Application of classical and model-based spectral methods to ophthalmic arterial Doppler signals with uveitis disease

In this study, Doppler signals recorded from ophthalmic artery of 75 subjects were processed by PC-computer using classical and model-based methods. The classical method (fast Fourier transform) and three model-based methods (Burg autoregressive, moving average, least-squares modified Yule–Walker autoregressive moving average methods) were selected for processing ophthalmic arterial Doppler signals with uveitis disease. Doppler power spectra of ophthalmic arterial Doppler signals were obtained by using these spectrum analysis techniques. The variations in the shape of the Doppler spectra as a function of time were presented in the form of sonograms in order to obtain medical information. These Doppler spectra and sonograms were then used to compare the applied methods in terms of their frequency resolution and the effects in determination of uveitis disease.     

Application of FFT analyzed cardiac Doppler signals to fuzzy algorithm

Doppler signals, recorded from the output of tricuspid, mitral, and aorta valves of 60 patients, were transferred to a personal computer via 16-bit sound card. The fast Fourier transform (FFT) method was applied to the recorded signal from each patient. Since FFT method inherently cannot offer a good spectral resolution at highly turbulent blood flows, it sometimes leads to wrong interpretation of cardiac Doppler signals. In order to avoid this problem, firstly six known diseased heart signals such as hypertension, mitral stenosis, mitral failure, tricuspid stenosis, aorta stenosis, aorta insufficiency were introduced to fuzzy algorithm. Then, the unknown heart diseases from 15 patients were applied to the same fuzzy algorithm in order to detect the kinds of diseases. It is observed that the fuzzy algorithm gives true results for detecting the kind of diseases.     

Comparison of eigenvector methods with classical and model-based methods in analysis of internal carotid arterial Doppler signals

Doppler ultrasound is known as a reliable technique, which demonstrates the flow characteristics and resistance of arteries in various vascular disease. In this study, internal carotid arterial Doppler signals recorded from 105 subjects were processed by PC-computer using classical, model-based, and eigenvector methods. The classical method (fast Fourier transform), two model-based methods (Burg autoregressive, least-squares modified Yule-Walker autoregressive moving average methods), and three eigenvector methods (Pisarenko, multiple signal classification, and Minimum-Norm methods) were selected for processing internal carotid arterial Doppler signals. Doppler power spectra of internal carotid arterial Doppler signals were obtained using these spectrum analysis techniques. The variations in the shape of the Doppler power spectra were examined in order to obtain medical information. These power spectra were then used to compare the applied methods in terms of their frequency resolution and the effects in determination of stenosis and occlusion in internal carotid arteries.     

‘Objective’ algorithm for maximum frequency estimation in Doppler spectral analysers

Real-time spectral analysis is often used to detect the maximum frequency envelope of Doppler signals, and thus the so-called spectral broadening, which is claimed to be a sensitive indicator of arterial stenosis. However, a rational criterion for the estimation of maximum frequencies is lacking. In the paper an ‘objective’ algorithm which takes account of the specificity and the sensitivity of the procedure of maximum frequency detection is proposed. This algorithm is based on the statistical characteristics of FFT spectral estimators, and allows thresholds to be set to be used in two-step decision procedures. The proposed algorithm can be easily implemented on microcomputers and/or commercial spectral analysers. The results obtained are fairly independent of the operator’s subjective judgement and spectral analyser gain.     

Spectral analysis of internal carotid arterial Doppler signals using FFT, AR, MA, and ARMA methods

In this study, Doppler signals recorded from internal carotid artery of 45 subjects were processed by PC-computer using classical (fast Fourier transform) and model-based (autoregressive, moving average, autoregressive moving average (ARMA) methods) methods. Power spectral density estimates of internal carotid arterial Doppler signals were obtained using these spectral analysis methods. The variations in the shape of the Doppler power spectra as a function of time were presented in the form of sonograms in order to determine the degree of internal carotid artery stenosis. These Doppler power spectra and sonograms were then used to compare the applied methods in terms of their frequency resolution and the impact on determining stenosis in internal carotid arteries. Based on the results, performance characteristics of the autoregressive and ARMA methods were found extremely valuable for spectral analysis of internal carotid arterial Doppler signals obtained from healthy subjects and unhealthy subjects having artery stenosis.     

Versatile microcomputer-based system for the capture,storage and processing of spectrum-analysed Doppler ultrasound blood flow signals

The evaluation of any method of analysis of Doppler ultrasound blood flow signals is involved and time consuming because of the considerable time necessary to investigate a statistically significant representative population of arteriopathic blood flow waveforms. To overcome these problems we have developed a microcomputer-based system for the capture, storage and processing of spectrum-analysed Doppler ultrasound blood flow signals. This system allows the collection and storage on floppy disk of waveforms from many sites in a large population of arteriopaths and their later analysis using any desired method. Having thus created on disk a suitable population of arteriopathic waveforms the evaluation of any method of waveform analysis, whether existing or new, is a much more convenient and far less time-consuming process. The system described is extremely versatile, for example in addition to the collection of data for postprocessing the system is also used for the real-time analysis of blood flow waveforms.     

Spectral broadening of ophthalmic arterial Doppler signals using STFT and wavelet transform

In this study, short-time Fourier transform (STFT) and wavelet transform (WT) were used for spectral analysis of ophthalmic arterial Doppler signals. Using these spectral analysis methods, the variations in the shape of the Doppler spectra as a function of time were presented in the form of sonograms in order to obtain medical information. These sonograms were then used to compare the applied methods in terms of their frequency resolution and the effects in determination of spectral broadening in the presence of ophthalmic artery stenosis. A qualitative improvement in the appearance of the sonograms obtained using the WT over the STFT was noticeable. Despite the qualitative improvement in the individual sonograms, no quantitative advantage in using the WT over the STFT for the determination of spectral broadening index was obtained due to the poorer variance of the wavelet transform-based spectral broadening index and the additional computational requirements of the wavelet transform.     

Comparison of FFT and adaptive ARMA methods in transcranial Doppler signals recorded from the cerebral vessels

In this work, transcranial Doppler signals recorded from the temporal region of the brain on 35 patients were transferred to a personal computer by using a 16-bit sound card. Fast Fourier transform and adaptive auto regressive-moving average (A-ARMA) methods were applied to transcranial Doppler frequencies obtained from the middle cerebral artery in the temporal region. Spectral analyses were obtained to compare both methods for medical diagnoses. The sonograms obtained using A-ARMA method give better results for spectral resolution than the FFT method. The sonograms of A-ARMA method offer net envelope and better imaging, so that the determination of blood flow and brain pressure can be calculated more accurately. All diseases show higher resistance to flow than controls with no difference between males and females. Whereas values between disease classes differed, resistance within each class was remarkably constant.     

Online measurement of cardiac indices from frequency transformed TAV Doppler ultrasound signals

A system is described for the analysis of blood flow signals in the aortic artery which enables indices of stroke volume and cardiac output to be derived. A commercial Doppler ultrasound monitor is used, the demodulated return signals are digitised, and frequency analysis is performed in real time using an FFT signal processing circuit. A Z-80 microprocessor controls the synchronisation of the data acquisition, transformation and display of the signals. Algorithms have been developed to identify the maximum velocity profile of each heartbeat and perform the necessary calculations to produce indices of stroke volume and cardiac output. The system has been evaluated against an existing offline method for a series of recordings on normal subjects and has demonstrated good repeatability. It has also been used in a clinical study on the effects of anaesthesia on chronic spinal injury patients. The results have shown that the system can be used to follow serial changes in cardiac performance within individual subjects.     

多普勒血流信号中频谱展宽效应产生的原因及其影响因素

在连续波多普勒血流测量系统中，实际接收到的频移信号是血流束祺矢量的综合反映，是速度矢量在各方面上产生频移信号的叠加，本文建立一个模型来分析在连续波多产为勒血流测量系统中频谱展宽产生的原因以及其影响因素，并且对于圆形探头给出了详细的讨论结果。     

Spectral analysis of doppler flow velocity signals: Assessment of objectives,methods, and interpretation

Both pulsed and continuous wave Doppler ultrasound systems are finding increased application in the noninvasive assessment of peripheral and carotid arterial disease. An important aspect of such systems is the use of real-time Doppler spectral analysis. It has been shown that spectral analysis can enhance the diagnostic, accuracy and, in the case of carotid assessment, can potentially provide a means for quantification. This paper critically reviews the methods available for real-time analysis and relates the requirements and problems to the design of systems for routine clinical use.     

Computer acquisition of multiunit nerve-spike signals

Two methods are described for the computer acquisition of multichannel, multiunit nervespike sequences. Both methods retain the spike peak-amplitude information, so that separation of the component single-unit populations can be carried out by the computer using this information. The first method uses analogue peak tracking to determine the spike amplitude, while in the second method the spike shape is reconstituted from the continuously sampled signal, and the peak amplitude is determined digitally. The performance and implementation requirements of the two systems are compared.     

On methods for preprocessing direction Doppler signals to allow display of directional blood-velocity waveforms by spectrum analysers

Two processors are described, either of which may be used before spectral analysis to allow unambiguous display of directional blood-velocity waveforms by the spectrum analyser. The relevant circuit details are presented.     

Computer implementation in the reconstruction of 2-D flow velocity fields in ultrasound Doppler color imaging

Doppler color imaging can easily render flow information within the vessels and simultaneously provide anatomic information for diagnostic purposes. However, the angle dependence problem of the Doppler velocity measurement is a significant barrier for continuing progress toward quantitative clinical applications of this technology. This paper presents a method and the computer implementation for reconstruction of the 2-D flow velocity field (angle independent) in ultrasound Doppler color imaging. Formulae for deriving angle independent velocity amplitude and angle direction from the color images acquired with a linear array transducer are given. The hardware configuration of the data acquiring and processing system is described. Major considerations in the development of algorithms, especially the strategies for reducing the computation time are presented.     

Uterine electromyogram database and processing function interface: An open standard analysis platform for electrohysterogram signals

The uterine electromyogram or electrohysterogram (EHG) is one of the most promising biophysical markers of preterm labor. At this time no recording parameter standard exists for EHG recordings which can be a problem for the establishment of international multicentric trials. In this paper, we present a management and processing system dedicated to storing and processing EHG signals. This system can process EHG signals recorded in different experimental conditions i.e. different sampling frequencies. The signal management is performed using an easy to use graphical user interface. Other available functions include visualization, preprocessing and analysis of EHG signals. The proposed processing functions provide temporal, spectral and time-scale parameters obtained from the EHG bibliography. The obtained results from real signals recorded in two different hospitals in two different countries are in accordance with the literature and demonstrate the potential of the proposed system. The incorporation of new functions is easy, due to a standardization of the EHG data formats.     

Analysis and processing of laser Doppler perfusion monitoring signals recorded from the beating heart

Laser Doppler perfusion monitoring (LDPM) can be used for monitoring myocardial perfusion in the non-beating heart. However, the movement of the beating heart generates large artifacts. Therefore the aim of the study was to develop an LDPM system capable of correlating the laser Doppler signals to the cardiac cycle and to process the signals to reduce the movement artifacts. Measurements were performed on three calves, both on the normal beating heart and during occlusion of the left anterior descending coronary artery (LAD). The recorded LDPM signals were digitally processed and correlated to the sampled ECG. Large variations in the output (perfusion) and DC signals during the cardiac cycle were found, with average coefficients of variation of 0.36 and 0.14 (n-14), respectively. However, sections with a relatively low, stable output signal were found in late diastole, where the movement of the heart is at a minimum. Occlusion of the LAD showed the importance of recording the laser Doppler signals at an appropriate point in the cardiac cycle, in this case late systole, to minimise movement artifacts. It is possible to further reduce movement artifacts by increasing the lower cutoff frequency when calculating the output signal.