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At least 37 records · Page 2Linked to original sources
PubMed1988

A comparative study and assessment of Doppler ultrasound spectral estimation techniques. Part I: Estimation methods.

When compared to the classical Discrete Fourier Transform (DFT) or Fast Fourier Transform (FFT) approach, modern estimation methods offer the potential for achieving significant improvements in estimating the power density spectrum of Doppler ultrasound signals. Such improvements, for example, might enable minor flow disturbances to be detected, thereby improving the sensitivity in arterial disease assessment. Specifically, reduction in the variance and bias can be achieved, and this may enable disturbed flow to be detected in a more sensitive manner. The approach taken here, is to consider spectral estimation methods as a problem of fitting an assumed model to the Doppler signal. The models described assume that the signal is stationary. Since the Doppler signal is generally nonstationary, it is assumed that a short enough time window interval can be chosen over which the signal can be considered stationary. We shall review the various methods and when appropriate, relate them to the nature of the Doppler signal.

Arterial Occlusive Diseases↗
PubMed1995

An instrument for real-time spectral estimation of heart rate variability signals.

A Digital Signal Processor (DSP)-based instrument is proposed for estimating and displaying the Heart Rate Variability (HRV) spectrum in real-time. It consists of an intelligent module which is properly interfaced to an IBM PC and whose operations are independent from the computer's other tasks. In this way, the simultaneous recording of the ECG sequence, needed for the more complete off-line analysis, can be performed by the same host. The employed hybrid spectral estimator (in which a classical FFT analysis follows the autoregressive extrapolation of data) appears to be the most apt for the present fixed point arithmetics implementation. The reliability of the instrument and its accuracy are checked both with suitable test signals and by comparison with the results obtained through off-line analysis of the same ECG tracks. The instrument is presently used for cardiovascular investigations, in particular for quickly picking patients with cardiac autonomic neuropathy (CAN) out of a population of diabetic subjects.

Adult↗
PubMed1995

Measurement of baroreflex gain from heart rate and blood pressure spectra: a comparison of spectral estimation techniques.

The baroreflex is the physiological control system linking blood pressure and heart rate. Baroreflex gain, alpha, can be estimated from the ratio of heart rate and blood pressure spectra. The aim of this study was to quantify differences in estimates of alpha incurred by using four different spectral analysis techniques. ECG and blood pressure were recorded from 10 healthy subjects. Spectra were estimated using fast Fourier transform (FFT), zero-padded FFT (FFTZ), FFT of the windowed autocovariance function (ACVF), and maximum-entropy (ME) methods. For each subject a mean value of alpha was calculated in the MF (0.05-0.15 Hz) and HF (0.15-0.35 Hz) bands. Mean alpha MF varied between subjects (range 2-10 ms mmHg-1) as did mean alpha HF (range 4-12 ms mmHg-1). Mean differences in alpha MF and alpha HF estimated with different techniques were small. Differences in alpha MF ranged from 0.074 ms mmHg-1 (FFTZ against ME) to 0.298 ms mmHg-1 (FFT against ACVF) and those in alpha HF ranged from 0.057 ms mmHg-1 (FFT against FFTZ) to 0.342 ms mmHg-1 (ACVF against ME). None of these differences were significant. The use of different spectral analysis techniques does not significantly affect estimates of alpha.

Aged↗
PubMed1994

Differences in the power structures of Fourier transform and autoregressive spectral estimates of narrow-band Doppler signals.

There is considerable interest in the application of autoregressive (AR) spectral analysis to ultrasonic Doppler signals. Sonograms produced using this technique are, however, very different from those produced using classic Fourier transform methods. Simulations have shown that the heights of the peaks in the AR spectra of narrow-band signals are not necessarily proportional to signal power, and should be used with caution in the context of Doppler signal processing.

Algorithms↗
PubMed1997

Temporal and spectral estimations of harmonics-to-noise ratio in human voice signals.

The quantity, harmonic-to-noise ratio (HNR), has been used to estimate the level of noise in human voice signals. HNR estimation can be accomplished in two ways: (1) on a time-domain basis, in which HNR is computed directly from the acoustic waveform; and (2) on a frequency-domain basis, in which HNR is computed from a transformed representation of the waveform. An algorithm for computing HNR in the frequency domain was modified and tested in the work described here. The modifications were designed to reduce the influence of spectral leakage in the computation of harmonic energy, and to remove the necessity of spectral baseline shifting prescribed in one existing algorithm [G. de Krom, J. Speech Hear. Res. 36, 254-266 (1993)]. Frequency-domain estimations of HNR based on this existing algorithm and our modified algorithm were compared to time-domain estimations on synthetic signals and human pathological voice samples. Results indicated a highly significant, linear correlation between frequency- and time-domain estimations of HNR for our modified approach.

Female↗
PubMed1982

Identification and labeling of EEG graphic elements using autoregressive spectral estimates.

Syntactic EEG analysis requires descriptive labeling of short (1 s) epochs in an EEG. While discriminant analysis methods are useful for this purpose, significant improvement in label correctness can be achieved using the heuristic method described in this paper. The method is based on the estimation of frequency spectra by autoregressive (AR) modeling. The location of the peak frequencies and the power of these peaks are used to assign labels to 1 s epochs. Artefacts and epochs with exceptionally high or low amplitude and/or frequency values are identified as well. The assignment of labels is accomplished by comparing parameters, extracted from the power spectra estimated for 1 s epochs, with thresholds. These thresholds are automatically adapted to each individual EEG lead. In this paper, the method is outlined and its performance is compared with a discriminant analysis approach and visual labeling.

Computers↗
PubMed1990

Real-time system for robust spectral parameter estimation in Doppler signal analysis.

In assessing the level of stenosis in extracranial Doppler analysis, spectral analysis has until now been used qualitatively, for the most part. Owing to the many variables affecting the measurements (mainly noise level and instrument setting made subjectively by the operator), the reliability of the inferences on the degree of stenosis is not clearly definable. Under such conditions the need arises for algorithms and systems that can estimate spectral parameters with a higher degree of accuracy, to verify whether reliable inferences can indeed by made or if this technique is only a qualitative one. In the paper a real-time spectral analysis system is described. The system relies on a new spectral estimation algorithm which gives estimates with good robustness with respect to noise. Moreover, a clear measurement procedure which eliminates the many subjective factors affecting the estimates has also been proposed and used. The system has been evaluated with simulated signals and in clinical trials and has shown better performance than the commonly used commercial analysers.

Adult↗