Spectral analysis in cyclic changes of human sleep evaluation

In this study cyclic changes of human sleep structure were examined. For whole-night polysomnograms of 35 healthy volunteers of both sexes, manual hypnograms were created and divided into NREM-REM cycles. EEG signals from C3-A2 derivation were analysed by computer using a Fast Fourier Transform (FFT). For consecutive NREM-REM cycles of individual sleep stages, EEG power density contents for delta, theta, alpha, sigma and beta waves were analysed. For consecutive sleep cycles, a clear decrease in NREM sleep duration, especially slow wave sleep duration, was obtained. In addition, a decrease in power density of delta waves was observed. For consecutive sleep cycles, increases in REM sleep duration and in power density of theta and alpha waves were obtained. In consecutive sleep cycles, high amplitude delta slow waves are replaced by higher frequency and lower amplitude waves. Thus stages of NREM sleep are replaced by stages of REM.     

Practical model fitting approaches to the direct extraction of NMR parameters simultaneously from all dimensions of multidimensional NMR spectra

A maximum likelihood (ML)-based approach has been established for the direct extraction of NMR parameters (e.g., frequency, amplitude, phase, and decay rate) simultaneously from all dimensions of a D-dimensional NMR spectrum. The approach, referred to here as HTFD-ML (hybrid time frequency domain maximum likelihood), constructs a time-domain model composed of a sum of exponentially-decaying sinusoidal signals. The apodized Fourier transform of this time-domain signal is a model spectrum that represents the 'best-fit' to the equivalent frequency-domain data spectrum. The desired amplitude and frequency parameters can be extracted directly from the signal model constructed by the HTFD-ML algorithm. The HTFD-ML approach presented here, as embodied in the software package CHIFIT, is designed to meet the challenges posed by model fitting of D-dimensional NMR data sets, where each consists of many data points (10(8) is not uncommon) encoding information about numerous signals (up to 10(5) for a protein of moderate size) that exhibit spectral overlap. The suitability of the approach is demonstrated by its application to the concerted analysis of a series of ten 2D 1H-15N HSQC experiments measuring 15N T1 relaxation. In addition to demonstrating the practicality of performing maximum likelihood analysis on large, multidimensional NMR spectra, the results demonstrate that this parametric model-fitting approach provides more accurate amplitude and frequency estimates than those obtained from conventional peak-based analysis of the FT spectrum. The improved performance of the model fitting approach derives from its ability to take into account the simultaneous contributions of all signals in a crowded spectral region (deconvolution) as well as to incorporate prior knowledge in constructing models to fit the data.     

Estimation of pulmonary artery pressure by spectral analysis of the second heart sound

The objective of the present work was to test and validate a noninvasive method based on spectral analysis of the second heart sound (S2) to estimate the pulmonary artery (PA) systolic pressure in 89 patients with a bioprosthetic heart valve. The technique was compared with continuous-wave Doppler estimation of PA systolic pressure in these patients. The heart sounds recorded at the pulmonary area on the chest wall were digitized by computer. The spectra of S2 and those of the aortic (A2) and the pulmonary (P2) components of S2 were computed with a fast-Fourier transform. Seven features were extracted from these spectra. The statistical analysis performed with the Pearson linear correlation coefficient showed that the best estimation of PA systolic pressure obtained by spectral phonocardiography (r = 0.84, SEE +/- 5.6 mm Hg, p <0.0001) was provided by the following equation: PA systolic pressure = 47 + 0.68 Fp - 4.4 Qp - 17 Fp/Fa - 0.15 Fs, where Fs and Fp are dominant frequencies associated with the maximal amplitude of the power spectra of S2 and P2, respectively, Qp is the quality of resonance of P2, and Fp/Fa is the ratio of the dominant frequencies of P2 and A2, respectively.     

Selective discrete Fourier transform algorithm for time-frequency analysis: method and application on simulated and cardiovascular signals

The Selective Discrete Fourier transform (DFT) Algorithm [SDA] method for the calculation and display of time-frequency distribution has been developed and validated. For each time and frequency, the algorithm selects the shortest required trace length and calculates the corresponding spectral component by means of DFT. This approach can be extended to any cardiovascular related signal and provides time-dependent power spectra which are intuitively easy to consider, due to their close relation to the classical spectral analysis approach. The optimal parameters of the SDA for cardiovascular-like signals were chosen. The SDA perform standard spectral analysis on stationary simulated signals as well as reliably detect abrupt changes in the frequency content of nonstationary signals. The SDA applied during a stimulated respiration experiment, accurately detected the changes in the frequency location and amplitude of the respiratory peak in the heart rate (HR) spectrum. It also detected and quantified the expected increase in vagal tone during vagal stimuli. Furthermore, the HR time-dependent power spectrum displayed the increase in sympathetic activity and the vagal withdrawal on standing. Such transient changes in HR control would have been smeared out by standard heart rate variability (HRV), which requires consideration of long trace lengths. The SDA provides a reliable tool for the evaluation and quantification of the control exerted by the Central Nervous System, during clinical and experimental procedures resulting in nonstationary signals.     

Assessment of time-domain analyses for estimation of low-frequency respiratory mechanical properties and impedance spectra

Time-domain estimation has been invoked for tracking of respiratory mechanical properties using primarily a simple single-compartment model containing a series resistance (Rrs) and elastance (Ers). However, owing to the viscoelastic properties of respiratory tissues, Rrs and Ers exhibit frequency dependence below 2 Hz. The goal of this study was to investigate the bias and statistical accuracy of various time-domain approaches with respect to model properties, as well as the estimated impedance spectra. Particular emphasis was placed on establishing the tracking capability using a standard step ventilation. A simulation study compared continuous-time versus discrete-time approaches for both the single-compartment and two-compartment models. Data were acquired in four healthy humans and two dogs before and after induced severe pulmonary edema while applying sinusoidal and standard ventilator forcing. Rrs and Ers were estimated either by the standard Fast Fourier Transform (FFT) approach or by a time-domain least square estimation. Results show that the continuous-time model form produced the least bias and smallest parameter uncertainty for a single-compartment analysis and is quite amenable for reliable on-line tracking. The discrete-time approach exhibits large uncertainty and bias, particularly with increasing noise in the flow data. In humans, the time-domain approach produced smooth estimates of Rrs and Ers spectra, but they were statistically unreliable at the lower frequencies. In dogs, both the FFT and time-domain analysis produced reliable and stable estimates for Rrs or Ers spectra for frequencies out to 2 Hz in all conditions. Nevertheless, obtaining stable on-line parameter estimates for the two-compartment viscoelastic models remained difficult. We conclude that time-domain analysis of respiratory mechanics should invoke a continuous-time model form.     

Power spectral density of unevenly sampled data by least-square analysis: performance and application to heart rate signals

This work studies the frequency behavior of a least-square method to estimate the power spectral density of unevenly sampled signals. When the uneven sampling can be modeled as uniform sampling plus a stationary random deviation, this spectrum results in a periodic repetition of the original continuous time spectrum at the mean Nyquist frequency, with a low-pass effect affecting upper frequency bands that depends on the sampling dispersion. If the dispersion is small compared with the mean sampling period, the estimation at the base band is unbiased with practically no dispersion. When uneven sampling is modeled by a deterministic sinusoidal variation respect to the uniform sampling the obtained results are in agreement with those obtained for small random deviation. This approximation is usually well satisfied in signals like heart rate (HR) series. The theoretically predicted performance has been tested and corroborated with simulated and real HR signals. The Lomb method has been compared with the classical power spectral density (PSD) estimators that include resampling to get uniform sampling. We have found that the Lomb method avoids the major problem of classical methods: the low-pass effect of the resampling. Also only frequencies up to the mean Nyquist frequency should be considered (lower than 0.5 Hz if the HR is lower than 60 bpm). We conclude that for PSD estimation of unevenly sampled signals the Lomb method is more suitable than fast Fourier transform or autoregressive estimate with linear or cubic interpolation. In extreme situations (low-HR or high-frequency components) the Lomb estimate still introduces high-frequency contamination that suggest further studies of superior performance interpolators. In the case of HR signals we have also marked the convenience of selecting a stationary heart rate period to carry out a heart rate variability analysis.     

Valve diseases in the aged: when to operate?]

BACKGROUND: Patients with Raynaud's phenomenon due to systemic sclerosis exhibit a functional microangiopathy with endothelial cell damage. The aim of this study was to assess differences in the so-called nutritive and thermoregulative skin blood flow and to obtain further information by Fourier transformation and by nonlinear analysis of laser Doppler flux (LDF) time series. PATIENTS AND METHODS: A local cold stress test was performed in 10 patients and 10 age- and sex-matched healthy controls. Significant differences were detected between nutritive blood flow in the nailfold capillaries, assessed by capillary red blood cell velocity (CBV), and thermoregulatory blood flow, which was synchronously assessed by LDF. RESULTS: CBV was reduced during cooling, the drop being significantly larger in the patients than in the controls. In contrast, there was no significant difference in the decrease of LDF during cooling. The difference between the fall in CBV values and that in LDF was significantly more pronounced in patients. Further analysis of the LDF frequency spectrum by fast Fourier transformation revealed a significantly greater decrease in amplitude at the heart frequency level in healthy volunteers. A further analysis of the LDF signal revealed significant differences at rest and after cooling in fractal dimensions, suggesting an increased complexity of LDF signals in patients. SUMMARY: The patient's increased sensitivity towards local cold cn be observed best at the capillary level. But the changes of LDF in the frequency spectrum during cooling as calculated by fast Fourier transformation revealed significant differences. In addition differences in fractal dimensions of LDF time series suggest that an analysis of nonlinear dynamics may be a promising approach.     

Response Spectrum Analysis of Suspension Bridges for Random Ground Motion

The response spectrum method of analysis for suspension bridges subjected to multicomponent, partially correlated stationary ground motion is presented. The analysis is based on the relationship between the power spectral density function and the response spectrum of the input ground motion and fundamentals of the frequency domain spectral analysis. The analysis duly takes into account the spatial correlation of ground motions between the supports, the quasi-static component of the response, and the modal correlation between different modes of vibration. A suspension bridge is analyzed under a set of important parametric variations in order to (1) compare between the responses obtained by the response spectrum method of analysis and the frequency domain spectral analysis; and (2) investigate the behavior of suspension bridges under seismic excitation. The parameters include the spatial correlation of ground motion, the angle of incidence of the earthquake, the ratio between the three components of ground motion, the number and nature of modes considered in the analysis, and the nature of the power spectral density function of ground motion. It is shown that the response spectrum method of analysis provides a fair estimate of responses under parametric variations considered in the study.     

Increased expression of CD11b/CD18 on phagocytes in ischaemic disease: a bridge between inflammation and coagulation

The aim of this study was to assess the expression of CD11b/CD18 integrin adhesion molecules on the phagocytes of patients with ischaemic diseases, and to evaluate the concentration of soluble adhesion molecules that are released from endothelium (sICAM-1) and from phagocytes (sL-selectin). A total of 370 patients were enrolled: 120 with coronary artery disease (CAD); 50 with peripheral artery occlusive disease (PAOD); and 200 control subjects with no clinical manifestations of ischaemic disease. CD11b/CD18 integrin was detected by flow cytometry, whereas sL-selectin and sICAM-1 concentrations were detected using a sandwich-type immunoassay. CD11b/CD18 integrin expression was found to be higher in the patients with ischaemic disease than in the control subjects (P < 0.001). The PAOD patients had higher values of CD11b/CD18 integrin than the CAD ones (P < 0.01). The concentration of soluble adhesion molecules did not show any significant differences within the three groups (P = NS). The high expression of CD11b/CD18 integrin in ischaemic disease patients may depend on the increased, but probably stable, cytokine network that has been demonstrated to occur in chronic ischaemic diseases: the difference observed between PAOD and CAD patients could be the consequence of higher inflammatory activation probably resulting from the greater extent of the atherosclerotic process in PAOD, or of the more localized ischaemic area in CAD patients. CD11b/CD18 can therefore be considered a marker of chronic phagocyte activation during ischaemic disease. On the other hand, sICAM and sL-selectin concentrations were found to be within the normal range; they have recently been considered as a marker for acute ischaemic events and acute inflammatory process activation. Our results confirm that in uncomplicated atherosclerosis no acute inflammatory process activation should occur.     

Dynamics of the effects of levoprotiline and maprotiline on EEG in patients with major depressive episodes (DSM-III-R)

The presented study compares the effect of the well-tested antidepressant maprotiline and a new antidepressant with an atypical pharmacological profile, levoprotiline, on EEG during repeated assessment after single dose administration. From the original number of 34 patients fulfilling the criteria of a major depressive episode (DSM-III-R) on account of a low-voltage record or pathological findings 11 were eliminated. To 12 of the remaining patients levoprotiline was administered and to 11 maprotiline, after a one-week placebo period, in doses of 150 mg. The EEG was recorded after an accommodation session immediately before, 1.5, 3, 4.5, 6 and 24 hours after a single dose administration. The record was taken on a 16-channel average reference montage at rest with closed eyes. Two-minute intervals were divided into 30 four-second periods at a sampling frequency of 128 Hz. From the signal by means of FFT the spectra were estimated and the mean spectrum for the entire recording was calculated. This was then divided into 10 frequency bands. The new method of frequency analysis of alpha-entropy was also used which is a global measure of the difference between two spectra. Three hours after administration of a single dose levoprotiline had an EEG profile corresponding to the profile of tricyclic antidepressants, i.e. it increased the values of the power spectra density in the region of 5-8.5 Hz and in the entire beta band; the decline of power in the alpha band was, however, absent. As regards maprotiline, 3 hours after administration a profile typical for antidepressants was not found; obviously because of the great variance of values of power spectra density as a result of great interindividual differences in the ingestion phase. Changes of the EEG spectrum expressed as values of alpha-entropy during different periods of apparently assessment are not incidental. After the initial rise of values a decline occurs.     

Binding of nitric oxide to intact human erythrocytes as monitored by electron paramagnetic resonance

Human blood was diluted in isotonic saline at pH 7.4 and deoxygenated. After gentle exposure to nitric oxide gas (NO), the red blood cells (erythrocytes) remained intact. Increasing the cell volume fraction allowed detection of strong electron paramagnetic (EPR) signals, even at ambient temperature (293 K). These spectra were compared to those recorded at 77 K. With maximal NO exposure, a relatively featureless and stable spectrum was recorded. Reduced exposure produced a spectrum, which gradually transformed into the final one, with more structure. The spectral features with unfrozen samples reflected the degree of resolution of the hyperfine triplet component observed at 77 K. This hyperfine coupling was independent of the temperature. The spectra reveal rearrangement of the NO ligand between the subunits of hemoglobin. At subsaturation levels, binding to the alpha subunit, with its iron pentacoordinated in the T-state, dominates.     

Hilbert-Huang Transform Analysis of Dynamic and Earthquake Motion Recordings

This study examines the rationale of Hilbert-Huang transform (HHT) for analyzing dynamic and earthquake motion recordings in studies of seismology and engineering. In particular, this paper first provides the fundamentals of the HHT method, which consist of the empirical mode decomposition (EMD) and the Hilbert spectral analysis. It then uses the HHT to analyze recordings of hypothetical and real wave motion, the results of which are compared with the results obtained by the Fourier data processing technique. The analysis of the two recordings indicates that the HHT method is able to extract some motion characteristics useful in studies of seismology and engineering, which might not be exposed effectively and efficiently by Fourier data processing technique. Specifically, the study indicates that the decomposed components in EMD of HHT, namely, the intrinsic mode function (IMF) components, contain observable, physical information inherent to the original data. It also shows that the grouped IMF components, namely, the EMD-based low- and high-frequency components, can faithfully capture low-frequency pulse-like as well as high-frequency wave signals. Finally, the study illustrates that the HHT-based Hilbert spectra are able to reveal the temporal-frequency energy distribution for motion recordings precisely and clearly.     

Systemic and fetal-maternal nitric oxide synthesis in normal pregnancy and pre-eclampsia

Quantitatively estimating functional reserve of blood supply to the legs in patients with peripheral arterial occlusive disease (PAOD) remains a clinical issue. This study was designed to investigate the regional blood supply to the legs in PAOD patients during exercise by use of thallium 201 (201Tl) whole-body imaging in comparison with transcutaneous PO2 (tcPO2) measurement. Thirty-three patients with PAOD and 10 subjects without PAOD (control) performed an incremental cycle ergometry (CE), while tcPO2 was continuously registered on the involved calf. In the last minute of exercise, 2 mCi of 201Tl was injected intravenously and the 201Tl whole-body images were taken immediately (stress) and four hours (redistribution) following stress with a dual-head camera system. Regional blood supply (RBS) (%) was calculated from the geometric mean counts of the region of interest divided by the total counts of the whole body. The performance of PAOD patients was reduced in doing CE, and tcPO2 fell distinctly in PAOD patients (from 51 to 19 mmHg) whereas it increased in controls (from 57 to 67 mmHg). The RBS in PAOD patients was obviously reduced in comparison with that of controls. While in controls the RBS of the calf (3.1%) at stress did not differ from that at redistribution (3.4%), in PAOD patients the redistribution RBS (2.8%) increased as compared with that of stress (1.5%). There was a hyperbolic relationship between stress RBS of the calf and the velocity of tcPO2 fall in PAOD patients during exercise test (velocity of tcPO2 fall = -0.032 + 0.39/RBS, r2 = 0.54, P < 0.05). In conclusion, the RBS determined by 201Tl whole-body imaging is comparable to the tcPO2 measurement in differentiating patients with PAOD from subjects without PAOD during exercise. Regional 201Tl uptake reflects regional blood supply in PAOD patients. There is a hyperbolic relationship between the RBS derived from 201Tl whole-body imaging and tcPO2 in PAOD patients during exercise, implying that in a critical ischemia the lower the RBS is, the more steeply the tcPO2 decreases.     

Basilar membrane vibration in the gerbil hemicochlea

Excised gerbil cochleae were cut along the mid-modiolar plane (hemicochlea). Along one-half turn of this preparation, fluorescent microbeads were placed on the basilar membrane (BM). The BM was vibrated with click stimuli (50 micros) produced mechanically by a piezo pusher. The stimulus delivery probe could be positioned either more apical or more basal from the beads. Vibration patterns were measured with a wide bandwidth photomultiplier from the movements of the beads. When the probe was positioned more basal, the responses to click stimuli were brief, damped sinusoids. According to the fast Fourier transforms (FFTs) of the averaged time wave forms, the best frequency between successive beads decreased toward the apex (0.8 octave/mm). Sharpness of tuning of the normalized FFT spectra (NQ10dB) on average was 1.5. Response amplitude at a fixed input level, measured at different beads away from the stimulation site, dropped exponentially (58 dB/mm). In addition, for each individual bead, amplitude dropped linearly with decreasing stimulus intensity. In experiments where the stimulating probe was placed more apical, two major properties were observed: first, beads revealed only the spectral components present in the motion of the probe. Second, magnitude reduction of the displacement of the cochlear partition was greater, on average 155 dB/mm, indicating a lack of significant propagation in the reverse direction.     

一种PWM整流器虚拟磁链矢量重构方法

电压型脉宽调制(pulse width modulation,PWM)整流器的虚拟磁链矢量可以由电网电压矢量进行积分得到,实际中常用一阶低通滤波器代替纯积分环节来消除直流偏置误差和抑制高频次谐波干扰,但一阶低通滤波器的引入也会带来电网电压幅值衰减和相移,从而导致虚拟磁链观测不准确.为消除一阶低通滤波器对虚拟磁链观测的影响,本文提出一种基于矢量重构技术的观测方法,通过分析一阶低通滤波器的幅频特性和相频特性,分别对滤波后的电压矢量幅值和相位进行重构,可实现虚拟磁链幅值和相位的精确估算.该方法应用于虚拟磁链定向的电压型脉宽调制整流器直接功率控制系统.仿真和实验结果表明,与传统的一阶低通滤波器策略相比,该方法提高了虚拟磁链的估计精度,有效抑制了直流母线电压动态响应波动,更有利于滤除网侧电流谐波.     

Rhythms in the central nervous system and 1/f fluctuations of the heart rate

We have developed a system to analyze heart rate variability (HRV) (power spectral array of the HRV) during 24 h ambulatory electrocardiographic monitoring. Several rhythms (circadian and several ultradian rhythms) were observed in the power spectral array of the heart rates and 1/f-like fluctuations in the log-log scaled heart rate power spectrum. The circadian change of the heart rate is closely related to the body temperature rhythm. The 90 min rhythm of HRV during sleep was suspected to be produced by the sleep cycle (REM/NREM) and the lower frequency peak of the HRV was coherent with oscillation in amplitude modulated respiration. These circadian and ultradian rhythm as assessed by heart rate variability exist both in normal subjects and in patients with autonomic failure. The power of the high frequency band decreases in subjects with autonomic failure. The power of low frequency components increases during periodic breathing or Cheyne-Stokes respiration. Log-log scaled analysis of the power spectrum of HRV disclosed that the slope of the HRV is markedly modulated by the range of the frequency applied for the least square regression line analysis. The increased power that might be produced by periodic breathing and decreased power in patients with autonomic failure might strongly modulate the slope of the log-log scaled HRV. It is concluded that the power spectral array of the HRV during 24 h period is useful in the detection of circadian and ultradian rhythm, and log-log scaled power spectra might be useful in the overall integration of the heart rate dynamics produced by the central nervous system. The several rhythm factors that might be produced by the central nervous system might modulate 1/f fluctuations of the HRV.     

Spectral characteristics of skin temperature indicate peripheral stress-response

High-resolution measurement of skin temperature in 11 normal subjects revealed low-amplitude temperature oscillations (40 x 10(-3) degrees C). The temperature signal measured on two hands during baseline, stress, and recovery periods, was filtered to separate the low-amplitude oscillations from the temperature signal. Spectral analysis of the filtered signal showed that most of the energy of the signal is in a range of 0.01 to 0.03 Hz. Frequency shifts and amplitude changes of the largest component were observed in response to mental stress. In subjects with high baseline values of either of these two variables, a decrease was observed in response to stress. An opposite response was observed in subjects with significantly lower baseline levels. Stress-related changes in peak frequency ranged from -25% to +18.2%; changes in peak amplitude ranged from -74.6% to +280%. Changes in the mean temperature were limited to 2.4%. Thus, the oscillatory component showed higher sensitivity to psychological stress than mean temperature. The spectrum of this component was compared to the spectrum of the blood pressure waves measured noninvasively. Both exhibited similar dynamics of energy, peak amplitude, and peak frequency in response to psychological stress. This similarity suggests that the oscillatory temperature component reflects stress-related changes of peripheral vasomotor activity.     

Power spectra accuracy improvement by optimal signal epoch selection: an heuristic approach

The problem of epoch selection in frequency analysis of biomedical signals often involves tradeoffs between the physiological system studied stationarity, the spectral resolution required, the need for dynamic investigations implying shorter epochs, etc. The accuracy of the spectra strongly depends on the epoch length. We propose a method for optimal epoch selection introducing the notion of 'quality of power spectra'. Two criteria for quantitative estimation of spectral quality are defined, considering a quality to be high when more power is concentrated in narrow frequency bands. A synthesized signal is used for describing the procedure developed and evaluating the accuracy. Noise sensitivity is assessed by adding intensive noise to the signal. Hundreds of synthesized signals are used for validation of the method and some initial experiments with heart rate variation data are presented.     

Spectral analysis of heart period variance (HPV)--a tool to stratify risk following myocardial infarction

The purpose of this study was to contribute to the improvement of stratification of post-myocardial infarction patients at increased risk of malignant ventricular arrhythmia (MVA). Power spectral analysis of heart period variability (HPV) was used as a non-invasive tool to assess cardiac autonomic control. Three groups were used: (1) post-myocardial infarction patients with MVA; (2) post-myocardial infarction patients without MVA; and (3) a control group without heart disease. Spectral analysis of HPV (AR model) was performed on four minute long RR-interval time series derived from consecutive hours of Holter ECG. Significant decrease of powers of mid-frequency (MF) (70-150 mHz) and high-frequency (HF) (150-450 mHz) spectral components of HPV was obtained in Group 1 as compared to Group 2 (p = 0.001 and p = 0.02, respectively). There were no significant differences between groups concerning the power of low frequency (LF) (10-70 mHz) component HPV, spectra of patients in Group 1 were dominated by a single low frequency spectral peak (with a central frequency of 37 mHz). The relative power was computed as the percentage of power in each of the above (HF, MF, LF) components related to the total spectral power. Highly significant differences (p = 0.04) were obtained between Group 1 and Group 2 concerning relative powers of MF and LF components as well as LF/MF ratio. The above method appeared to be highly sensitive in differentiating patients with increased risk of MVA.