Time-Frequency Analysis of the Blood Flow Doppler Ultrasound Signal.

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  • Noguchi Yasuaki
    Department of Applied Physics, National Defense Academy, Yokosuka 239-8686, Japan
  • Kashiwagi Eiichi
    Department of Computer Science, National Defense Academy, Yokosuka 239-8686, Japan
  • Watanabe Kohtaro
    Department of Computer Science, National Defense Academy, Yokosuka 239-8686, Japan
  • Matsumoto Fujihiko
    Department of Applied Physics, National Defense Academy, Yokosuka 239-8686, Japan
  • Sugimoto Suguru
    School of Engineering, Shohnan Institute of Technology, Fujisawa 251-8511, Japan

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Power spectral analysis is extensively used to interpret ultrasound data. However, the technique is useful only when the data can be treated as stationary. Ultrasound data are mostly nonstationary. Thus, a short time Fourier transform (STFT or spectrogram) is widely used to analyze spectral components which change with time. However, the STFT has a low accuracy in both time and frequency domains. Currently, Cohen's class time-frequency (TF) analysis is popular for analyzing nonstationary signals. The authors recently proposed a new kernel (named a figure eight kernel). In order to apply the TF analysis with the new kernel to a blood flow signal, experimental data were obtained from the carotid artery by an ultrasound Doppler monitor (Toitsu, Japan). To analyze the data, three kernels were used: (1) a Wigner kernel, (2) a Choi-Williams kernel, and (3) a figure eight kernel. Using our new figure eight kernel, the demodulation accuracy was improved and blood flow components were observed.

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