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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.

A broad view on the analysis of Doppler embolic signals is presented, uniting physics, engineering and computing, and clinical aspects. The overview of the field discusses the physiological significance of emboli and Doppler ultrasound with particular attention given to Transcranial Doppler; an outline of high-performance computing is presented, disambiguating the terminology and concepts used thereafter. The presentation of the major diagnostic approaches to Doppler embolic signals focuses on the most significant methods and techniques used to detect and classify embolic events including the clinical relevancy. Coverage of estimators such as time-frequency, time-scale, and displacement-frequency is included. The discussion of current approaches targets areas of identified need for improvement. A brief historical perspective of high-performance computing of Doppler blood flow signals and particularly Doppler embolic signals is accompanied by the reasoning behind the technological trends and approaches. The final remarks include, as a conclusion, a summary of the contribution and as future trends, some pathways hinting to where new developments might be expected.

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This paper reports a novel method for representing Particular details of the blood flow during the diastolic phase the spectrum of pulsed Doppler ultrasound blood flow signals. It might be difficult to be aware of, due to the high amount of is an alternative to the time-frequency estimation method, that information displayed. maintains the information contained in the time signal using a To overcome this limitation, a spectral estimator with minimum computational cost solution.adaptive overlapping, displacement-frequency, is proposed.The key concept behind the displacement-frequency approach Keywords -Biomedical acoustics, Blood flow, Spectral analysis, is that all blood events should be given equal relevancy Biomedical signal processing. regardless the velocity of blood at the time of their occurrence. The displacement-frequency estimator accomplishes this by being aware of the rate of change of the I. Introduction relevant information in the signal, disregarding the data that Clinical information about the conditions of blood flow in conveys no novelty. vesselincalinformation be rac romultrcounditignsblso ruloint It is possible to preserve the information contained in a vessels can be extracted from ultrasound signals resultant Doppler signal if the samples considered for spectral from insonation ofthe particular artery or vein under analysis. estimation include an adequate record of all the blood cells Typically, clinical evaluation oftthe clinical condition is based that travel through the sample volume during a period of on observation of the real-time spectrogram of consecutive insonation. Assuming that predictions of the maximum cardiac cycles, the analysis of the values of the diagnostic velocities of flow are available, it is possible to determine the indexes computed from the spectrogram, and, the qualitative time resolution that satisfies this requirement. The processing appreciationioftheaDopplerisound produced. saved using such a matched resolution could be used to In clinical applications, time-frequency estimators are perform other calculations or in image processing associated preferred to time domain methods of Doppler signal analysis with the diagnostic procedure. All the processing involved because they enable a better and easier manipulation of the should be performed and displayed in real-time.variables that characterize the signals under observation.In this paper we review the time-frequency methodology, Traditionally, the Short Time Fourier Transform is the introduce displacement-frequency methodology, present the spectral estimator used to obtain the time-frequency formulation of the spectral estimator and, resorting to an representation of signals, but other methods have been example, we compare the time-frequency and the described as enhancing the quality of the estimation. Previous displacement-frequency estimators. Finally some concluding studies reported the Short Time Modified Covariance and the remarks are drawn highlighting possible application of the discrete Choi-Williams distr...