Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Spectral estimation”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9Linked to original sources
PubMed1996

Neuromagnetic study of movement-related changes in rhythmic brain activity.

Neuromagnetic fields from the left cerebral hemisphere of five healthy, right-handed subjects were investigated in a typical Bereitschaftspotential paradigm consisting of self-paced voluntary movement of the right index finger. To assess movement-related spectral changes of the spontaneous magnetoencephalogram. latency-dependent short-time spectra were obtained by Fourier analysis for each single trial. The number of trials in which the spectral estimate for a certain frequency and latency deviated from reference values was then transformed into a probabilistic relative power measure. A spectral power depression around 20 Hz was observed starting about 2.5 s before movement onset, followed by elevated power in the 20-35 Hz range starting about 500 ms after movement onset. Generally, the power increase differed from the prior depression in both spectrum and topography, suggesting different generating processes rather than just a 'rebound' effect of the idling rhythm generator. The time course and topography of spectral power changes are discussed in relation to the corresponding properties of the movement-related neuromagnetic fields (readiness field, motor field, and movement-evoked field I).

Adult↗
PubMed2000

A chemometric approach to the estimation of the absorption spectra of dye probe merocyanine 540 in aqueous and phospholipid environments.

Merocyanine 540 (MC540) is a widely used dye probe for membranous environments. However, fundamental knowledge of the spectral features of this dye in aqueous and hydrophobic environments is still lacking. Such knowledge is important because biomembranes involve a hydrophobic environment surrounded by a hydrophilic environment. Because many investigations so far have been performed based on indistinct spectral estimations, the interpretation of the data obtained using this dye as a fluorescent transmembrane probe remains controversial. In order to determine the exact spectra in both aqueous and hydrophobic environments, we adopted principal factor analysis (PFA), a method of multivariate analysis. The PFA method can also determine the number of molecular species present in the reaction mixture, which is three in pure water and two in phospholipid suspension. Two of the species in both water and phospholipid suspension were the monomer and dimer. The third species in water was the trimer, but its amount was so small at 10 microM MC540 solution that the spectral data in water can be approximated neglecting this molecular species. The monomer spectrum changed its form markedly with a bathochromic shift when transferred from the water to phospholipid environment, whereas the dimer remained similar in its shape except for a remarkable red shift. In water, the dissociation constants, K(1) and K(2), for the assumed stacking-model reactions, M+M <--> M(2) and M+M(2) <--> M(3), were 3.1 x 10(-4) M and 5.7 x 10(-4) M, respectively. In the phospholipid environment, the dissociation constant K* for the assumed stacking-model reaction, M(*)+M(*) <--> *M(2), was 1.9x10(-5)M. The fluorescent intensities of MC540 were also measured in both water and phospholipid environments. A comparison based on the absorption and fluorescence spectra suggested that the temporal increase in the amount of the monomer on the excitable membrane contributes to the fluorescent intensity change observed in the transmembrane potential change.

Fluorescent Dyes↗
PubMed2004

Automatic correction of ocular artifacts in the EEG: a comparison of regression-based and component-based methods.

A variety of procedures have been proposed to correct ocular artifacts in the electroencephalogram (EEG), including methods based on regression, principal components analysis (PCA) and independent component analysis (ICA). The current study compared these three methods, and it evaluated a modified regression approach using Bayesian adaptive regression splines to filter the electrooculogram (EOG) before computing correction factors. We applied each artifact correction procedure to real and simulated EEG data of varying epoch lengths and then quantified the impact of correction on spectral parameters of the EEG. We found that the adaptive filter improved regression-based artifact correction. An automated PCA method effectively reduced ocular artifacts and resulted in minimal spectral distortion, whereas ICA correction appeared to distort power between 5 and 20 Hz. In general, reducing the epoch length improved the accuracy of estimating spectral power in the alpha (7.5-12.5 Hz) and beta (12.5-19.5 Hz) bands, but it worsened the accuracy for power in the theta (3.5-7.5 Hz) band and distorted time domain features. Results supported the use of regression-based and PCA-based ocular artifact correction and suggested a need for further studies examining possible spectral distortion from ICA-based correction procedures.

Adult↗
PubMed1998

Optical design of the U7 undulator beamline at the Pohang Light Source.

The first insertion-device beamline at the Pohang Light Source is designed for high-resolution spectroscopy and spectromicroscopy. The beamline will contain a variable-included-angle plane-grating monochromator (VIA-PGM) using a grating substrate which has seven different grooves with different depths. The advantages of this scheme will be the fixed exit-slit position and the mechanical stability of the grating scan mechanism while changing the photon energy range. The beamline is designed to cover the photon energy range 20-2000 eV. The estimated spectral resolution, E/DeltaE, is above 8000 in the photon energy range below 500 eV, and above 4000 for the remaining photon energy range. The estimated flux at the end-station is of the order of 10(12) photons s(-1) (0.1% bandwidth)(-1).

Journal Article↗
PubMed1987

Secretory pattern of canine growth hormone.

Our aim was to define the secretory pattern of growth hormone (GH) under basal conditions in fasted, conscious, male dogs accustomed to handling. Blood samples were withdrawn from a cephalic vein at 15-min intervals. In this way, any ultradian rhythms, if present, could be detected within the frequency range of 0.042-2 cycles/h. In addition, samples were drawn at either 1- or 2.5-min intervals for 2.5 or 5 h to determine whether frequency components greater than 2 cycles/h were present. GH was measured by radioimmunoassay and the raw data were submitted to time series analysis employing power spectral estimation by means of fast Fourier transformation techniques. Peak plasma levels were up to 12 times higher than the baseline concentration of approximately 1 ng/ml. Spectral analysis revealed an endogenous frequency of 0.22 cycles/h, i.e., a periodicity of 4.5 h/cycle. The results indicate that under basal conditions the secretory bursts of canine GH are limited to one peak every 4.5 h.

Animals↗
PubMed1999

Instantaneous postural stability characterization using time-frequency analysis.

Postural stability assessment is critical to a more accurate understanding of sway and balance control. The center of pressure (COP) metric has been shown to be a suitable output measure for time and frequency analysis. However, the center of pressure is a non-stationary signal. Standard time and frequency analysis methods may not be adequate for monitoring the dynamic changes in the center of pressure signal. In this study a time-frequency method, based on data-adaptive evolutionary spectral estimation, is applied to monitor the dynamic changes of the center of pressure in a non-stationary environment. Metrics including the instantaneous mean frequency (IMF), instantaneous spectral bandwidth (ISB), and instantaneous average power (IAP) are analyzed to characterize the center of pressure signal in both the anterior-posterior (AP) and the medial-lateral (ML) planes. Within the confines of this study, the IMF was found to be inversely proportional to IAP. The inverse proportionality factors were calculated in both eyes-open and eyes-closed trials during upright quiet standing. These findings suggest that the time-frequency analysis provides instantaneous metrics which describe the amplitude changes and frequency shift of the center of pressure under a variety of environmental conditions, thus providing a more reliable quantification of postural control.

Adult↗
PubMed2005

Multispectral synthesis of daylight using a commercial digital CCD camera.

Performance of multispectral devices in recovering spectral data has been intensively investigated in some applications, as in spectral characterization of art paintings, but has received little attention in the context of spectral characterization of natural illumination. This study investigated the quality of the spectral estimation of daylight-type illuminants using a commercial digital CCD camera and a set of broadband colored filters. Several recovery algorithms that did not need information about spectral sensitivities of the camera sensors nor eigenvectors to describe the spectra were tested. Tests were carried out both with virtual data, using simulated camera responses, and real data obtained from real measurements. It was found that it is possible to recover daylight spectra with high spectral and colorimetric accuracy with a reduced number of three to nine spectral bands.

Journal Article↗
PubMed1987

Strategies for the representation of a tone in background noise in the temporal aspects of the discharge patterns of auditory-nerve fibers.

The responses of populations of auditory-nerve fibers to both a 1.0-kHz tone, and 1.0-kHz tone in broadband noise, have been measured. Period histograms were generated from fiber spike trains and discrete Fourier transforms (DFTs) with a resolution of 125 Hz were computed from each histogram. Sample mean and sample variance statistics were generated for period histograms of response and for temporal response measures derived from discrete Fourier transforms. It is demonstrated how the statistical properties of auditory-nerve fiber response determine the strategy for the estimation and discrimination of particular stimulus components. When the tone is presented alone, the entire population of auditory-nerve fibers provides statistically reliable estimates of the 1.0-kHz tone. Upon addition of the broadband noise stimulus only those units with characteristic frequencies which are close in frequency to the 1.0-kHz stimulus provide spectral estimates which have high signal-to-noise ratios (mean-squared-to-variance ratios). Estimates of the 1.0-kHz-tone stimulus derived from auditory-nerve fibers with characteristic frequencies which are far from the 1.0-kHz stimulus are statistically unreliable. Based on the responses of the population of auditory-nerve fibers, the strategy for estimating the 1.0-kHz-tone stimulus is to derive estimates of the 1.0-kHz stimulus from the subpopulation of neurons with characteristic frequencies close to the 1.0-kHz stimulus. It is concluded that neurons which are tuned close to 1.0-kHz provide the central nervous system (CNS) with the most salient information about the 1.0-kHz stimulus in the presence of the broadband background.

Analysis of Variance↗
PubMedDate not supplied

Characteristics of fricatives and sentence duration after cochlear implantation.

Ten postlingually deafened patients (5 male, 5 female) were examined after cochlear implantation to measure improvements in their quality of speech. Parameters such as the spectral maximum of fricatives and the duration of utterances were analysed in speech recordings taken at regular intervals after implantation. The speech samples were recorded in an audiological chamber. Parameters were analysed using ST(x) (S-Tools Software). Frequency analyses based on the fast Fourier transform and spectral estimation methods, as well as fundamental frequency and formant extraction (cepstrum, LPC = linear prediction coding) and digital filter implementations were prepared. The results indicate a tendency towards improvement in the spectral maximum of the fricatives and affricates and a shortening of the duration of the fricative parts in affricates and of sentences in nearly all our subjects. These results showed the restored auditory feedback produced by cochlear implantation to have a favourable effect on speech production.

Adolescent↗
PubMed1993

Low-frequency respiratory mechanics using ventilator-driven forced oscillations.

We evaluated the potential for using a fast Fourier transform (FFT) analysis applied to a standard ventilator waveform to estimate (< 2 Hz) frequency dependence of respiratory or lung resistance (R) and elastance (E). In four healthy humans we measured pressure and flow at the airway opening while applying sine wave forcing from 0.2 to 0.6 Hz at two tidal volumes (VT; 250 and 500 ml). We then applied a step inspiratory ventilator flow wave with relaxed expiration at the same VT and only 0.2 Hz. Step waveform data were also acquired from nine mechanically ventilated patients under intensive care unit conditions. Finally, we simultaneously measured total respiratory (rs), lung (L), and chest wall (cw) impedance data from two dogs (0.156-2 Hz) before and after severe pulmonary edema. Rrs and Ers were estimated by the FFT approach. Humans displayed a small frequency dependence in Rrs and Ers from 0.2 to 0.6 Hz, and both Rrs and Ers decreased at the higher VT. The spectral estimates of Rrs and Ers with the step ventilator wave were often qualitatively comparable to sine wave results below 0.6 Hz but became extremely erratic above the third harmonic. Conversely, in dogs the step wave produced reliable and stable estimates up to 2 Hz in all conditions. Nevertheless, Ecw and Ers still displayed clear and correlated oscillations with increasing frequency, whereas EL showed none. This suggests that nonlinear processes, most likely at the chest wall, contribute to periodic-like fluctuations in respiratory mechanical properties when estimated by applying FFT to a step ventilator wave. Moreover, in humans, but not dogs, a ventilator flow cycle contains insufficient signal energy beyond the third harmonic. We show that the amount of energy available at higher frequencies is largely governed by the mechanical time constant contributing to passive expiratory flow. In dogs the shorter time constant contributes to increased energy. In essence, the frequency content of the flow is subject dependent, and this is not a desirable situation for controlling the quality of the impedance spectra available from a standard ventilator wave.

Adult↗
PubMedDate not supplied

Time series versus Fourier transform methods for estimation of respiratory impedance spectra.

Most current techniques to estimate respiratory system mechanical input impedance spectra (Zrs) use digitally created (Fourier transform (FFT) based) random noise. Recent Zrs data reported from 0.1-4 Hz and above 32 Hz display sharper, more distinct spectral features. When expressing Zrs as a power spectral density (PSD), such features suggest the application of a time series spectral estimation approach. Here, a simulation study was performed to compare the quality of impedance (PSD and Zrs) estimates from the time series technique to those from the FFT approach in the presence of measurement noise. Random noise pressure and flow time domain sequences were simulated for two different networks, one which exhibits impedance features reported from 0.1-4 Hz and one which exhibits impedance features reported above 32 Hz. In the time series method, autoregressive (AR), moving average (MA), and autoregressive-moving average (ARMA) models were fit to the pressure and flow sequences separately. The estimated PSD and complex Zrs spectra were compared to the true spectra calculated from the models. Results show that the time series PSD estimates were reasonable even in the presence of additive measurement noise. Conversely, with additive noise, the time series estimates of the complex Zrs showed a negative real part which is physiologically inappropriate. This occurs because of the loss of phase information inherent to the time series approach. Regardless of measurement noise, the FFT estimates of impedance were always close to the true impedance and always superior to the time series estimates. We conclude that an accurate estimate of the PSD or complex Zrs spectra from digitally created FFT-based random noise is best obtained using the traditional FFT method.

Airway Resistance↗
PubMed2004

Segmenting cardiac-related data using sleep stages increases separation between normal subjects and apnoeic patients.

Inter-patient comparisons of cardiovascular metrics indicative of patient health have been shown to be successful in differentiating patients on a group rather than an individual level. This is in part due to the range of mental (as well as physical) activity-based variations for each patient and the difficulty assessing physical and mental activity during conscious states. In order to provide an objective scale for measuring central nervous system activity during sleep, the heart rate (RR) interval time series is divided into coarse sleep stage segments in which the LF/HF-ratio (the relative balance between low and high frequency power) is estimated for age and sex-matched populations of apnoeic and healthy subjects. Activity-based noise is therefore reduced and a more useful comparison of heart rate variability can be made. Additionally, the spectral estimation performances of the FFT and the Lomb-Scargle periodogram (LSP), a Fourier-based technique for unevenly sampled time series are compared. Separation of patients according to condition is shown to be more pronounced when using the LSP than the FFT. Furthermore, separation is found to be most marked in slow wave sleep.

Adult↗
PubMed1985

Reduced-order autoregressive modeling for center-frequency estimation.

The center frequency of a narrowband, discrete-time random process, such as a reflected ultrasound signal, is estimated from the parameter values of a reduced, second-order autoregressive (AR) model. This approach is proposed as a fast estimator that performs better than the zero-crossing count estimate for determining the center-frequency location. The parameter values are obtained through a linear prediction analysis on the correlated random process, which in this case is identical to the maximum entropy method for spectral estimation. The frequency of the maximum of the second-order model spectrum is determined from these parameters and is used as the center-frequency estimate. This estimate can be computed very efficiently, requiring only the estimates of the first three terms of the process autocorrelation function. The bias and variance properties of this estimator are determined for a random process having a Gaussian-shaped spectrum and compared to those of the ideal FM frequency discriminator, zero-crossing count estimator and a correlation estimator. It is found that the variance values for the reduced-order AR model center-frequency estimator lie between those for the ideal FM frequency discriminator and the zero-crossing count estimator.

Computers↗
PubMed1994

Real-time digital processing of Doppler ultrasound signals and calculation of flow parameters.

Vascular diseases and their complications are responsible for around 27% of deaths in Brazil. Doppler ultrasound is a non-invasive technique that has been used to study blood flow in intact blood vessels since Satomura first reported the potential of the technique in 1959. Because it is non-invasive it makes sequential studies and those in normals feasible. Whereas in contrast angiography only vessel anatomy is displayed, Doppler ultrasound produces dynamic information on blood-flow. It may be used to estimate flow-rates, to image regions of blood flow (colour Doppler), and to help in locating sites of arterial disease, thus complementing X-ray examinations. This paper describes a system based on a Digital Signal Processor for real-time spectrum analysis of Doppler ultrasound signals, real-time display of sonograms, and calculation and analysis of three parameters of clinical interest derived from the Doppler signal. The system comprises a TMS320C25 development board, which acquires the signal and performs spectrum analysis, and a microcomputer, which reads the spectral estimates, displays them as a sonogram in real-time and calculates a set of spectral parameters proposed in the literature. The system permits a maximum sampling frequency of 40.96 kHz, and in the sonogram, 80 power spectra per second (each with 128 frequency bins) are displayed. In a preliminary study, the stability of the haemodynamic parameters and their dependence on a user-defined threshold value is investigated.

Algorithms↗
PubMed1984

Detection of periodic signals in noise: an iterative procedure.

A method for detection and estimation of periodic signals in the presence of noise is described. The algorithm is an iterative improvement of the autoregressive-moving average estimation of a stochastic process and gives an exact frequency resolution of sinusoidal signals additively mixed with noise in a low signal-to-noise ratio only from a small number of measurements. The iterative improvement of the spectral estimation compared with other methods is demonstrated by examples.

Computers↗
PubMed2001

The short-time Fourier transform and muscle fatigue assessment in dynamic contractions.

The mean frequency of the power spectrum of an electromyographic signal is an accepted index for monitoring fatigue in static contractions. There is however, indication that it may be a useful index even in dynamic contractions in which muscle length and/or force may vary. The objective of this investigation was to explore this possibility. An examination of the effects of amplitude modulation on modeled electromyographic signals revealed that changes in variance created in this way do not sufficiently affect characteristic frequency data to obscure a trend with fatigue. This validated the contention that not all non-stationarities in signals necessarily manifest in power spectral parameters. While an investigation of the nature and effects of non-stationarities in real electromyographic signals produced from dynamic contractions indicated that a more complex model is warranted, the results also indicated that averaging associated with estimating spectral parameters with the short-time Fourier transform can control the effects of the more complex non-stationarities. Finally, a fatigue test involving dynamic contractions at a force level under 30% of peak voluntary dynamic range, validated that it was possible to track fatigue in dynamic contractions using a traditional short-time Fourier transform methodology.

Adult↗
PubMed2003

Spectral analysis of the acoustic emission of laser-produced plasmas.

A Q-switched frequency Nd:YAG laser was focused on copper, aluminum, and lead targets. The acoustic emission accompanying plasma formation was acquired and analyzed in both the time and the frequency domains. Spectral analysis of the shock wave has proved to be a simple and low-cost diagnostic of plasma phenomena. In the time domain, several propagation mechanisms of the shock wave were observed and the velocity profile of the shock wave estimated. Spectral measurements were performed in the acoustic propagation regime of the shock waves. Spectral features related to the plasma formation mechanism were identified and discussed for copper, aluminum, and lead on the basis of the physical properties of these elements, the expansion mechanisms of the plasma, and an empirical parameter representative of the transported energy.

Journal Article↗
PubMed2000

Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment.

In this article we consider the application of parametric spectral analysis to multichannel event-related potentials (ERPs) during cognitive experiments. We show that with proper data preprocessing, Adaptive MultiVariate AutoRegressive (AMVAR) modeling is an effective technique for dealing with nonstationary ERP time series. We propose a bootstrap procedure to assess the variability in the estimated spectral quantities. Finally, we apply AMVAR spectral analysis to a visuomotor integration task, revealing rapidly changing cortical dynamics during different stages of task processing.

Animals↗