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PubMed2000

Sleep stage dependant changes of the high-frequency part of the somatosensory evoked potentials at the thalamus and cortex.

OBJECTIVES: It is known that the high-frequency oscillations (above 400 Hz) of the somatosensory evoked potentials (SEPs) diminish during sleep while the N20 persists (Neurology 38 (1988) 64; Electroenceph clin Neurophysiol 70 (1988) 126; Electroenceph clin Neurophysiol 100 (1996) 189). We investigated possible differential effects of sleep on the 600 Hz SEPs at the thalamus and cortex. METHODS: SEPs from 10 subjects were recorded using 64 channels following electric stimulation at the wrist during awake state and sleep stages II, IV and REM. Dipole source analysis was applied to separate brain-stem, thalamic and cortical activity in the low-frequency (20-450 Hz) and the high-frequency (450-750 Hz) part of the signal. RESULTS: The low-frequency SEPs showed a non-significant increase of the latency of the N20 and a bifid change of the waveform in 3 subjects. The high-frequency SEPs showed a significant decrease of their amplitude at the level of the thalamus and cortex but not at the brain-stem. This decrease in amplitude at the thalamus and cortex were significantly correlated. There was no effect on the latency of the signal. In addition, at the cortex, differential effects on early and late parts of the 600 Hz oscillations were found by time-frequency analysis using a wavelet transformation. CONCLUSIONS: Sleep dependent decrease of the high-frequency SEPs were first observed at the thalamus pointing to the known function of the reticular thalamic nucleus regulating arousal. The results presented here provide further evidence for a thalamic origin of the 600 Hz oscillations. In addition, on the basis of the differential effects on early (up to the N20 peak) and late (between 20 and 25 ms) parts of the signal, at least one intracortical generator of these oscillations is proposed. In general, the high-frequency SEPs (600 Hz oscillations) are supposed to reflect activity of a somatosensory arousal system.

Adult↗
PubMed1996

Automated feature extraction for the classification of human in vivo 13C NMR spectra using statistical pattern recognition and wavelets.

If magnetic resonance spectroscopy (MRS) is to become a useful tool in clinical medicine, it will be necessary to find reliable methods for analyzing and classifying MRS data. Automated methods are desirable because they can remove user bias and can deal with large amounts of data, allowing the use of all the available information. In this study, techniques for automatically extracting features for the classification of MRS in vivo data are investigated. Among the techniques used were wavelets, principal component analysis, and linear discriminant function analysis. These techniques were tested on a set of 75 in vivo 13C spectra of human adipose tissue from subjects from three different dietary groups (vegan, vegetarian, and omnivore). It was found that it was possible to assign automatically 94% of the vegans and omnivores to their correct dietary groups, without the need for explicit identification or measurement of peaks.

Adipose Tissue↗
PubMed1982

Two retinal processes displayed in the cat electroretinogram.

Local stimulation of dark adapted cat's retina with spots of light of various intensities elicits a complex b-wave in which four deflections can be consistently identified. An analysis of these wavelets recorded with the low frequency cut off at 80 Hz is made in an attempt to infer their origin. The experimental conditions under which these wavelets were studied were standardized by stimulation with a spot of light at different intensities, frequencies and positions in the visual field. The changes in amplitude and latency by those different conditions of stimulation and by the intravenous (i.v.) injection of additional doses of nembutal, suggests that these peaks are triggered by two retinal excitatory processes related to the scotopic system. It is also pointed out that components 1-2 are mainly determined by the activation of retinal cells which correspond to the area centralis and that components 3-4 represent the activity of retinal cells from the lateral regions (nasal and temporal). The possible clinical use of our results is discussed.

Action Potentials↗
PubMed2003

Investigating the evolution and structure of chemokine receptors.

Chemokine receptors represent a prime target for the development of novel therapeutic strategies in a variety of disease processes, including inflammation, allergy and neoplasia. Here we use maximum likelihood methods and bootstrap methods to investigate both the phylogenetic relationships in a large set of human chemokine receptor sequences and the relationships between chemokine receptors and their nearest neighbors. We found that CCR and CXCR families are not homogeneous. We also provide evidences that angiotensin receptors are the closest neighbors. Other close neighbors include opioid, somatostatin and melanin-concentrating hormone receptors. The phylogenetic analysis suggests ancient paralogous relationships and establishes a link between immune, metabolic and neural systems modulation. We complement our findings with a structural analysis based on wavelet methods of the major branches of chemokine receptors phylogeny. We hypothesize that receptors very close in the tree can form heterodimers. Our analyses reveal different characteristics of amino acid hydrophobicity and volume propensity in the different subfamilies. We also found that the second extra-cytoplasmic loop has higher rates of evolution than the internal loops and transmembrane segments, suggesting that selection, shifting, reassignments and broadening of receptor binding specificities involve mainly this loop.

Evolution, Molecular↗
PubMed2006

Ultrasensitive detection and characterization of posttranslational modifications using surface-enhanced Raman spectroscopy.

Posttranslational modification (PTM) of proteins is likely to be the most common mechanism of altering the expression of genetic information. It is essential to characterize PTMs to establish a complete understanding of the activities of proteins. Here, we present a sensitive detection method using surface-enhanced Raman spectroscopy (SERS) that can detect PTMs from as little as zeptomoles of peptide. We demonstrate, using model peptides, the ability of SERS to detect a variety of protein modifications, such as acetylation, trimethylation, phosphorylation, and ubiquitination. In addition, we show the capability to obtain positional information for modifications such as trimethylation and phosphorylation using SERS and wavelet decomposition data analysis techniques. We further show that it is possible to apply SERS to detect PTMs from biological samples such as histones. We envision that this detection method might be a valuable technique that is complementary to mass spectrometry in obtaining orthogonal chemical and modification-specific information from biological samples at sensitive levels.

Acetylation↗
PubMed2002

High accuracy of automatic detection of atrial fibrillation using wavelet transform of heart rate intervals.

Permanent and paroxysmal AF is a risk factor for the occurrence and the recurrence of stroke, which can occur as its first manifestation. However, its automatic identification is still unsatisfactory. In this study, a new mathematical approach was evaluated to automate AF identification. A derivation set of 30 24-hour Holter recordings, 15 with chronic AF (CAF) and 15 with sinus rhythm (SR), allowed the authors to establish specific RR variability characteristics using wavelet and fractal analysis. Then, a validation set of 50 subjects was studied using these criteria, 19 with CAF, 16 with SR, and 15 with paroxysmal AF (PAF); and each QRS was classified as true or false sinus or AF beat. In the SR group, specificity reached 99.9%; in the CAF group, sensitivity reached 99.2%; in the PAF group, sensitivity reached 96.1%, and specificity 92.6%. However, classification on a patient basis provided a sensitivity of 100%. This new approach showed a high sensitivity and a high specificity for automatic AF detection, and could be used in screening for AF in large populations at risk.

Algorithms↗
PubMed2006

Effects of prolonged surface pressure on the skin blood flowmotions in anaesthetized rats--an assessment by spectral analysis of laser Doppler flowmetry signals.

The objective of this study is to assess the effect of prolonged surface compression on the skin blood flowmotion in rats using spectral analysis based on wavelets transform of the periodic oscillations of the cutaneous laser Doppler flowmetry (LDF) signal. An external pressure of 13.3 kPa (100 mmHg) was applied to the trochanter area and the distal lateral tibia of Sprague-Dawley rats via two specifically designed pneumatic indentors. The loading duration was 6 hours/day for 4 consecutive days. Five frequency intervals were identified (0.01-0.04 Hz, 0.04-0.15 Hz, 0.15-0.4 Hz, 0.4-2 Hz and 2-5 Hz) corresponding to endothelial related metabolic, neurogenic, myogenic, respiratory and cardiac origins. The absolute amplitude of oscillations of each particular frequency interval and the normalized amplitude were calculated for quantitative assessments. The results showed that (1) tissue compression following the above schedule induced significant decrease in the normalized amplitude in the frequency interval of 0.01-0.04 Hz both in the trochanter area (p < 0.001) and tibialis area (p = 0.023), (2) prolonged compression induced significant increase in the absolute amplitude (p = 0.004 for the trochanter area and p = 0.017 for the tibialis area) but significant decrease in the normalized amplitude (p = 0.023 for the trochanter area and p = 0.026 for the tibialis area) in the frequency interval of 0.15-0.4 Hz, and (3) at the tibialis area, the flowmotion amplitude (frequency interval 0.15-0.4 Hz) measured prior to the daily tissue compression schedule was found to be significantly higher on day 4 than the measurements obtained on day 1. However, this finding was not observed at the trochanter area. Our results suggested that prolonged compression might induce endothelial damage and affect the endothelial related metabolic activities.

Adaptation, Physiological↗
PubMed2006

Effects of prolonged compression on the variations of haemoglobin oxygenation - assessment by spectral analysis of reflectance spectrophotometry signals.

The consequences of rhythmical flow motion for nutrition and the oxygen supply to tissue are largely unknown. In this study, the periodic variations of haemoglobin oxygenation in compressed and uncompressed skin were evaluated with a reflection spectrometer using an in vivo Sprague-Dawley rat model. Skin compression was induced over the trochanter area by a locally applied external pressure of 13.3 kPa (100 mmHg) via a specifically designed pneumatic indentor. A total of 19 rats were used in this study. The loading duration is 6 h per day for four consecutive days. Haemoglobin oxygenation variations were quantified using spectral analysis based on wavelets' transformation. The results found that in both compressed and uncompressed skin, periodic variations of the haemoglobin oxygenation were characterized by two frequencies in the range of 0.01-0.05 Hz and 0.15-0.4 Hz. These frequency ranges coincide with those of the frequency range of the endothelial-related metabolic and myogenic activities found in the flow motion respectively. Tissue compression following the above loading schedule induced a significant decrease in the spectral amplitudes of frequency interval 0.01-0.05 Hz during the pre-occlusion period on day 3 and day 4 as compared to that on day 1 (p < 0.05). In contrast, at a frequency range of 0.15-0.4 Hz, prolonged compression caused a significant increase in spectral amplitude during the pre-occlusion period in the compressed tissue on day 3 (p = 0.041) and day 4 (p = 0.024) compared to that in the uncompressed tissue on day 1. These suggested that the variations of the haemoglobin oxygenation were closely related to the endothelial-related metabolic and myogenic activities. Increased amplitude in the frequency interval 0.15-0.4 Hz indicated an increased workload of the vascular smooth muscle and could be attributed to the increase of O(2) consumption rates of arteriolar walls. The modification of vessel wall oxygen consumption might substantially affect the available oxygen supply to the compressed tissue. This mechanism might be involved in the process leading to pressure ulcer formation.

Animals↗
PubMed2005

Comparison of technical and anatomical noise in digital thorax X-ray images.

Former studies by Hoeschen and Buhr indicated a higher total noise in a thorax image than expected from technical noise, i.e. quantum and detector noise. This difference results from the overlay of many small anatomical structures along the X-ray beam, which leads to a noise-like appearance without distinguishable structures in the projected image. A method is proposed to quantitatively determine this 'anatomical noise' component, which is not to be confused with the anatomical background (e.g. ribs). This specific anatomical noise pattern in a radiograph changes completely when the imaging geometry changes because different small anatomical structures contribute to the projected image. Therefore, two images are taken using slightly different exposure geometry, and a correlation analysis based on wavelet transforms allows to determining the uncorrelated noise components. Since the technical noise also differs from image to image, which makes it difficult to separate the anatomical noise, images of a lung phantom were produced on a low-sensitive industrial X-ray film using high-exposure levels. From these results, the anatomical noise level in real clinical thorax radiographs using realistic exposure levels is predicted using the general dose dependence described in the paper text and compared with the quantum and detector noise level of an indirect flat-panel detector system. For consistency testing, the same lung phantom was imaged with the same digital flat-panel detector and the total image noise including anatomical noise is determined. The results show that the relative portion of anatomical noise may exceed the technical noise level. Anatomical noise is an important contributor to the total image noise and, therefore, impedes the recognition of anatomical structures.

Artifacts↗
PubMed2000

Nonlinear dynamics optically induced in nematic liquid crystals

We report the analysis of the dynamical regimes induced in a homeotropically aligned nematic liquid-crystal layer when an s-polarized laser beam impinges at a small incident angle. These regimes are studied by analyzing the time series of the variation of the polarization state of a light probe beam, recorded at different light intensities. A detailed description of the dynamical regimes, based on the analysis of the wavelet transforms performed on the observed time series, is presented. We recognize a first Hopf bifurcation followed by a gluing bifurcation, and a further transition toward an irregular regime. Similarities between our experimental results and a scenario of transition to chaos via a sequence of gluing bifurcations have been discussed.

Journal Article↗
PubMed2003

Optimization of wavelet decomposition for image compression and feature preservation.

A neural-network-based framework has been developed to search for an optimal wavelet kernel that can be used for a specific image processing task. In this paper, a linear convolution neural network was employed to seek a wavelet that minimizes errors and maximizes compression efficiency for an image or a defined image pattern such as microcalcifications in mammograms and bone in computed tomography (CT) head images. We have used this method to evaluate the performance of tap-4 wavelets on mammograms, CTs, magnetic resonance images, and Lena images. We found that the Daubechies wavelet or those wavelets with similar filtering characteristics can produce the highest compression efficiency with the smallest mean-square-error for many image patterns including general image textures as well as microcalcifications in digital mammograms. However, the Haar wavelet produces the best results on sharp edges and low-noise smooth areas. We also found that a special wavelet whose low-pass filter coefficients are 0.32252136, 0.85258927, 1.38458542, and -0.14548269) produces the best preservation outcomes in all tested microcalcification features including the peak signal-to-noise ratio, the contrast and the figure of merit in the wavelet lossy compression scheme. Having analyzed the spectrum of the wavelet filters, we can find the compression outcomes and feature preservation characteristics as a function of wavelets. This newly developed optimization approach can be generalized to other image analysis applications where a wavelet decomposition is employed.

Algorithms↗
PubMed2006

DNA molecule classification using feature primitives.

BACKGROUND: We present a novel strategy for classification of DNA molecules using measurements from an alpha-Hemolysin channel detector. The proposed approach provides excellent classification performance for five different DNA hairpins that differ in only one base-pair. For multi-class DNA classification problems, practitioners usually adopt approaches that use decision trees consisting of binary classifiers. Finding the best tree topology requires exploring all possible tree topologies and is computationally prohibitive. We propose a computational framework based on feature primitives that eliminates the need of a decision tree of binary classifiers. In the first phase, we generate a pool of weak features from nanopore blockade current measurements by using HMM analysis, principal component analysis and various wavelet filters. In the next phase, feature selection is performed using AdaBoost. AdaBoost provides an ensemble of weak learners of various types learned from feature primitives. RESULTS AND CONCLUSION: We show that our technique, despite its inherent simplicity, provides a performance comparable to recent multi-class DNA molecule classification results. Unlike the approach presented by Winters-Hilt et al., where weaker data is dropped to obtain better classification, the proposed approach provides comparable classification accuracy without any need for rejection of weak data. A weakness of this approach, on the other hand, is the very "hands-on" tuning and feature selection that is required to obtain good generalization. Simply put, this method obtains a more informed set of features and provides better results for that reason. The strength of this approach appears to be in its ability to identify strong features, an area where further results are actively being sought.

Computational Biology↗
PubMed2005

Detecting long-range correlations in time series of dorsal horn neuron discharges.

We have studied the discharge dynamics of dorsal horn neurons by applying the detrended fluctuation analysis and the wavelet transform technique. We have adopted that the neuronal discharge dynamics is manifested by the random time series of interspike intervals. In all cases studied, we found two different power-law type behaviors across interspike intervals enumeration scale, that are separated by crossover regions (which implies existence of two different types of neuronal noise). Our results reveal that complex neuronal dynamics may change in the presence of external stimulation, manifested by changing of the noise characteristics that appear before crossover.

Action Potentials↗
PubMed2005

A soft decision algorithm for obstructive sleep apnea patient classification based on fast estimation of wavelet entropy of RRI data.

A soft decision algorithm for Obstructive Sleep Apnea (OSA) patient classification using R-R interval (RRI) data is investigated. This algorithm is based on fast and approximate estimation of the entropy of the wavelet-decomposed bands of the RRI data. The classification is done on the whole record as OSA patient or non-patient (normal). The ratio of the estimated entropy of the low-frequency (LF) band to that of the very-low frequency (VLF) band is used as a classification factor. RRI data used in this work are drawn from MIT database. The MIT trial records are used to set the threshold value of the classification factor using the Receiver Operating Characteristics (ROC). This threshold value is used then to classify the MIT challenge (test) records to obtain the efficiency of classification. The new algorithm classifies correctly 30/30 of MIT-test data using different wavelet filters. Comparison of the results of different wavelet filters is done in terms of complexity and distance parameters. The method is also compared with other two techniques using wavelets in their analysis. The consistency of the results is examined using the leave-one-out technique.

Adult↗
PubMed2005

[Estimation of age-related changes in the regulation of peripheral blood flow in humans].

The age-dependent features in the state of skin microvascular bed has been studied with laser Doppler flowmetry in healthy volunteers of different age groups. To reveal the reaction of skin blood flow in response to short-term ischemia, the occlusive test has been carried out. To estimate the contribution of rhythmic components to blood flow signal, continuous wavelet-transform spectral analysis was used. Age-dependent increase of pulse-wave amplitude and decrease of respiratory wave amplitude reflecting age-dependent changes in functioning of arteriolar and venular links of microvascular bed have been observed at rest. In response to short-term ischemia the age-dependent reduction of reserve resources has been revealed in functioning of arteriolar link of microvascular bed. The reduction of activity of myogenic, neurogenic and endothelial regulation systems have been shown at rest in ageing.

Adult↗
PubMed2006

Advanced image fusion algorithms for Gamma Knife treatment planning. Evaluation and proposal for clinical use.

Image fusion is a process of combining information from multiple sensors. It is a useful tool implemented in the treatment planning programme of Gamma Knife Radiosurgery. In this paper we evaluate advanced image fusion algorithms for Matlab platform and head images. We develop nine level grayscale image fusion methods: average, principal component analysis (PCA), discrete wavelet transform (DWT) and Laplacian, filter - subtract - decimate (FSD), contrast, gradient, morphological pyramid and a shift invariant discrete wavelet transform (SIDWT) method in Matlab platform. We test these methods qualitatively and quantitatively. The quantitative criteria we use are the Root Mean Square Error (RMSE), the Mutual Information (MI), the Standard Deviation (STD), the Entropy (H), the Difference Entropy (DH) and the Cross Entropy (CEN). The qualitative are: natural appearance, brilliance contrast, presence of complementary features and enhancement of common features. Finally we make clinically useful suggestions.

Algorithms↗
PubMed2000

Intensity analysis in time-frequency space of surface myoelectric signals by wavelets of specified resolution.

Surface myoelectric signals often appear to carry more information than what is resolved in root mean square analysis of the progress curves or in its power spectrum. Time-frequency analysis of myoelectric signals has not yet led to satisfactory results in respect of separating simultaneous events in time and frequency. In this study a time-frequency analysis of the intensities in time series was developed. This intensity analysis uses a filter bank of non-linearly scaled wavelets with specified time-resolution to extract time-frequency aspects of the signal. Special procedures were developed to calculate intensity in such a way as to approximate the power of the signal in time. Applied to an EMG signal the intensity analysis was called a functional EMG analysis. The method resolves events within the EMG signal. The time when the events occur and their intensity and frequency distribution are well resolved in the intensity patterns extracted from the EMG signal. Averaging intensity patterns from multiple experiments resolve repeatable functional aspects of muscle activation. Various properties of the functional EMG analysis were shown and discussed using model EMG data and real EMG data.

Electromyography↗
PubMed1994

Time-frequency analysis of the electrocortical activity during maturation using wavelet transform.

In this study, we introduce the wavelet transform (WT) as a method for characterizing the maturational changes in electrocortical activity in 24 fetal lambs ranging from 110-144 days gestation (term 145 days). The WT, based on multiresolution signal decomposition, is free of assumptions regarding the characteristics of the signal. The approximation of the electrocortical activity at resolutions varying from 2j+1 to 2j can be extracted by decomposing the signal on a wavelet orthonormal basis of L2(R). We performed multiresolution decomposition for four sets of parameters D2j, where -1 < j < -4. The four series WT represent the detail signal band-widths: (1) 16-32 Hz, (2) 8-16 Hz, (3) 4-8 Hz, (4) 2-4 Hz. The data were divided into three groups according to gestational age: 110-122 days (early), 123-135 days (middle), and 136-144 days (late). In the early group, the power was highest in the fourth signal bandwidth, with relatively low power in the other bands. Increase in gestational age was characterized by increased power in all four bandwidths. Comparison of the cumulative distribution function of the power in the four wavelet bands confirmed the presence of two statistically different patterns in all three age groups. These two patterns correspond to the visually identified patterns of HVSA (high-voltage slow activity) and LVFA (low-voltage fast activity). The earliest development change occurred in HVSA, with progressive increase in power in the 2-8 Hz band. Later changes occurred in LVFA, with a significant increase in power in the 16-32 Hz band.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗