Time-Frequency Analysis of the Blood Flow Doppler Ultrasound Signal

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.