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At least 199 records · Page 11Linked to original sources
PubMed2003

Short-period circumnutations found in sunflower hypocotyls in satellite orbit. A reappraisal of data from Spacelab-1.

We have further analysed data from an experiment performed in satellite orbit, in Spacelab-1. In micro-gravity the hypocotyls of Helianthus annuus, cv. "Teddy Bear", showed short period circumnutations (periods around 30 minutes) as well as the already reported long period nutations (with an average period of about 115 minutes). We applied various types of signal analysis (Fourier and wavelet analysis) to the data series. The long period circumnutations have a larger amplitude than the short term circumnutations. Both short and long period circumnutations exist in one and the same hypocotyl. (This is in contrast to our ground control experiments, where were found only the long-period nutations.) The period of the nutations changed throughout the experiment. These results are extending the conclusions drawn after the Spacelab experiment (Brown et al. 1990). In particular they emphasize the existence of both short- and long-period circumnutations in micro-gravity.

Fourier Analysis↗
PubMed2003

Wavelet transform analysis of heart rate variability to assess the autonomic changes associated with spontaneous coronary spasm of variant angina.

We used Wavelet transform (WT) to investigate whether variation in autonomic tone was associated with spontaneous coronary spasm in patients with variant angina by analysis of heart rate variability (HRV). Twenty-one episodes preceding ST-segment elevation were selected under Holter monitoring in 12 men and 3 women with variant angina. HRV indices were calculated at 10 second intervals with the continuous WT, and analyzed within 30 minutes preceding ST-segment elevation. High frequency (HF; 0.15 approximately 2.00 Hz) increased significantly during the 4 minutes prior to ST-segment elevation, low frequency (LF; 0.04 approximately 0.15 Hz) decreased significantly during the period from 10 to 5 minutes and increased significantly during the 2 minutes prior to ST-segment elevation, the LF/HF ratio decreased significantly during the period from 10 to 3 minutes and increased significantly during the 2 minutes prior to ST-segment elevation. The RR interval decreased significantly during the 2 minutes prior to ST-segment elevation. These results suggest that the acute variation in autonomic tone was associated with spontaneous coronary spasm in patients with variant angina. A reduction in sympathetic activity, then enhancement of vagal activity may play a key role in triggering the spontaneous coronary spasm, and the secondary activation of sympathetic activity may worsen the coronary spasm resulting in the attack.

Adult↗
PubMed2003

Cross-correlation time-frequency analysis for multiple EMG signals in Parkinson's disease: a wavelet approach.

Using a wavelet analysis approach, it is possible to investigate better the transient and intermittent behavior of multiple electromyographic (EMG) signals during ballistic movements in Parkinsonian patients. In particular, a wavelet cross-correlation analysis on surface signals of two different shoulder muscles allows us to evidence the related unsteady and synchronization characteristics. With a suitable global parameter extracted from local wavelet power spectra, it is possible to accurately classify the subjects in terms of a reliable statistic and to study the temporal evolution of the Parkinson's disease level. Moreover, a local intermittency measure appears as a new promising index to distinguish the low-frequency behavior from normal subjects to Parkinsonian patients.

Adult↗
PubMed2004

[Analysis of wavelet transformed electromyographic signals that were altered by wearing a knee brace].

The comparison of electromyograms represents a challenge for data analysis. The aim of the project was to present a method that uses a minimal computational effort to resolve small but significant changes in the muscular activity that occur while walking with and without a knee brace. The wavelet transformed electromyograms were represented as intensity patterns that resolve the power of the signal in time and frequency. The intensity pattern of each electromyogram defines single points in a pattern space. The distance between these points in pattern space were used to detect and show the separation between the groups of electromyograms that were recorded while walking with and without a knee brace. The method proposes a distance versus angle representation to visually discriminate the intensity patterns. Once it has been shown that the differences are statistically significant, one can visualize the result in a difference intensity pattern that indicates at what time and at what frequency the electromyograms vary between the two conditions tested. It is to be expected that interventions that are more intrusive than a knee brace will reveal even more distinct differences.

Adult↗
PubMed2006

Evaluation of arrhythmogenic substrate in patients with hypertrophic cardiomyopathy using wavelet transform analysis.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is thought to have a microvolt-level electrical disarrangement in the myocardium that leads to ventricular tachyarrhythmias and sudden cardiac death. Although signal-averaged electrocardiography (ECG) has been used to detect late potential as a parameter of electrical instability, its predictability is not high. The focus of the present study was the ability of high-resolution wavelet transform from beat-to-beat analysis to detect arrhythmogenic substrates and to evaluate its relationship to the severity of ventricular tachycardia. METHODS AND RESULTS: The study group comprised 50 healthy subjects and 50 patients with HCM. The filtered-QRS duration from the signal-averaged ECG, the high-power duration (HPD) and number of disarrangement points (NDP) from the wavelet-transform ECG were measured. When HPD was defined >114 ms and/or NDP >9 points as abnormal, the sensitivity and specificity for ventricular tachycardia was 93.8% and 79.4%, respectively. When a mean +/- standard deviation of the HPD in normal subjects was defined as normal, 93.8% of patients with a positive late potential were out of the normal range. CONCLUSIONS: The newly developed color-display 3-dimensional wavelet transform system showed good time-frequency resolution in analyzing every single beat without signal-averaging. The analysis could be used to detect arrhythmogenic substrates in patients with HCM.

Arrhythmias, Cardiac↗
PubMed2006

Propagating magnetohydrodynamics waves in coronal loops.

High cadence Transition Region and Coronal Explorer (TRACE) observations show that outward propagating intensity disturbances are a common feature in large, quiescent coronal loops, close to active regions. An overview is given of measured parameters of such longitudinal oscillations in coronal loops. The observed oscillations are interpreted as propagating slow magnetoacoustic waves and are unlikely to be flare-driven. A strong correlation, between the loop position and the periodicity of the oscillations, provides evidence that the underlying oscillations can propagate through the transition region and into the corona. Both a one- and a two-dimensional theoretical model of slow magnetoacoustic waves are presented to explain the very short observed damping lengths. The results of these numerical simulations are compared with the TRACE observations and show that a combination of the area divergence and thermal conduction agrees well with the observed amplitude decay. Additionally, the usefulness of wavelet analysis is discussed, showing that care has to be taken when interpreting the results of wavelet analysis, and a good knowledge of all possible factors that might influence or distort the results is a necessity.

Journal Article↗
PubMed2002

Habituation and sensitization in rat auditory evoked potentials: a single-trial analysis with wavelet denoising.

In this work, systematic changes of single-trial auditory evoked potentials elicited in rats were studied. Single-trial evoked potentials were obtained with the help of wavelet denoising, a very recently proposed method that has already been shown to be useful in the analysis of scalp human evoked potentials. For the evoked components in the 13-24-ms range (i.e. P13, N18, P20 and N24), it was possible to identify slow exponential decreases in the peak amplitudes, most likely related to a slow habituation process, while for N18, an initial increase in amplitude was also found. On the contrary, the slower components (N38 and N52) habituated within a few trials, and we therefore propose that they are related to a different functional process. The outcomes of the present study show that wavelet denoising is a useful technique for analyzing evoked potentials in rats at the single-trial level. In fact, in the present study it was possible to obtain more information than the one described in previous related works. This allows the study of other forms of learning processes in rats with the aid of evoked potentials. Finally, the outcomes of this study may have some relevance for the comparison of human and rat evoked potentials.

Acoustic Stimulation↗
PubMed1998

Wavelet-based analysis of human blood-flow dynamics.

To analyze signals measured from human blood flow in the time-frequency domain, we used the wavelet transform which gives good time resolution for high-frequency components and good frequency resolution for low-frequency components. Five characteristic frequency peaks, corresponding to five almost periodic rhythmic activities, were found on the time scale of minutes. These oscillations were characterized by time and spatial invariant measures. The potential of this approach in studying the blood-flow dynamics was illustrated by revealing differences between the groups of control subjects and athletes.

Cardiovascular Physiological Phenomena↗
PubMed2001

Estimation of an unexpected-overlooking error by means of the single eye fixation related potential analysis with wavelet transform filter.

An unexpected-overlooking error that caused failure to notice near the peripheral vision is one of the accident factors in driving behavior. We estimated how the unexpected-overlooking error affected the amplitude of the lambda wave in the eye fixation related potential (EFRP). Four subjects participated in the experiment. Each subject was required press the right or left switch according to the given task, which was that he/she pressed the right switch when the blue dot appeared in the right detected area or he/she pressed the left switch when the red dot appeared in the right. The single trial data from Pz, which referred to both earlobes, were analyzed by means of a wavelet transform (WT) filter. The difference of the lambda amplitude between the corrected data was applied for analysis of variance. Three subjects showed a significant effect (P<0.01 or P<0.05), and the remaining one subject did not show a significant consequence of only two errors. The unexpected-overlooking errors had a low amplitude compared to the mean of amplitude throughout the task. It was concluded that the amplitude of the lambda wave might reflect the attention level of a subject.

Algorithms↗
PubMed2004

A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis.

Here we describe a practical, step-by-step primer to scale-dependent correlation (SDC) analysis. The analysis of transitory processes is an important but often neglected topic in ecological studies because only a few statistical techniques appear to detect temporary features accurately enough. We introduce here the SDC analysis, a statistical and graphical method to study transitory processes at any temporal or spatial scale. SDC analysis, thanks to the combination of conventional procedures and simple well-known statistical techniques, becomes an improved time-domain analogue of wavelet analysis. We use several simple synthetic series to describe the method, a more complex example, full of transitory features, to compare SDC and wavelet analysis, and finally we analyze some selected ecological series to illustrate the methodology. The SDC analysis of time series of copepod abundances in the North Sea indicates that ENSO primarily is the main climatic driver of short-term changes in population dynamics. SDC also uncovers some long-term, unexpected features in the population. Similarly, the SDC analysis of Nicholson's blowflies data locates where the proposed models fail and provides new insights about the mechanism that drives the apparent vanishing of the population cycle during the second half of the series.

Animals↗
PubMed2004

The fetal electrocardiogram by independent component analysis and wavelets.

Once the fetal electrocardiogram (FECG) waveforms from ECG on the maternal abdomen are detected, the fetal P wave and T wave cannot always be identified by using continuous wavelet transform (CWT). We took noninvasive FECG from the maternal abdomen, extracted it from the maternal electrocardiogram waveforms after an Independent Component Analysis (ICA), and identified the features of those waveforms by using CWT. We also simultaneously analyzed the observed signals by Primary Component Analysis (PCA). FECG has been extracted by ICA from 25 of 30 pregnant women. The fetal P wave and T wave could be identified in 21 of the 25 cases. FECG was extracted by PCA in only one case. ICA is superior to PCA, whose separation quality highly depends on the careful positioning of the electrodes. We believe that after ICA, FECG obtained by the wavelet theory based method will become a powerful tool for the differential diagnosis of fetal arrhythmias.

Adult↗
PubMed2000

Fourier and wavelet transform analysis, a tool for visualizing regular patterns in DNA sequences.

A correlation function that compares each base in a DNA sequence to its various neighbours and which is subsequently processed by Fourier and wavelet transforms has been developed. The procedure has been applied to sequences from the human chromosome 22, to nef genes from various HIV clones and to myosin heavy chain DNA. It permits to readily visualize regular features in DNA which are related to the stability of heteroduplexes formed upon strand slippage.

Animals↗
PubMed2006

Wavelet multiresolution analysis of the three vorticity components in a turbulent far wake.

The main objective of the present study is to examine the characteristics of the vortical structures in a turbulent far wake using the wavelet multiresolution technique by decomposing the vorticity into a number of orthogonal wavelet components based on different central frequencies. The three vorticity components were measured simultaneously using an eight-wire probe at three Reynolds numbers, namely 2000, 4000, and 6000. It is found that the dominant contributions to the vorticity variances are from the intermediate and relatively small-scale structures. The contributions from the large and intermediate-scale structures to the vorticity variances decrease with the increase of Reynolds number. The contributions from the small-scale structures to all three vorticity variances jump significantly when Reynolds number is changed from 2000 to 4000, which is connected to previous observations in the near wake that there is a significant increase in the generation of small-scale structures once the Reynolds number reaches about 5000. This result reinforces the conception that turbulence "remembers" its origin.

Journal Article↗
PubMed2000

[An approach to achieve classification of QRS waves with wavelet multiresolution analysis and fractal dimension].

This paper discussed the theoretical analysis of multiresolution ECGs decomposition and expounds the calculation of the fractal dimension. Based on Mallat's multiresolution analysis and fractal dimension of the series, a new approach to classify the QRS complex was provided: the QRS complex was decomposed with a quadratic spline wavelet. At scale 4, the fractal dimension of the decomposed series was calculated, the values of modulus maxima of wavelet transform and the fractal dimension were used as discriminatory criteria to classify QRS. The method was simple and had high anti-noise ability.

Algorithms↗
PubMed2004

Toward a direct brain interface based on human subdural recordings and wavelet-packet analysis.

Highly accurate asynchronous detection of movement related patterns in individual electrocorticogram channels has been shown using detection based on either event-related potentials (ERPs) or event-related desynchronization and synchronization (ERD/ERS). A method using wavelet-packet features selected with a genetic algorithm was proposed to simultaneously detect ERP and ERD/ERS and was tested on data from seven subjects and four motor tasks. The proposed wavelet method performed better than previous methods with perfect detection for four subject/task combinations and hit percentages greater than 90% with false positive percentages less than 15% for at least one task for all seven subjects.

Action Potentials↗
PubMed2006

Surface myoelectric signal analysis: dynamic approaches for change detection and classification.

Toward the goal of elbow and wrist prostheses control by characterizing events in surface myoelectric signals, this paper presents a dynamic method to simultaneously detect and classify such events. Dynamic cumulative sum of local generalized likelihood ratios using wavelet decomposition of the myoelectric signal is used for on-line detection. Frequency as well as energy changes are detected with this hybrid approach. Classification is composed of using multiresolution wavelet analysis and autoregressive modeling to extract signal features while polynomial classifiers are used for pattern modeling and matching. The results of detecting and classifying four elbow and wrist movements show that, in average, 91% of the events are correctly detected and classified using features obtained from multiresolution wavelet analysis while 95% accuracy is achieved with AR modeling. The classification accuracy decreases, however, if short prostheses response delay is desired. This paper also shows that the performance of the polynomial classifiers is better than that of the commonly used neural networks since it gives higher classification accuracy and consistent classification outcomes. In comparison to the well known support vector machine classification, the polynomial classifier gives similar results without the need to optimize and search for classifier parameters.

Action Potentials↗
PubMed2004

Fourier-, Hilbert- and wavelet-based signal analysis: are they really different approaches?

Spectral signal analysis constitutes one of the most important and most commonly used analytical tools for the evaluation of neurophysiological signals. It is not only the spectral parameters per se (amplitude and phase) which are of interest, but there is also a variety of measures derived from them, including important coupling measures like coherence or phase synchrony. After reviewing some of these measures in order to underline the widespread relevance of spectral analysis, this report compares the three classical spectral analysis approaches: Fourier, Hilbert and wavelet transform. Recently, there seems to be increasing acceptance of the notion that Hilbert- or wavelet-based analyses be in some way superior to Fourier-based analyses. The present article counters such views by demonstrating that the three techniques are in fact formally (i.e. mathematically) equivalent when using the class of wavelets that is typically applied in spectral analyses. Moreover, spectral amplitude serves as an example to show that Fourier, Hilbert and wavelet analysis also yield equivalent results in practical applications to neuronal signals.

Algorithms↗
PubMed2000

Lactate editing and lipid suppression by continuous wavelet transform analysis: application to simulated and (1)H MRS brain tumor time-domain data.

Determination of lactate concentrations in vivo is required in the noninvasive diagnosis, staging, and therapeutic monitoring of diseases such as cancer, heart disease, and stroke. An iterative filtering process based on the continuous wavelet transform (CWT) method in the time domain is proposed to isolate the lactate doublet signal from overlapping lipid resonances and estimate the magnetic resonance spectroscopy (MRS) parameters of the lactate methyl signal (signal amplitude, chemical shift, J-coupling and apparent transverse relaxation time (T*(2))). This method offers a number of advantages over the multiple quantum (MQ) and difference spectroscopy approaches, including: 1) full recovery of the lactate methyl signal, whereas the MQ methods usually detect 50% of the signal intensity; 2) in contrast to MQ methods, the lipid signal is retained together with J-coupling data on the lactate peak; 3) the CWT method is much less sensitive to motion artifacts than difference spectroscopy. Application of the method to simulated and real (1)H MRS data collected from human blood plasma and brain tumors demonstrated that this filter provides accurate estimates of the MRS parameters of the lactate doublet and efficiently removes lipid contributions.

Adult↗