Ana Leiria

STFT or CWT for the detection of Doppler ultrasound embolic signals

Aiming reliable detection and localization of cerebral blood flow and emboli, embolic signals were added to simulated middle cerebral artery Doppler signals and analysed. Short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used in the evaluation. The following parameters were used in this study: the powers of the embolic signals added were 5, 6, 6.5, 7, 7.5, 8 and 9 dB; the mother wavelets for CWT analysis were Morlet, Mexican hat, Meyer, Gaussian (order 4) and Daubechies (orders 4 and 8); and the thresholds for detection (equated in terms of false positive, false negative and sensitivity) were 2 and 3.5 dB for the CWT and STFT, respectively. The results indicate that although the STFT allows accurately detecting emboli, better time localization can be achieved with the CWT. Among the CWT, the current best overall results were obtained with Mexican Hat mother wavelet, with optimal results for sensitivity (100% detection rate) for nearly all emboli power values studied.

Time-variable blood flow averaged waveforms

The computation of the average of random signals is addressed in this article. These averaging techniques are particularly relevant for Doppler blood flow clinical evaluation and research that usually accesses clinical indicators related to maximum and mean frequency, bandwidth and power variation over time. A novel technique is presented and compared to one previously described in the literature (Kitney and Giddens, “Analysis of blood velocity waveforms by phase shift averaging and autoregressive spectral estimation”, J. Biomech. Eng., 105, 398–404, 1983.). While the latter method is an iterative one, which sometimes does not converge, the former is a sequential technique, guaranteeing convergence. Clinical Doppler blood flow signals were averaged using both methods and the resulting waveforms were evaluated against the original signals, emphasising the impact on the relevant spectral parameters. The results obtained showed that, except for the maximum error in the computation of power variation over time, the errors produced are reduced by the proposed new algorithm.

Displacement-Frequency Doppler Blood Flow Estimation

This paper reports a novel method for representing the spectrum of pulsed Doppler ultrasound blood flow signals. It is an alternative to the time-frequency estimation method, that maintains the information contained in the time signal using a minimum computational cost solution.