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PubMed2004

Wavelet analysis of pulse oximeter waveform permits identification of unwell children.

BACKGROUND: Children who are unwell often display signs of circulatory compromise. It has been observed that pronounced changes occur in the appearance of the photoplethysmogram (pulse oximeter tracing) in these children. The aim of the study was to discover if wavelet transforms can identify more subtle changes in the photoplethysmogram of children who are unwell. METHODS: Photoplethysmograms were obtained from children attending a paediatric accident and emergency department with clinical features suggestive of significant bacterial illness or circulatory compromise. Photoplethysmograms were also obtained from a control group of well children. Wavelet transforms were applied to the traces in an attempt to separate the two groups. RESULTS: 20 traces were obtained from unwell children and 12 from controls. Analysis of the entropy of the wavelet transform of the photoplethysmogram allows the differentiation of unwell children from controls (p = 0.00002). CONCLUSIONS: Wavelet transform of the photoplethysmogram offers the possibility of a rapid non-invasive method of screening children for significant illness.

Blood Gas Monitoring, Transcutaneous↗
PubMed1998

Wavelet analysis of click-evoked otoacoustic emissions.

Time-frequency distribution methods are being widely used for the analysis of a variety of biomedical signals. Recently, they have been applied also to study otoacoustic emissions (OAE's), the active acoustic response of the hearing end organ. Click-evoked otoacoustic emissions (CEOAE's) are time-varying signals with a clear frequency dispersion along with the time axis. Analysis of CEOAE's is of considerable interest due to their close relation with cochlear mechanisms. In this paper, several basic time-frequency distribution methods are considered and compared on the basis of both simulated signals and real CEOAE's. The particular structure of CEOAE's requires a method with both a satisfactory time and frequency resolution. Results from simulations and real CEOAE's revealed that the wavelet approach is highly suitable for the analysis of such signals. Some examples of the application of the wavelet transform to CEOAE's are provided here. Applications range from the extraction of normative data from adult and neonatal OAE's to the extraction of quantitative parameters for clinical purposes.

Adult↗
PubMed2006

Comparative multiresolution wavelet analysis of ERP spectral bands using an ensemble of classifiers approach for early diagnosis of Alzheimer's disease.

Early diagnosis of Alzheimer's disease (AD) is becoming an increasingly important healthcare concern. Prior approaches analyzing event-related potentials (ERPs) had varying degrees of success, primarily due to smaller study cohorts, and the inherent difficulty of the problem. A new effort using multiresolution analysis of ERPs is described. Distinctions of this study include analyzing a larger cohort, comparing different wavelets and different frequency bands, using ensemble-based decisions and, most importantly, aiming the earliest possible diagnosis of the disease. Surprising yet promising outcomes indicate that ERPs in response to novel sounds of oddball paradigm may be more reliable as a biomarker than the more commonly used responses to target sounds.

Aged↗
PubMed2002

Wavelet analysis of instantaneous heart rate: a study of autonomic control during thrombolysis.

Myocardial infarction (MI) is known to elicit activation of the autonomic nervous system. Reperfusion, induced by thrombolysis, is thus expected to bring about a shift in the balance between the sympathetic and vagal systems, according to the infarct location. In this study, we explored the correlation between reperfusion and the spectral components of heart rate (HR) variability (HRV), which are associated with autonomic cardiac control. We analyzed the HR of patients during thrombolysis: nine anterior wall MI (AW-MI) and eight inferoposterior wall MI (IW-MI). Reperfusion was determined from changes in ST levels and reported pain. Reocclusion was detected in four patients. HRV was analyzed using a modified continuous wavelet transform, which provided time-dependent versions of the typically used low-frequency (LF) and high-frequency (HF) peaks and of their ratio, LF/HF. Marked alterations in at least one of the HRV parameters was found in all 18 reperfusion events. Patterns of HRV, compatible with a shift toward relative sympathetic enhancement, were found in all of the nine reperfusion events in IW-MI patients and in three AW-MI patients. Patterns of HRV compatible with relative vagal enhancement were found in six AW-MI patients (P < 0.001). Significant changes in HRV parameters were also found after reocclusion. Time-dependent spectral analysis of HRV using the wavelet transform was found to be valuable for explaining the patterns of cardiac rate control during reperfusion. In addition, examination of the entire record revealed epochs of markedly diminished HRV in two patients, which we attribute to vagal saturation.

Adult↗
PubMedDate not supplied

Multiresolution wavelet analysis of the body surface ECG before and after angioplasty.

Electrocardiographic recordings of patients with coronary artery stenosis, made before and after angioplasty, were analyzed by the multiresolution wavelet transform (MRWT) technique. The MRWT decomposes the signal of interest into its coarse and detail components at successively finer scales. MRWT was carried out on different leads in order to compare the P-QRS-T complex from recordings made before with those made after percutaneous transluminal coronary angioplasty (PTCA). ECG signals before and after successful PTCA procedures show distinctive changes at certain scales, thus helping to identify whether the procedure has been successful. In six patients who underwent right coronary artery PTCA, varying levels of reperfusion were achieved, and the changes in the detail components of ECG were shown to correlate with the successful reperfusion. The detail components at scales 5 and 6, corresponding approximately to the frequencies in the range of 2.3-8.3 Hz, are shown to be the most sensitive to ischemia-reperfusion changes (p < 0.05). The same conclusion was reached by synthesizing the post-PTCA signals from pre-PTCA signals with the help of these detail components. For on-line monitoring a vector plot, analogous to vector cardiogram, of the two most sensitive MRWT detail components is proposed. Thus, multiresolution analysis of ECG may be useful as a monitoring and diagnostic tool during angioplasty procedures.

Adult↗
PubMedDate not supplied

Wavelet analysis of EEG for three-dimensional mapping of epileptic events.

This paper is aimed at understanding epileptic patient disorders through the analysis of surface electroencephalograms (EEG). It deals with the detection of spikes or spike-waves based on a nonorthogonal wavelet transform. A multilevel structure is described that locates the temporal segments where abnormal events occur. These events are then visually interpreted by means of a 3D mapping technique. This 3D display makes use of a ray tracing scheme and combines both the functional (the EEG but also its wavelet representation) and the morphological data (acquired from computed tomography [CT] or magnetic resonance imaging [MRI] devices). The results show that a significant reduction of the clinical workload is obtained while the most important episodes are better reviewed and analyzed.

Algorithms↗
PubMed2000

Complex denoising of MR data via wavelet analysis: application for functional MRI.

A fast post-processing method for noise reduction of MR images, termed complex-denoising, is presented. The method is based on shrinking noisy discrete wavelet transform coefficients via thresholding, and it can be used for any MRI data-set with no need for high power computers. Unlike previous wavelet application to MR images, the denoising algorithm is applied, separately, to the two orthogonal sets of the complex MR image. The norm of the combined data are used to construct the image. With this method, signal-noise decoupling and Gaussian white noise assumptions used in the wavelet noise suppression scheme, are better fulfilled. The performance of the method is tested by carrying out a qualitative and quantitative comparison of a single-average image, complex-denoised image, multiple-average images, and a magnitude-denoised image, of a standard phantom. The comparison shows that the complex-denoising scheme improves the signal-to-noise and contrast-to-noise ratios more than the magnitude-denoising scheme, particularly in low SNR regions. To demonstrate the method strength, it is applied to fMRI data of somatosensory rat stimulation. It is shown that the activation area in a cross-correlation analysis is approximately 63% larger in the complex-denoised versus original data sets when equal threshold value is used. Application of the method of Principal Component Analysis to the complex-denoised, magnitude-denoised, and original data sets results in a similar but higher variance of the first few principal components obtained from the former data set as compared to those obtained from the later two sets.

Algorithms↗
PubMed2006

Wavelet analysis of scaling properties of gastric electrical activity.

We present a novel approach to the analysis of fluctuations in human myoelectrical gastric activity measured noninvasively from the surface of the abdomen. The time intervals between successive maxima of the wavelet transformed quasi-periodic electrogastrographic waveform define the gastric rate variability (GRV) time series. By using the method of average wavelet coefficients, the statistical fluctuations in the GRV signal in healthy individuals are determined to scale in time. Such scaling was previously found in a variety of physiological phenomena, all of which support the hypothesis that physiological dynamics utilize fractal time series. We determine the scaling index in a cohort of 17 healthy individuals to be 0.80 +/- 0.14, which compared with a set of surrogate data is found to be significant at the level P < 0.01. We also determined that the dynamical pattern, so evident in the spectrum of average wavelet coefficients of the GRV time series of healthy individuals, is significantly reduced in a cohort of systemic sclerosis patients having a scaling index 0.64 +/- 0.17. These results imply that the long-term memory in GRV time series is significantly reduced from healthy individuals to those with systemic sclerosis. Consequently, this disease degrades the complexity of the underlying gastrointestinal control system and this degradation is manifest in the loss of scaling in the GRV time series.

Adult↗
PubMed2001

Otoacoustic emissions and improved pass/fail separation using wavelet analysis and time windowing.

A new method is presented for the purpose of improving pass/fail separation during transient evoked otoacoustic emission (TEOAE) hearing screening. The method combines signal decomposition in scales using the discrete wavelet transform, non-linear denoising and scale-dependent time windowing. The cross-correlation coefficient between two subaveraged, processed TEOAE signals is used as a pass/fail criterion and assessed in relation to the pure-tone, mean hearing level. The performance is presented in terms of receiver operating characteristics for a database of 5,214 individuals. The results show that the specificity improves from 68% to 83% at a sensitivity of 90% when compared with the conventional wave reproducibility parameter.

Hearing Loss↗
PubMed2001

Efficient hemodynamic event detection utilizing relational databases and wavelet analysis.

Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on large-scale time-oriented medical databases.

Algorithms↗
PubMed2000

Low-resolution phase extension using wavelet analysis.

A method to extend low-resolution phases is presented which uses histogram matching not only of the electron density, but also of histograms obtained from the different levels of detail provided by the wavelet transform of the electron density. Statistical values for the wavelet coefficients can be predicted and depend only on the resolution and solvent content. Therefore, new details can be added to an electron-density map by matching the values of the wavelet coefficients to those predicted for an increased resolution. The positions of the new details are also guided by the diffraction pattern. In this way, the resolution can be increased gradually; on a number of trial structures of different size, solvent percentage and space group, it has been possible to extend the phasing from 10 A to around 6-7 A.

Electrons↗
PubMed2006

Heart rate variability characterization in daily physical activities using wavelet analysis and multilayer fuzzy activity clustering.

A portable data recorder was developed to parallel measure the electrocardiogram and body accelerations. A multilayer fuzzy clustering algorithm was proposed to classify the physical activity based on body accelerations. Discrete wavelet transform was incorporated to retrieve time-varying characteristics of heart rate variability under different physical activities. Nine healthy subjects were included to investigate activity-related heart rate variability during 24 h. The results showed that the heartbeat fluctuations in high frequencies were the greatest during lying and the smallest during standing. Moreover, very-low-frequency heartbeat fluctuations during low activity level (lying) were greater than during high activity level (nonlying).

Activities of Daily Living↗
PubMed2004

Fine structure in the energy region of the isoscalar giant quadrupole resonance: characteristic scales from a wavelet analysis.

Fine structure in the energy region of the isoscalar giant quadrupole resonance in nuclei is observed in high-resolution proton scattering experiments at iThemba LABS over a wide mass range. A novel method based on wavelet transforms is introduced for the extraction of scales characterizing the fine structure. A comparison with microscopic model calculations including two-particle two-hole (2p2h) degrees of freedom identifies the coupling to surface vibrations as the main source of the observed scales. A generic pattern is also found for the stochastic coupling to the background of the more complex states.

Journal Article↗
PubMed2002

Wavelet analysis of vortex tubes in experimental turbulence.

This paper proposes a method to study vortex tubes in one-dimensional velocity data of experimental turbulence. Vortex tubes are detected as local maxima on the scale-space plot of wavelet transforms of the velocity data. Then it is possible to extract a typical velocity pattern. The result for data obtained in a wind tunnel is consistent with those of three-dimensional direct numerical simulations.

Journal Article↗
PubMed1993

Wavelet analysis of arterial pressure and blood velocity pulsations in the aorta of anesthetized dogs.

The arterial pressure and blood velocity pulsations were recorded from the aorta of anesthetized dogs by means of micro-tip pressure and velocity transducers. Wavelet transforms (Wt) were obtained by converting the analog signals into digital samples at the rate of 42.7 per second, which were subsequently subjected to an algorithm of WT. An iterative rarefaction (2(0) to 2(-4) resolutions) of the number of samples was followed by a substraction of the high frequency components (wavelet coefficients) from the corresponding resolutions. Analyses of the arterial pulsations revealed that the second WT always yielded four types of systolic apexes, which were apparently devoid of physiological meaning, since they were inherent to the "triangulation phase" of the WT algorithm. In addition, the third WT occasionally revealed slow amplitude modulations, which could not be identified in the original recordings and whose significance deserves further investigation. This is also valid for the wavelet coefficients, whose biological meaning is still obscure. In summary, the WT operates as a low pass filter, which brings to light the lower frequency components of arterial pulsations and which finally yields the mean values of both arterial pressure and blood velocities.

Algorithms↗
PubMed1999

Wavelet analysis of electromyography for back muscle fatigue detection during isokinetic constant-torque exertions.

STUDY DESIGN: An investigation of the effects of human trunk extensor muscle fatigue on the temporal change in frequency content of the electromyogram as quantified using the Fourier and wavelet transforms during the performance of repetitive dynamic trunk extension. OBJECTIVE: To evaluate whether alterations in the Fourier and wavelet transform measures were consistent with a shift of the signal power to lower frequencies, and to determine which measures were more highly correlated with the decline in maximal trunk extension torque. SUMMARY OF BACKGROUND DATA: Objective assessment of trunk muscle fatigue is likely to play a more important role in the rehabilitation and prevention of low back injuries, given the association between lack of trunk muscle endurance and acquisition of low back pain. Validation of new methods designed to quantify the level of fatigue using the surface electromyogram is necessary before these techniques can be used in industrial rehabilitation settings. The wavelet transform is a recent development in the signal processing of electromyograms that shows promise as a method for assessment of fatigue. METHODS: Trunk muscle electromyograms obtained from study participants performing repetitive isokinetic trunk extension endurance tests were analyzed using the wavelet and the traditional Fourier methods. Trunk extension torque was controlled at 35% and 70% of the participants' maximal voluntary contraction while they exerted at 5 and 10 repetitions per minute. The decline in maximal trunk extension torque was measured once per minute. Linear regression quantified the rate of change in Fourier and wavelet measures caused by fatigue, whereas Pearson's correlation coefficient determined their association with the decline in maximum torque. RESULTS: Changes in the characteristics of the electromyogram were consistent with a shift to lower frequencies: The signal power at higher frequencies was reduced, whereas the power at lower frequencies was elevated. The amount of change was dependent on the task conditions (exertion level and repetition rate). The wavelet-based measures demonstrated as strong an association with the decline in maximal torque output as the Fourier-based measures. CONCLUSIONS: This study demonstrates that assessment of trunk muscle fatigue during isokinetic movementis possible using both Fourier and wavelet measurements. However, the methods were not as likely to change significantly during lower rates of exertion. These methods, when implemented in a controlled setting, may be used to document the rehabilitation process and guide preventive exercise training.

Adult↗
PubMed2000

Wavelet analysis and time-frequency distributions of the body surface ECG before and after angioplasty.

In a pilot study, electrocardiographic (ECG) recordings of patients with left and right coronary stenosis taken before and after angioplasty were analyzed using the continuous wavelet transform. Time-frequency distributions were obtained for different leads in order to examine the dynamics of the QRS-spectrum and establish features specific of ischemia in the time-frequency domain. We found relevant changes in the mid-frequency range, reflecting the ECG's response to percutaneous transluminal coronary angioplasty (PTCA). The changes appeared in ECG leads close to ischemic zones of the myocardium. Time-frequency distributions of the ECG during the QRS may thus become another electrocardiographic indicator of ischemia, alternative to ST-level in standard ECG or body surface mapping. The paper demonstrates the ability of the continuous wavelet transform to detect short lasting events of low amplitude superimposed on large signal deflections.

Angioplasty, Balloon, Coronary↗
PubMed2001

Wavelet analysis of P3a and P3b.

Target/standard discrimination difficulty and the degree of stimulus "novelty" were manipulated systematically in a three-stimulus odd-ball task to assess how these variables affect target and non-target P300 scalp distributions for visual stimuli. Wavelet transformation (WT) analyses were performed on the non-target (P3a) and target (P3b) ERPs to assay how the underlying electroencephalographic (EEG) activity was affected by both the difficulty and novelty factors. When target/standard discrimination was easy, P300 amplitude was higher for the target than the non-target across all electrode sites, and both demonstrated parietal maximums. In contrast, when target/standard discrimination was difficult, non-target amplitude (P3a) was higher and earlier over the frontal/central electrode sites for both levels of novelty, whereas target amplitude (P3b) was greater parietally and occurred later than the non-target components and was generally unaffected by non-target novelty level. The WT analyses indicated that appreciable theta activity was related to the more novel non-target stimuli; primarily target component delta coefficients were affected by the discrimination difficulty variable. The findings suggest that target/standard discrimination difficulty, rather than stimulus novelty, determines P3a generation for visual stimuli but that the underlying theta oscillations are differentially affected by stimulus novelty. WT analysis methods are discussed along with the theoretical and neurophysiological implications of the findings.

Adult↗