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PubMed1998

Discrimination between monomorphic and polymorphic ventricular tachycardia using cycle length variability measured by wavelet transform analysis.

The objective of this study was to assess the capability of wavelet transform (WT) analysis to differentiate between monomorphic (MVTs) and polymorphic ventricular tachycardias (PVTs) in a canine model and to relate these results to epicardial isochronal maps on a beat-by-beat basis. Unipolar electrograms were simultaneously recorded from the surface of both ventricles with a 127-lead sock electrode array in 24 open-chest anesthetized dogs. The sampling frequency was 500 Hz. Atrioventricular block was induced by formaldehyde injection into the atrioventricular node. The left anterior descending coronary artery was occluded for 60 minutes under ventricular pacing (140 stimuli/min) followed by reperfusion. Ventricular tachycardias were obtained during reperfusion and during left stellate ganglion stimulation. After visual selection, a total of 97 segments of 2,048 samples (4.096 seconds) were extracted and classified as 67 MVTs and 30 PVTs. A parameter based on the cycle length variability was defined in the second scale of the WT decomposition, normalized by its mean value. Similar assessment of cycle length variability was performed based on the detection of the point of most rapid change in potential with a negative slope in excess of -0.5 mV/ms in each individual electrogram to test the accuracy of the results obtained with the WT parameter. The WT parameter correctly identified 97% MVT and 83.3% PVT segments, for an overall accuracy of 92.8%. Beat-by-beat epicardial maps of MVT displayed a cluster of sites of initial activation close to the reperfusion area, while the sites of breakthrough from beats during PVT were much more dispersed over both ventricles. A strong and significant correlation was found between the number of electrodes with the earliest epicardial activation and the WT parameter (r = .78, P < .0001). To test the accuracy of the results obtained, a comparison was performed between the WT parameter (0.082 +/- 0.007) and the cycle length variability, estimated as the normalized standard deviation of the intervals between individual electrograms (0.076 +/- 0.006). No significant differences were shown (P = .0022), and a strong linear correlation was found between both measurements (Pearson correlation coefficient, .966). It is concluded that WT analysis discriminated accurately between MVT and PVT, and a quantitative relation was found with the spatial dispersion of sites of earliest epicardial activation. The WT results strongly correlated with those obtained by another method of estimating cycle length variability. Methodologically, the strength of the WT lies in the complementary information that could be extracted from the processing of electrograms to enhance the detection/discrimination of different types of arrhythmias.

Animals↗
PubMed2003

Identification of isochore boundaries in the human genome using the technique of wavelet multiresolution analysis.

Incorporated with the Z curve method, the technique of wavelet multiresolution (also known as multiscale) analysis has been proposed to identify the boundaries of isochores in the human genome. The human MHC sequence and the longest contigs of human chromosomes 21 and 22 are used as examples. The boundary between the isochores of Class III and Class II in the MHC sequence has been detected and found to be situated at the position 2,490,368bp. This result is in good agreement with the experimental evidence. An isochore with a length of about 7Mb in chromosome 21 has been identified and found to be gene- and Alu-poor. We have also found that the G+C content of chromosome 21 is more homogeneous than that of chromosome 22. Compared with the window-based methods, the present method has the highest resolution for identifying the boundaries of isochores, even at a scale of single base. Compared with the entropic segmentation method, the present method has the merits of more intuitiveness and less calculations. The important conclusion drawn in this study is that the segmentation points, at which the G+C content undergoes relatively dramatic changes, do exist in the human genome. These 'singularity' points may be considered to be candidates of isochore boundaries in the human genome. The method presented is a general one and can be used to analyze any other genomes.

Algorithms↗
PubMed1997

Time-domain quanification of amplitude, chemical shift, apparent relaxation time T2, and phase by wavelet-transform analysis. Application to biomedical magnetic resonance spectroscopy.

The wavelet-transform method is used to quantify the magnetic resonance spectroscopy (MRS) parameters: chemical shift, apparent relaxation time T2, resonance amplitude, and phase. Wavelet transformation is a time-frequency representation which separates each component from the FID, then successively quantifies it and subtracts it from the raw signal. Two iterative procedures have been developed. They have been combined with a nonlinear regression analysis method and tested on both simulated and real sets of biomedical MRS data selected with respect to the main problems usually encountered in quantifying biomedical MRS, specifically "chemical noise," resulting from overlapping resonances, and baseline distortion. The results indicate that the wavelet-transform method can provide efficient and accurate quantification of MRS data.

Algorithms↗
PubMed2003

Effects of tenotomy surgery on congenital nystagmus waveforms in adult patients. Part I. Wavelet spectral analysis.

Congenital nystagmus (CN) is an aperiodic oscillatory eye movement disorder. Horizontal rectus tenotomy with simple re-attachment has been proposed as a therapy for CN. This therapy might affect vision and/or eye movements. Another paper deals with improvements in visual acuity. This and the companion paper examine changes in eye movements. In this study, we examined the effect of tenotomy on nystagmus waveforms using wavelet spectral analysis. No common effect was found across the patients on the wavelet spectra of the CN beat, suggesting that tenotomy surgery has no effect, or only a quite small effect, on the waveform structure of CN.

Adult↗
PubMed2005

Is the method of signal analysis and test selection important for measuring standing balance in subjects with persistent whiplash?

Dizziness and or unsteadiness, associated with episodes of loss of balance, are frequent complaints in those suffering from persistent problems following a whiplash injury. Research has been inconclusive with respect to possible aetiology, discriminative tests and analyses used. The aim of this pilot research was to identify the test conditions and the most appropriate method for the analysis of sway that may differentiate subjects with persistent whiplash associated disorders (WAD) from healthy controls. The six conditions of the Clinical Test for Sensory Interaction in Balance was performed in both comfortable and tandem stance in 20 subjects with persistent WAD compared to 20 control subjects. The analyses were carried out using a traditional method of measurement, total sway distance, to results obtained from the use of wavelet analysis. Subjects with WAD were significantly less able to complete the tandem stance tests on a firm surface than controls. In comfortable stance, using wavelet analysis, significant differences between subjects with WAD and the control group were evident in total energy of the trace for all test conditions apart from eyes open on the firm surface. In contrast, the results of the analysis using total sway distance revealed no significant differences between groups across all six conditions. Wavelet analysis may be more appropriate for detecting disturbances in balance in whiplash subjects because the technique allows separation of the noise from the underlying systematic effect of sway. These findings will be used to direct future studies on the aeitiology of balance disturbances in WAD.

Adult↗
PubMed1999

Wavelet transform analysis of heart rate variability during dipyridamole-induced myocardial ischemia: relation to angiographic severity and echocardiographic dyssynergy.

BACKGROUND: Analysis of heart rate variability (HRV) is a valuable noninvasive method for quantifying autonomic cardiac control in humans and has been utilized during dipyridamole echocardiographic test to differentiate positive from negative test results. HYPOTHESIS: We aimed to evaluate, by means of HRV analysis, the influence of the angiographic severity of coronary artery disease on cardiac autonomic control during dipyridamole-induced myocardial ischemia. METHODS: We analyzed RR interval variability changes during dipyridamole-induced myocardial ischemia in 31 selected patients (mean age 54 +/- 9 years) with available coronary angiography and positive dipyridamole echocardiographic test. Spectral components of HRV were assessed by means of wavelet transform analysis for the last 5 min before the beginning of the test (baseline) and for 5 min after the onset of ischemia-related events (peak dipyridamole effect). RESULTS: Patients were divided into three groups according to the number of coronary diseased vessels (Group A, single-vessel disease; Group B, double-vessel disease; Group C, triple-vessel disease). No difference was detectable at baseline among the three groups. After dipyridamole, low-frequency power, a measure of sympathetic modulation of heart rate, increased and echocardiographic wall motion score index worsened in all groups (p < 0.001). The increase in low-frequency power was more evident in Group C patients than in the other two groups (p < 0.005). Furthermore, after dipyridamole, a direct correlation was found between low-frequency power and wall motion score index (r = 0.59; p < 0.001). CONCLUSIONS: These data suggest that HRV analysis performed during dipyridamole echocardiographic test provides useful information to assess the severity of coronary artery disease.

Autonomic Nervous System↗
PubMed1999

Time-varying spectral analysis of heart rate and left ventricular pressure variability during balloon coronary occlusion in humans: a sympathoexicitatory response to myocardial ischemia.

OBJECTIVES: We assessed time-varying spectral components of heart rate and left ventricular (LV) pressure variability during coronary angioplasty to elucidate dynamic autonomic responses to transient myocardial ischemia. BACKGROUND: Sympathoexcitatory reflexes elicited by acute coronary occlusion are rarely addressed in the clinical settings because of a lack of technique to monitor transient changes in sympathetic activation. METHODS: RR interval and LV pressure and volume were serially recorded in 14 patients with effort angina during balloon coronary angioplasty. Wavelet analysis was applied for determination of nonstationary spectral components of RR interval and LV peak pressure variability. RESULTS: The wavelet analysis revealed that coronary occlusion provoked low-frequency (LF) fluctuations of RR interval (seven patients) and LV peak pressure (six patients) at 0.06 +/- 0.01 Hz, but not in the remaining patients. Following the balloon inflation, the LF component of RR interval began to increase after the onset of myocardial ischemia, peaked at about 80 s, and then declined in the late phase of inflation. Consequently, the ratio of low to high frequency component rose to be significantly greater in the LF augmentation group than in the no LF augmentation group in the middle phase of coronary occlusion. The patients with no LF augmentation had little evidence of myocardial ischemia as reflected by changes in ST segment and LV systolic function during coronary occlusion. CONCLUSIONS: The wavelet analysis of RR interval and LV pressure variability clearly showed a dynamic profile of spectral components in response to transient coronary artery occlusion. The resultant regional myocardial ischemia elicited a profound sympathoexcitatory response followed by a gradual suppression. This method provides a useful tool to gain a new insight into the nonstationary autonomic influence on the cardiovascular system.

Adult↗
PubMed2006

Study-level wavelet cluster analysis and data-driven signal models in pharmacological MRI.

In pharmacological MRI (phMRI) studies tracking signal changes following the acute administration of a compound, the spatiotemporal pattern of response is often unknown a priori. Moreover, when analysed within a general linear model (GLM) framework, the experimental paradigm of a single injection point under-informs the construction of an appropriate signal model, and information from pharmacokinetics or ancillary in vivo studies may be unavailable or insufficient to accurately describe the dynamic signal changes observed following injection of the drug. Here, we extend the application of a data-driven clustering algorithm, wavelet cluster analysis (WCA), to phMRI data from one or more groups of subjects in a study. A WCA decomposition of spatially concatenated time series' provides a compact overview of spatiotemporal response patterns across cohorts, highlighting typical temporal signatures, brain regions implicated in the response and inter-subject variability. Further, we demonstrate the use of regressors based on selected temporal components as suitable signal models in GLM-based analyses, resulting in a close fit to dynamic phMRI signal changes. This approach is illustrated with simulated data and two representative in vivo phMRI studies in the rat (nicotine and apomorphine challenges).

Animals↗
PubMed1998

Speckle reduction and contrast enhancement of echocardiograms via multiscale nonlinear processing.

This paper presents an algorithm for speckle reduction and contrast enhancement of echocardiographic images. Within a framework of multiscale wavelet analysis, we apply wavelet shrinkage techniques to eliminate noise while preserving the sharpness of salient features. In addition, nonlinear processing of feature energy is carried out to enhance contrast within local structures and along object boundaries. We show that the algorithm is capable of not only reducing speckle, but also enhancing features of diagnostic importance, such as myocardial walls in two-dimensional echocardiograms obtained from the parasternal short-axis view. Shrinkage of wavelet coefficients via soft thresholding within finer levels of scale is carried out on coefficients of logarithmically transformed echocardiograms. Enhancement of echocardiographic features is accomplished via nonlinear stretching followed by hard thresholding of wavelet coefficients within selected (midrange) spatial-frequency levels of analysis. We formulate the denoising and enhancement problem, introduce a class of dyadic wavelets, and describe our implementation of a dyadic wavelet transform. Our approach for speckle reduction and contrast enhancement was shown to be less affected by pseudo-Gibbs phenomena. We show experimentally that this technique produced superior results both qualitatively and quantitatively when compared to results obtained from existing denoising methods alone. A study using a database of clinical echocardiographic images suggests that such denoising and enhancement may improve the overall consistency of expert observers to manually defined borders.

Algorithms↗
PubMed2002

Wavelet transform analysis of dynamic speckle patterns texture.

We propose the use of the wavelet transform to characterize the time evolution of dynamic speckle patterns. We describe it by using as an example a method used for the assessment of the drying of paint. Optimal texture features are determined and the time evolution is described in terms of the Mahalanobis distance to the final (dry) state. From the behavior of this distance function, two parameters are defined that characterize the evolution. Because detailed knowledge of the involved dynamics is not required, the methodology could be implemented for other complex or poorly understood dynamic phenomena.

Journal Article↗
PubMed1998

Spatial enhancement of event-related potentials using multiresolution analysis.

Multiresolution analysis is a potentially useful tool to enhance the brain's electrical fields (spatial distributions of event-related potentials (ERP)), and to bring out spatial features which may not be seen in the fields before enhancement. For comparing different images (slices from ERP of different subjects or from the same subject but evoked by different stimuli), we define a measure (surface energy) at each decomposition scale and for different wavelets. The best wavelet and the best level for comparing the given images can be chosen based on this measure. Our experiments show that for very similar images, their difference can be brought out at some scale level. Three preprocessing steps are needed in order to carry out this wavelet analysis. First, a wavelet denoising step is needed to remove noise from the raw ERP. Secondly, a one-to-one mapping is needed to map scalp surface into a square, because the current wavelet analysis theory and algorithm are constructed on regular domains. Finally, a fitting or interpolation step is needed to construct an image on a regular grid in order to apply the fast wavelet transform algorithms.

Brain↗
PubMed2001

Time-on-task analysis using wavelet networks in an event-related potential study on attention-deficit hyperactivity disorder.

OBJECTIVE: The aim of this event-related potential (ERP) study was to test time-on-task analysis at the level of single sweeps in a clinical trial. Since inattentiveness is one of the main symptoms of attention-deficit hyperactivity disorder (ADHD), this child psychiatric disorder was chosen as an exemplary application. METHODS: Twenty-four healthy and 24 ADHD boys, aged 9--15 years, performed an auditory selective attention task for about 5 min. ERP single trials were analyzed using wavelet networks. Time-on-task analysis was applied to omission errors, reaction time and slow ERP components (frontal negativity, parietal positivity), represented by a low-frequency wavelet component. RESULTS: Both performance and ERP measures showed distinct temporal dynamics. Time-on-task effects were not only linear, but also of higher order and started after less than 1 min. For ADHD children, earlier time-on-task effects, i.e. an earlier increase of omission errors and frontal negativity, resulted. Healthy children could allocate more attentional resources during the course of the experiment. CONCLUSION: Time-on-task analysis at the level of single trials revealed phenomena probably reflecting ADHD children's attentional deficits. Thus, a more differentiated ERP analysis may provide a better understanding of the pathophysiological background in neuropsychiatric disorders.

Acoustic Stimulation↗
PubMed2006

Single-trial evoked potential estimation: comparison between independent component analysis and wavelet denoising.

OBJECTIVE: Brain responses to repeated sensory stimuli are typically buried in the more prominent background activity, and thus analysis of these responses on a single-trial basis would require advanced procedures to estimate the brain activity related only to the experimental task. Recently, we have proposed a new iterative independent component analysis (iICA) approach to estimate single-trial responses. In this paper, we compare the performance of iICA at estimating single-trial responses with ensemble averaging and wavelet transform (WT) denoising. METHODS: We analyzed simulated evoked potentials (EPs) and actual recordings of the auditory N100 component from 33 normal subjects, and the performance of each method was quantified in terms of the average root-mean-square error and average correlation before and after processing. RESULTS: We found that WT gave a smoother overall average EP, while iICA could isolate the N100 component out of the entire EP waveform. With simulated data, iICA provided significantly better estimates of the true EP compared to plain averaging (p<0.01) and WT (p<0.01). With actual data, iICA showed clear responses in single trials, in all subjects. Additionally, the corresponding average EPs had a sharper N100-P200 complex, with flatter preceding and following regions, resulting in an enhanced N100 component. CONCLUSIONS: The iICA procedure can provide clear responses in each single trial, and the resulting average N100 component is significantly improved compared to plain averaging and wavelet denoising. SIGNIFICANCE: The proposed technique may have a significant impact as a clinical tool in the analysis of single-trial responses.

Adult↗
PubMed2004

Wavelet-based analysis of low-frequency fluctuations of blood pressure and sympathetic nerve activity in rats.

Biorthogonal wavelets were employed to quantify the relationship of fluctuations between blood pressure (BP) and sympathetic nerve activity (SNA). We forced the SNA to fluctuate by electrical stimulation the medulla in anesthetized, paralyzed, vagotomized, cardiac sympathetic-blocked, baroreceptor-denervated, and angiotensin II-converting enzyme-inhibited rats. Although spectral analysis showed a close coupling between fluctuations of BP and SNA at the stimulating frequencies, only the fluctuations of SNA in frequencies of 0.25 to approximately 0.4 Hz were proportional to BP fluctuations over the course of time. The results suggest that fluctuations transmitted from SNA to BP were uniform without shifting due to the nature of vasculature or the lagging of sympathetic action in frequencies of 0.25 to approximately 0.4 Hz, and support the possibility of using low-frequency variabilities of BP to quantitatively estimate fluctuations of SNA at time domain.

Action Potentials↗
PubMed2005

High-frequency components of auditory evoked potentials are detected in responsive but not in unconscious patients.

BACKGROUND: The dose-dependent suppression of midlatency auditory evoked potentials by general anesthetics has been proposed to measure depth of anesthesia. In this study, perioperatively recorded midlatency auditory evoked potentials were analyzed in a time-frequency space to identify significant changes induced by general anesthesia. METHODS: Perioperatively recorded auditory evoked potentials of 19 patients, recorded at varying levels of anesthesia, were submitted to a multiscale analysis using the wavelet analysis. Energy contents of the signal were calculated in frequency bands 0-57.1 Hz, 57.1-114.3 Hz, 114.3-228.6 Hz, and 228.6-457.1 Hz. A Friedman test and a Dunn multiple comparisons test were performed to identify significant differences. RESULTS: Statistical evaluation showed a highly significant decrease of the wavelet energies for the frequency bands 57.1-114.3 Hz (P < 0.0001), 114.3-228.6 Hz (P < 0.0001), and 228.6-457.1 Hz (P < 0.0001) for the measuring points representing deep general anesthesia. This decrease is accompanied by a decrease in the wavelet energy of the frequency band 0-57.1 Hz of no statistical significance (P = 0.021) (level of significance set to P = 0.01). The changes are most prominent in the poststimulus interval between 10 and 30 ms. CONCLUSIONS: This study describes the presence of high-frequency components of the auditory evoked potential. The amount of these components is higher during responsiveness when compared to unconsciousness. Temporal localization of the high-frequency components within the auditory evoked potential shows that they represent a response to the auditory stimulus. Further studies are required to identify the source of these high-frequency components.

Acoustic Stimulation↗
PubMed2005

Diagnosing aortic valve stenosis by correlation analysis of wavelet filtered heart sounds.

Traditional auscultation performed by the general practitioner remains problematic and often gives significant results only in a late stage of heart valve disease. Valve stenoses and insufficiencies are nowadays diagnosed with accurate but expensive ultrasonic devices. This study aimed to develop a new heart sound analysis method for diagnosing aortic valve stenoses (AVS) based on a wavelet and correlation technique approach. Heart sounds recorded from 373 patients (107 AVS patients, 61 healthy controls (REF) and 205 patients with other valve diseases (OVD)) with an electronic stethoscope were wavelet filtered, and envelopes were calculated. Three correlations on the basis of these envelopes were performed: within the AVS group, between the groups AVS and REF and between the groups AVS and OVD, resulting in the mean correlation coefficients rAVS, rAVSv.REF and rAVSv.OVD. These results showed that rAVS (0.783 +/- 0.097) is significantly higher (p < 0.0001) than rAVSv.REF (0.590 +/- 0.056) and rAVSv.OVD (0.516 +/- 0.056), leading to a highly significant discrimination between the groups. The wavelet and correlation-based heart sound analysis system should be useful to general practitioners for low-cost, easy-to-use automatic diagnosis of aortic valve stenoses.

Adult↗
PubMedDate not supplied

Wavelet-based multiresolution analysis of irregular surface meshes.

This paper extends Lounsbery's multiresolution analysis wavelet-based theory for triangular 3D meshes, which can only be applied to regularly subdivided meshes and thus involves a remeshing of the existing 3D data. Based on a new irregular subdivision scheme, the proposed algorithm can be applied directly to irregular meshes, which can be very interesting when one wants to keep the connectivity and geometry of the processed mesh completely unchanged. This is very convenient in CAD (Computer-Assisted Design), when the mesh has attributes such as texture and color information, or when the 3D mesh is used for simulations, and where a different connectivity could lead to simulation errors. The algorithm faces an inverse problem for which a solution is proposed. For each level of resolution, the simplification is processed in order to keep the mesh as regular as possible. In addition, a geometric criterion is used to keep the geometry of the approximations as close as possible to the original mesh. Several examples on various reference meshes are shown to prove the efficiency of our proposal.

Algorithms↗
PubMed2000

Adaptive wavelet filtering for analysis of event-related potentials from the electro-encephalogram.

A challenging task in psychophysiology is the extraction of event-related potentials (ERPs) from the background electro-encephalogram. The task is made more difficult by the properties of ERPs, which typically consist of multiple features of variable latency, localised in time and frequency. A novel technique is described for analysis of ERPs, adaptive wavelet filtering (AWF), which is proposed as an alternative to trial averaging. Band-limited detail representations of each trial are obtained using wavelet analysis. The Woody adaptive filter is then used to align trials with respect to the evoked response. In a simulation study, the AWF extracts 39% of higher-frequency signal variance from background noise, compared with less than 1% for standard averaging and the Woody filter. The AWF is applied to a data-set of 448 ERPs, comprising right-finger button presses from eight subjects. Average split-half reliability of the AWF on scales up to 12 Hz was 0.51.

Electroencephalography↗