M. M. M. Moura

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.

FAST CALCULATION OF THE BESSEL TIME-FREQUENCY DISTRIBUTION

Abstract The Bessel distribution, one of the Cohens class time-frequency distributions, has been reported, in many application areas and particularly on biomedical signal processing, as an efficient spectral estimator. Its usage on practical applications has been deprecated due to its computational burden. This paper presents a Bessel distribution algorithm and the results of its implementation on a variety of commercial off-the-shelf personal computers. The analysis of these results indicates that the Bessel distribution may no longer be put aside for real-time applications. It is demonstrated that the real-time estimation of pulsed Doppler blood flow spectral parameters is achievable.

Time, time-frequency and displacement-frequency analysis of embolic signals

The characteristics of a new method, the displacement-frequency representation, prompted the study of its use for the analysis of embolic blood flow signals. This paper reports the comparison of displacement-frequency and time-frequency methods with time domain methods, in the characterization of emboli. The study was performed on clinical signals derived from gaseous and participate embolic events. The results obtained with the different approaches were compared. The conclusions of this study provide encouragement for the use of displacement-frequency domain processing for this kind of analysis.