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PubMed1982

Diagnosis of carotid stenosis by bruit spectral analysis.

Bruit spectral analysis provides an improved noninvasive method of quantifying the severity of carotid stenosis, and the method of Lees estimates the residual luminal diameter. Although the analysis required is complex, the test can be easily performed using the Spectraview, a microcomputer-based device which records and processes the sound information. The present study evaluated 44 cervical bruits in patients and found that in 84 percent of the vessels the estimated luminal size was within 1 mm of the angiographic lumen. Although substantial experience is required to obtain the maximum diagnostic accuracy, work with the technique during 18 months indicates that is provides more information from arterial bruits thn traditional phonoangiography.

Aged↗
PubMed1999

A comparison of period amplitude analysis and FFT power spectral analysis of all-night human sleep EEG.

Zero-cross and zero-derivative period amplitude analysis (PAA) data were compared with power spectral analysis (PSA) data obtained with the fast Fourier transform in all-night sleep EEG from 10 subjects. Although PAA zero-cross-integrated amplitude showed good agreement with PSA power in 0.3-2 Hz, zero-cross analysis appears relatively ineffective in measuring 2-4 Hz and above waves. However, PAA zero-derivative measures of peak-trough amplitude correlated well with PSA power in 2-4 Hz. Thus, while PAA appears able to measure the entire EEG spectrum, the analytic technique should be changed from zero cross to zero derivative at about 2 Hz in human sleep EEG. PAA and PSA both demonstrate robust and interrelated across-night oscillations in three frequency bands: delta (0.3-4 Hz); sigma (12-16 Hz); and fast beta (20-10 Hz). The frequencies between delta and sigma, and between sigma and fast beta, did not show clear across-night oscillations using either method, and the two methods showed lower epoch-to-epoch agreement in these intermediate bands. The causes of this reduced agreement are not immediately clear, nor is it obvious which method gives more valid results. We believe that the three strongly oscillating frequency bands represent fundamental properties of the human sleep EEG that provide important clues to underlying physiological mechanisms. These mechanisms are more likely to be understood if their dynamic properties are preserved and measured naturalistically rather than being forced into arbitrary sleep stages or procrustean models. Both PAA and PSA can be employed for such naturalistic studies. PSA has the advantages of applying the same analytic method across the EEG spectrum and rests on more fully developed theory. Combined zero-cross and zero-derivative PAA demonstrates EEG oscillations that closely parallel those observed with spectral power, and the PAA measures do not rely on assumptions about the spectral composition of the signal. In addition, both PAA techniques can measure the relative contributions of wave amplitude and incidence to total power: These waveform characteristics represent different biological processes and respond differentially to a wide range of experimental conditions.

Adult↗
PubMed1984

[Evaluation of the degree of carotid stenosis by spectral analysis of the Doppler signal. Comparison of the results of spectral analysis, angiography and anatomo-pathology].

With the single Doppler spectrum analysis, one can appreciate the degree of the carotid stenosis according to the importance of the haemodynamic disturbances induced by the stenosis. The purpose of our study is to show the possibilities and the limitations of this method. Spectrum disturbances were classified in 5 grades, each of them being related to the importance of the stenosis. The degree of stenosis has been evaluated by the C.W. Doppler spectrum analysis, the angiographies and the anatomical study of the endarteriectomies. We considered that we had a perfect concordance between the results of the different methods when the degree of stenosis measured on the angiographies or on the endarteriectomies was compatible with the spectrum analysis classification: grade I: stenosis inferior to 40% (in area), 23% (in diameter); grade II: stenosis ranging between 40 and 60% in area (23 and 40 in diameter); grade III: stenosis of 60 to 75% in area (40 to 50% in diameter) and of particular shape (extended plaque); grade IV: stenosis ranging between 60 and 90% in area (40 to 70% in diameter); grade V: stenosis higher than 90% in area (70% in diameter). The confrontation of spectrum analysis and angiographic date concerns 58 bifurcations. We got a perfect correlation in 93% of the cases. The confrontation of the spectrum analysis method and the anatomical study of the endarteriectomies concerns 38 bifurcations. We got a perfect correlation in 92% of the cases. The appreciation of the carotid stenosis degree is now performed in routine at the Hospital. For some patients, the endarteriectomy has been decided from the clinical and the spectrum analysis data, and an electro-encephalogram with compression. However these date are generally completed with an angiography with venous punction.

Carotid Arteries↗
PubMed1993

Assessing the severity of aortic valve stenosis by spectral analysis of cardiac murmurs (spectral vibrocardiography). Part I: Technical aspects.

Assessing the severity of aortic stenosis remains an important clinical problem. The turbulent pressure fluctuations generated by the confined jet down-stream of the stenotic valve produce vibrations in the aortic wall. These vibrations are transmitted through the chest to the skin surface, where they can be measured as systolic ejection murmurs. The purpose of the present study was to find the relationship between the severity of aortic valve stenosis and the frequency content of the precordial systolic murmurs, and to evaluate the transthoracic attenuation of murmurs and its variation from patient to patient. Twenty-four patients with clinical signs of aortic stenosis underwent cardiac catheterization to measure the peak transvalvular pressure difference. The mean energy density spectrum of the measured systolic precordial murmurs was calculated and the murmur energy ratio between 100-500 Hz and 20-500 Hz was correlated to the transvalvular pressure difference. The inter-individual variability of the transthoracic attenuation was evaluated by calculating the transthoracic transfer function from simultaneous measurements of precordial vibrations at the second right intercostal space and intravascular recordings of high frequency pressure fluctuations in the ascending aorta. The transvalvular pressure difference and the square root of the murmur energy ratio correlated well (r = 0.81, SEE = 27 mmHg). In the frequency range from 10-500 Hz the transthoracic transfer function could be modelled by a low-pass filter function with a low frequency attenuation of 36 +/- 7.7 dB (mean +/- SD), a corner frequency of 26 +/- 12 Hz and an attenuation slope of -29 +/- 7.9 dB/decade. Spectral analysis of systolic murmurs might be an attractive non-invasive addition to the array of techniques already in use for assessing the severity of aortic stenosis. It is a simple and cost effective technique, and requires less skill and time for data analysis than conventional methods.

Adult↗
PubMed1998

A simplified method for the quantitative analysis of 99Tc(m)-GSA liver scintigraphy using spectral analysis.

The aim of this study was to develop a simplified method for quantitative analysis of liver scintigraphy with 99Tc(m)-diethylenetriamine pentaacetic acid-galactosyl-human serum albumin (GSA) using spectral analysis. Dynamic liver scintigraphy using GSA was performed in three normal volunteers and 19 patients with chronic liver disease. Dynamic data were obtained with a gamma camera for 30 min after the injection of approximately 185 MBq GSA. The rate constant for the liver uptake of GSA from the blood (Ku, min(-1)), total excretion rate (Ke, min(-1)) and non-specific volume of distribution (Vh) were obtained by spectral analysis. Vh was defined as the volume in the liver region of interest (ROI) occupied by GSA which was in equilibrium with that in the blood. It should be noted that Vh had no units, since the counts in both the liver and heart ROIs were normalized by scan length to obtain counts pixel(-1) min(-). For comparison, compartmental analysis was also performed. A receptor index (LHL15) was calculated by dividing the radioactivity of the liver ROI by that of the liver plus heart ROIs 15 min post-injection. The Ku values obtained by spectral analysis (y) agreed well with those obtained by compartmental analysis (x) (y = 0.953x - 0.013, r = 0.992, S.E.E. = 0.016 min(-1)). The Ke and Vh values obtained by spectral analysis (y) correlated significantly with those obtained by compartmental analysis (x) (y = 1.149x - 0.016, r = 0.826, S.E.E. = 0.017 min(-1) for Ke; y = 1.191x + 0.044, r = 0.975, S.E.E. = 0.021 for Vh). The Ku values obtained by spectral analysis decreased as the severity of liver disease progressed, and were non-linearly related to the LHL15 values, suggesting that Ku is more sensitive to liver damage than LHL15, especially in the early stages of liver damage. These results suggest that spectral analysis applied to dynamic liver scintigraphy with GSA provides a simple, non-invasive and useful tool for the quantitative evaluation of liver function.

Hepatitis↗
PubMed1984

Detection of technical error during arterial surgery by pulsed Doppler spectral analysis.

Pulsed Doppler spectral analysis of midstream flow was compared with arteriography in 90 patients following carotid endarterectomy (N = 60) or lower-extremity bypass grafting (N = 30) for the detection of unsuspected technical error. Spectral changes in the velocity waveform indicating flow disturbance were identified in the endarterectomy or anastomotic sites of 11 patients (12%). All were associated with an anatomic defect apparent on arteriography. The revision of major defects in six patients (7%) corrected the flow disturbance. The absence of flow disturbance in 79 patients (88%) predicted a technically satisfactory arterial reconstruction. Intraoperative assessment by pulsed Doppler spectral analysis is a noninvasive, rapid, and accurate method for detecting technical errors during arterial surgery. The high sensitivity of this method makes it suitable for use as a screening test, resulting in the selective use of operative arteriography.

Angiography↗
PubMed1988

Quantification of cardiovascular instability in premature infants using spectral analysis of waveforms.

Spectral analysis was applied to blood pressure and cerebral blood flow velocity recordings in premature infants with respiratory distress in order to quantify respiration-induced cardiovascular variability. Aortic blood pressure was transduced via an umbilical arterial catheter and cerebral blood flow velocity measured in the anterior cerebral artery using a 10 MHz continuous wave Doppler velocimeter in 16 infants less than or equal to 32 wk gestational age. Spectral analysis of the resulting waveforms revealed heart rate and respiratory rate components whose relative amplitudes (heart rate/respiratory rate amplitude ratio) represent an index of that component of variability induced by respiratory events. The mean (heart rate/respiratory rate amplitude) ratio was 47.2 in spontaneously breathing infants and rose to 165.9 in infants who were ventilated during muscle paralysis (p = 0.0003). Cerebral blood flow velocity recordings showed R components in only 22 of 38 simultaneous recordings. This method can be used to quantify respiration-induced cardiovascular variability and its response to therapy, and may provide a means of identifying infants at risk from brain injury due to an inability to regulate cerebral blood flow.

Blood Flow Velocity↗
PubMed1977

EEG operant conditioning in a monkey model: II. EEG spectral analysis.

EEG power spectral analysis was studied from 14 (alumina-gel) chronically epileptic, undrugged monkeys during an EEG operant conditioning experiment. The composite profile of the average epileptic monkey shows the majority of power to be below 10 Hz. Because of the large variance in the data, no significant changes in the EEG power spectra could be detected as a function of conditioning. The possible reasons for this large variance are discussed. Hypothesis from previous human "biofeedback" studies would allow the prediction that those frequencies corresponding to the mu and sensory-motor-rhythm should negatively covary with seizure frequency. Data from this study did not support such assertions. The method of using spectral analysis for quantifying changes in the EEG which covary with operant conditioning is evaluated.

Animals↗
PubMed1995

Quantitative assessment of the autonomic nervous system activities during atropine-induced bradycardia by heart rate spectral analysis.

Using power spectral analysis of heart rate fluctuation, autonomic nervous system activities in bradycardia appearing in the initial phase of atropine administration were evaluated quantitatively in 16 healthy females. Atropine sulfate (10 micrograms/kg), diluted in 100 ml of 0.9% NaCl solution, was intravenously infused at a rate of 0.5 micrograms/kg per min. Electrocardiograms were sampled for 4 min for later analysis before and 0, 5, 10, 15 and 20 min after initiation of atropine infusion. Powers of low (LFC, 0.05-0.15 Hz) and high-frequency (HFC, 0.15-0.4 Hz) components in the power spectrum of R-R interval variations, and the LFC/HFC ratio were determined at each sampling point. HFC power at 0-4 min increased from 1.11 +/- 0.18 ms2 (mean) of baseline value to 1.37 +/- 0.19 ms2 (P < 0.05). The next 5-9-min value of 1.48 +/- 0.14 ms2 was the maximum, and the amount of atropine infused by 9 min was 4.5 micrograms/kg. The HFC powers following this point decreased. The 20-24-min value after 10 micrograms/kg atropine decreased to 0.21 +/- 0.03 ms2 (P < 0.01), which was lower than the previous 15-19-min value of 0.36 +/- 0.04 ms2 (P < 0.01). The LFC/HFC ratios showed no significant change for the initial 9 min of the atropine infusion. However, these ratios at 15-19 min and 20-24 min were increased from 0.50 +/- 0.04 (mean) of baseline value to 0.75 +/- 0.09 and 0.81 +/- 0.09, respectively (P < 0.01). A transient vagotonic state after atropine administration, followed by the well-known vagolytic state, was quantitatively detected by non-invasive spectral analysis of heart-rate fluctuation.

Adolescent↗
PubMed1991

Modern spectral analysis techniques for blood flow velocity and spectral measurements with pulsed Doppler ultrasound.

Four spectral analysis techniques were applied to pulsed Doppler ultrasonic quadrature signals to compare the relative merits of each technique for estimation of flow velocity and Doppler spectra. The four techniques were 1) the fast Fourier transform method, 2) the maximum likelihood method, 3) the Burg autoregressive algorithm, and 4) the modified covariance approach to autoregressive modeling. Both simulated signals and signals obtained from an in vitro flow system were studied. Optimal parameter values (e.g., model orders) were determined for each method, and the effects of signal-to-noise ratio and signal bandwidth were investigated. The modern spectral analysis techniques were shown to be superior to Fourier techniques in most circumstances, provided the model order was chosen appropriately. Robustness considerations tended to recommend the maximum likelihood method for both velocity and spectral estimation. Despite the restrictions of steady laminar flow, the results provide important basic information concerning the applicability of modern spectral analysis techniques to Doppler ultrasonic evaluation of arterial disease.

Algorithms↗
PubMed1999

Hepatic extraction fraction of hepatobiliary radiopharmaceuticals measured using spectral analysis.

Measuring the hepatic extraction fraction (HEF) of a hepatobiliary radiopharmaceutical helps to differentiate hepatocyte from biliary tract diseases, and it is generally performed using deconvolution analysis. In this study, we measured HEF using spectral analysis. With spectral analysis, HEF was calculated from (the sum of the spectral data obtained by spectral analysis--the highest frequency component of the spectrum) divided by (the sum of the spectral data) x 100 (%). We applied this method to dynamic liver scintigraphic data obtained from six healthy volunteers and from 46 patients with various liver diseases, using 99Tcm-N-pyridoxyl-5-methyltryptophan (PMT). We also measured HEF using deconvolution analysis, in which the modified Fourier transform technique was employed. The HEF values obtained by spectral analysis correlated closely with those obtained by deconvolution analysis (r = 0.925), suggesting our method is valid. The HEF values obtained by spectral analysis decreased as the severity of liver disease progressed. The values were 100.0 +/- 0.0%, 94.7 +/- 13.6%, 76.2 +/- 27.4%, 45.7 +/- 15.6%, 82.7 +/- 24.2% and 95.2 +/- 11.8% (mean +/- S.D.) for the normal controls (n = 6), mild liver cirrhosis (n = 16), moderate liver cirrhosis (n = 11), severe liver cirrhosis (n = 5), acute hepatitis (n = 8) and chronic hepatitis groups (n = 6), respectively. The HEF was obtained more simply and rapidly by spectral analysis than by deconvolution analysis. The results suggest that our method using spectral analysis can be used as an alternative to the conventional procedure using deconvolution analysis for measuring HEF.

Aged↗
PubMed1993

Effect of antihypertensive treatment on daytime and nighttime power spectral analysis of heart rate.

Power spectral analysis of heart rate may provide useful information about cardiac neural activity. The aim of this study was to evaluate cardiac sympathetic and parasympathetic activity, as assessed by power spectral analysis of heart rate, in hypertensive patients before and after antihypertensive treatment. In 14 hypertensive patients and in 7 normotensive subjects 24 h Holter electrocardiogram monitoring was performed under basal conditions and after 6 months of treatment with nifedipine (n = 7) or enalapril (n = 7). Sequences of 512 RR intervals were taken for the evaluation of power spectral analysis (autoregressive method); absolute and normalized power spectral density of the peak at 0.10 Hz (low frequency peak: LF) and at 0.25 Hz (high frequency peak: HF), as well as their ratio (index of sympatovagal interaction: SVI) were calculated. Under basal conditions SVI was significantly decreased from daytime to nighttime in normotensives, while no change was observed in hypertensive patients. In all hypertensive patients a reduction of SVI during nighttime in respect to basal values was observed after treatment. SVI during nighttime was significantly reduced with both nifedipine and enalapril, while SVI during daytime was slightly increased during nifedipine treatment, and significantly reduced during enalapril treatment. Systolic and diastolic arterial pressure as well as left ventricular mass index were significantly reduced with both treatments. In conclusion, long term treatment with nifedipine or enalapril seems to be able to restore an impaired daytime to nighttime SVI modulation in hypertensive patients, even considering the potential limitations of power spectral analysis of heart rate.

Adult↗
PubMed1989

EEG spectral analysis in delirium.

Spectral analysis of EEG was conducted for 51 elderly delirious patients meeting the Diagnostic and Statistical Manual of Mental Disorders III (DSM-III) criteria and for 19 controls. As a whole group, and also when subdivided according to the type of delirium, severity of cognitive decline or the type of central nervous system disease, delirious patients showed significant reductions of alpha percentage, increased theta and delta activity and slowing of the peak and mean frequencies and these changes were also obvious in individual recordings. The alpha percentage and various ratio parameters correlated significantly with Mini Mental State score, and delta percentage and mean frequency with the lengths of delirium and hospitalisation. The results indicate an association between spectral EEG changes and severity of cognitive deterioration in delirium.

Aged↗
PubMed1970

Epileptic focus location: spectral analysis method.

A spectral analysis technique for locating the site of an epileptic focus in the cat brain with the use of multielectrode data, obtained during a generalized seizure, is described. The data, indicating widespread appearance of epileptic activity, does not lend itself to conclusive analysis by conventional means. Three channels of data are examined at a time. One channel is said to drive the other channels if the first channel explains or accounts for the linear relation between the other two over a frequency interval corresponding to the interval of greatest energy concentration. The method of analysis involves computation of the coherence and partial coherence between data from all electrode pairs.

Animals↗
PubMed2000

Acoustic and airflow spectral analysis of voice tremor.

Acoustic spectral analysis has been used to describe voice tremor with some success, but no feature distinguishing pathological from normal tremor has been clearly identified. To assist in monitoring voice tremor associated with neurological diseases, objective and quantifiable measures that can distinguish between normal and pathological tremor are desired. This study explored the plausibility of using airflow and acoustic signals to quantify the frequency and amplitude of voice tremor and potentially to distinguish pathological from normal tremor. Subjects were 10 individuals with pathological tremor, most of them individuals with Parkinson's disease, and 10 gender and age-matched individuals with no voice disorder. Simultaneous acoustic and airflow signals were recorded during sustained vowel phonation. The acoustic intensity contours and the airflow signals were submitted to spectral analysis. A peak prominence ratio, defined as the ratio of the spectral peak energy to the overall signal energy, was calculated for each spectral peak below 30 Hz. For each subject, the 6 spectral peaks with the highest peak prominence ratios were selected. Frequency values of the 6 selected acoustic or airflow spectral peaks failed to distinguish tremor group from control group. Peak prominence ratios of the 6 selected acoustic spectral peaks were significantly higher for tremor group than for control group. Although spectral analysis of airflow signals was not useful in differentiating tremor group from control group, acoustic intensity contours and airflow time waveforms were highly and positively correlated in more tremor subjects (90%) than control subjects (40%). This finding suggests that the relationship between acoustic intensity contours and airflow time waveforms may reflect the presence and the source of voice tremor.

Adult↗
PubMed1998

Parametric image reconstruction using spectral analysis of PET projection data.

Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[11C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small (< 5%) and mainly affect parameters related to early and late time points on the impulse response function (K1 and, to a lesser extent, VD). The optimal number of EM iteration was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands.

Algorithms↗