New application of wavelet transform in classification the arterial pulse signals

  • Authors:

  • Yasaman Zandi Mehran

  • Affiliations:

  • Department of Biomedical Engineering, Bioelectric Group, Islamic Azad University, Science and Research Branch, Tehran, Iran

  • Venue:
  • ICOSSE'06 Proceedings of the 5th WSEAS international conference on System science and simulation in engineering
  • Year:
  • 2006

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Abstract

The Discrete Wavelet Transform (DWT) is a transformation that can be used to analyze the temporal and spectral properties of non-stationary signals. In this paper we describe some applications of the DWT to the problem of extracting information from normal and abnormal arterial pulses. We shall review a feature extraction algorithm of pulse signals, wavelet analysis, with aim of generating the most appropriate input vector for a neural classifier and we will know that the wavelet approach is highly suitable for the analysis of such signals. Some examples of the application of the wavelet transform and artificial network to identify the pulse signals are provided here. Application range from the extraction of normative signals from nonnormative, to extraction of quantitative parameters for clinical purposes.