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Huang, N.E., Shen, Z., Long, S.R., Tung, C.C. and Liu, H.H. (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society, 454, 903-995.

has been cited by the following article:

• TITLE: Wrist blood flow signal-based computerized pulse diagnosis using spatial and spectrum features

  AUTHORS: Dong-Yu Zhang, Wang-Meng Zuo, David Zhang, Hong-Zhi Zhang, Nai-Min Li

  KEYWORDS: Pulse Diagnosis; Blood Flow Velocity; Hilbert-Huang Transform; Support Vector Machine

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.3 No.4, April 28, 2010

  ABSTRACT: ABSTRACT Current computerized pulse diagnosis is mainly based on pressure and photoelectric signal. Considering the richness and complication of pulse diagnosis information, it is valuable to explore the feasibility of novel types of signal and to develop appropriate feature representation for diagnosis. In this paper, we present a study on computerized pulse diagnosis based on blood flow velocity signal. First, the blood flow velocity signal is collected using Doppler ultrasound device and preprocessed. Then, by locating the fiducial points, we extract the spatial features of blood flow velocity signal, and further present a Hilbert-Huang transform-based method for spectrum feature extraction. Finally, support vector machine is applied for computerized pulse diagnosis. Experiment results show that the proposed method is effective and promising in distinguishing healthy people from patients with cho- lecystitis or nephritis.