of pulse signals based on wavelet transform


Author(s):  WANG Hui-yan, ZHANG Pei-yong

Affiliation(s):  College of Computer Science & Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China; more

Corresponding email(s):   zhangpy@vlsi.zju.edu.cn

Key Words:  Pulse signal, Feature extraction, Complex wavelet transform, Quantitative diagnosis


WANG Hui-yan, ZHANG Pei-yong. Investigation on the automatic parameters extraction of pulse signals based on wavelet transform[J]. Journal of Zhejiang University Science A, 2007, 8(8): 1283~1289.

@article{title="Investigation on the automatic parameters extraction of pulse signals based on wavelet transform",
author="WANG Hui-yan, ZHANG Pei-yong",
journal="Journal of Zhejiang University Science A",
volume="8",
number="8",
pages="1283~1289",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A1283"
}

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%T Investigation on the automatic parameters extraction of pulse signals based on wavelet transform
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%A ZHANG Pei-yong
%J Journal of Zhejiang University SCIENCE A
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%P 1283~1289
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%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A1283

TY - JOUR
T1 - Investigation on the automatic parameters extraction of pulse signals based on wavelet transform
A1 - WANG Hui-yan
A1 - ZHANG Pei-yong
J0 - Journal of Zhejiang University Science A
VL - 8
IS - 8
SP - 1283
EP - 1289
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2007.A1283


Abstract: 
This paper analyses a key problem in the quantification of pulse diagnosis. Due to the subjectivity and fuzziness of pulse diagnosis, quantitative methods are needed. To extract the parameters of pulse signals, the prerequisite is to detect the corners of pulse signals correctly. Up to now, the pulse parameters are mostly acquired by marking the pulse corners manually, which is an obstacle to modernize pulse diagnosis. Therefore, a new automatic parameters extraction approach for pulse signals using wavelet transform is presented. The results testified that the method we proposed is feasible and effective and can detect corners of pulse signals accurately, which can be expected to facilitate the modernization of pulse diagnosis.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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[6] Quddus, A., Fahmy, M.M., 1999. An Improved Wavelet-based Corner Detection Technique. Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, 6:3213-3216.

[7] Sun, L.U., Tang, Y.Y., You, X.G., 2004. Corner Detection for Object Recognition by Using Wavelet Transform. Proc. 3rd Int. Conf. on Machine Learning and Cybernetics. Shanghai, p.26-29.

[8] Tu, C.L., Hwang, W.L., 2005. Analysis of singularities from modulus maxima of complex wavelets. IEEE Trans. on Inf. Theory, 51:1049-1062.

[9] Wang, H.Y., Cheng, Y.Y., 2005. A Quantitative Model for Pulse Diagnosis in Traditional Chinese Medicine. 27th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society. Shanghai, China, p.5676-5679.

[10] Xu, L.S., Zhang, D., Wang, K.Q., Wang, L., 2006. Arrhythmic pulses detection using Lempel-Ziv complexity analysis. EURASIP J. Appl. Signal Processing, p.1-12.

[11] Xu, L.S., Zhang, D., 2007. Baseline wander correction in pulse waveform using wavelet-based cascaded adaptive filter. Computers Biol. Med., 37(5):716-731.

[12] Yoon, Y.Z., Lee, M.H., Soh, K.S., 2000. Pulse type classification by varying contact pressure. IEEE Eng. Med. Biol. Mag., 19:106-110.

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