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PubMed2001

[Detection of spikes in epileptic EEG based on Multiresolution Tsallis' entropy].

In this paper, the detection of the spikes in the epileptic EEG signal was studied based on Multiresolution Tsallis' entropy (MRET). First, EEG signals were decomposed into wavelet series, and then, at every scale, the abnormal spikes were distinguished from normal background EEG activities by using MRET. The analysis of 6 patients' EEG data showed that the abnormal epileptiform spikes in EEG can be accurately detected with this method, which opens up the perspectives of building up automatic detection devices for spikes in EEG. Compared with the Shannon entropy, the MRET provides one with more detailed information.

Electroencephalography↗
PubMed1982

Characteristics of the pulsed ultrasound field.

Pulsed ultrasound fields show some quantitative differences from continuous fields. In order to support the analysis of bioeffects of pulsed ultrasound fields these differences are characterized. For each observation point, the sound pulse is calculated by wavelet addition. The total pulse length has a maximum near the transducer surface, corresponding to large differences in acoustical pathlength from the surface elements. Accordingly, the spectrum varies strongly in the near field. In the far field, pulse-length and spectrum are almost constant as long as frequency-dependent absorption is negligible. The radiation field at each point is described by the time integral of sound intensity over one pulse (energy transport per unit area) and by the corresponding "dose" (absorbed energy per unit volume in one pulse). Differences between the spatial distributions of these two quantities are mainly detectable in the near field, which is also the region where differences between continuous and pulsed ultrasound (at the same centre frequency) are considerable.

Energy Transfer↗
PubMed2005

Comparative application of wavelet approaches to absorption and ratio spectra for the simultaneous determination of diminazene aceturate and phenazone in veterinary granules for injection.

A comparison of two wavelet approaches, Daubechies and reverse Biorthogonal, is described for the quantitative resolution of a binary mixture of diminazene aceturate (DIMA) and phenazone (PHE) in veterinary granules for injection without any chemical separation. These two approaches were specified as db4 (a = 180) and rbior3.7 (a = 125) respectively, after testing the signal analysis parameters for the overlapping absorption spectra and ratio spectra. In the first step db4 (a = 180) was applied to the original absorbance data vector of DIMA and PHE. In the second step rbio3.7 (a = 125) was applied to the ratio spectra data vectors of DIMA using the divisor PHE. The same approach was also subjected to the ratio spectra of PHE using the divisor DIMA. The db4 (a = 180) and rbior3.7 (a = 125) calibration graphs were constructed using the transformation values obtained in the wavelet domain. In the method validation, the wavelet calibration functions were tested using synthetic mixtures and the standard addition technique. The simultaneous quantitative analysis of DIMA and PHE in the commercial veterinary preparation was achieved by the elaborated methods. The assay results were compared with each other and good agreement was observed.

Algorithms↗
PubMed2006

Preprocessing RR interval time series for heart rate variability analysis and estimates of standard deviation of RR intervals.

Heart rate variability is concerned with the analysis of the fluctuations in the interval between heart beats known as RR intervals. The long time RR time series obtained suffer from non-stationarity and the presence of ectopic beats, which prevents extraction of useful statistical information. The paper describes a wavelet-based technique for trend removal and a nonlinear filter to remove ectopic beats. This attempts to correct the limitations observed in a recent advanced heart rate toolkit [J. Niskanen, M.P. Tarvainen, P.O. Ranta-aho P.A. Karjalainen, Software for advanced HRV analysis, Comput. Meth. Prog. Biomed.,76 (2004) 73-81] when preprocessing. The results are encouraging. The preprocessed data are then used to obtain the standard deviation of RR interval time series (SDRR) of 15 healthy patients and 15 patients suffering from congestive heart failure. The results demonstrate the importance of preprocessing. The analysis show that the SDRR values of congestive heart failure patients are depressed compared to the healthy group.

Autonomic Nervous System↗
PubMed2001

LV volume quantification via spatiotemporal analysis of real-time 3-D echocardiography.

This paper presents a method of four-dimensional (4-D) (3-D + Time) space-frequency analysis for directional denoising and enhancement of real-time three-dimensional (RT3D) ultrasound and quantitative measures in diagnostic cardiac ultrasound. Expansion of echocardiographic volumes is performed with complex exponential wavelet-like basis functions called brushlets. These functions offer good localization in time and frequency and decompose a signal into distinct patterns of oriented harmonics, which are invariant to intensity and contrast range. Deformable-model segmentation is carried out on denoised data after thresholding of transform coefficients. This process attenuates speckle noise while preserving cardiac structure location. The superiority of 4-D over 3-D analysis for decorrelating additive white noise and multiplicative speckle noise on a 4-D phantom volume expanding in time is demonstrated. Quantitative validation, computed for contours and volumes, is performed on in vitro balloon phantoms. Clinical applications of this spaciotemporal analysis tool are reported for six patient cases providing measures of left ventricular volumes and ejection fraction.

Cardiac Volume↗
PubMed2006

[Quadrature Doppler ultrasound signal denoising based on adapted local cosine transform].

The spectrogram of Doppler ultrasound signal has been widely used in clinical diagnosis. The additional frequency components arising from internal or external noise to the system will produce adverse effects on its subjective and quantitative analysis. A novel approach based on the adapted local cosine transform and the non-negative Garrote thresholding method was proposed to remove noise from quadrature Doppler signal. At first, the directional information was extracted from the quadrature signal. And then the denoising method based on the adapted local cosine transform is performed on the forward and backward flow signals, respectively. At last, the estimated signal was reconstructed from the denoised signals using Hilbert transform. In the simulation study, both the mean frequency and spectral width waveform were studied for the denoised signal. The simulation results had shown that this approach was superior to that based on the wavelet transform, especially under low SNR conditions.

Algorithms↗
PubMed2005

Radon transform orientation estimation for rotation invariant texture analysis.

This paper presents a new approach to rotation invariant texture classification. The proposed approach benefits from the fact that most of the texture patterns either have directionality (anisotropic textures) or are not with a specific direction (isotropic textures). The wavelet energy features of the directional textures change significantly when the image is rotated. However, for the isotropic images, the wavelet features are not sensitive to rotation. Therefore, for the directional textures, it is essential to calculate the wavelet features along a specific direction. In the proposed approach, the Radon transform is first employed to detect the principal direction of the texture. Then, the texture is rotated to place its principal direction at 0 degrees. A wavelet transform is applied to the rotated image to extract texture features. This approach provides a features space with small intraclass variability and, therefore, good separation between different classes. The performance of the method is evaluated using three texture sets. Experimental results show the superiority of the proposed approach compared with some existing methods.

Algorithms↗
PubMed2002

Movement-related changes in cortical oscillatory activity in ballistic, sustained and negative movements.

We studied movement-related EEG oscillatory changes in the alpha, beta and low-gamma frequency bands in three different paradigms of movement, namely ballistic, sustained, and negative (muscle relaxation). A time-frequency analysis of non-phase-locked activity in the 7-47 Hz range was performed on movement-centred EEG sweeps using wavelet filters and Gabor transforms. All three movements were accompanied by a decrease in beta activity that began contralaterally about 1.5 s prior to the onset of movement but that extended to both sides near the beginning of the movement. This decrease was followed by a rebound after the end of the movement in the ballistic and negative movements. A decrease was also seen in the alpha band during the three paradigms, which began later (1 s before movement) and lasted longer. An increase in gamma activity was only seen during ballistic and sustained movements, while a decrease in gamma energy was observed during negative movements. It was concluded that changes in the beta band of the EEG before movement are related to the preparation for the movement, but an important afferent component may be present in the later changes. Gamma band activity may be just involved in the execution of the movement, related to muscle contraction.

Alpha Rhythm↗
PubMed2006

Detection of scale-specific community dynamics using wavelets.

The response of ecological communities to anthropogenic disturbance is of both scientific and practical interest. Communities where all species respond to disturbance in a similar fashion (synchrony) will exhibit large fluctuations in total biomass and dramatic changes in ecosystem function. Communities where some species increase in abundance while others decrease after disturbance (compensation) can maintain total biomass and ecosystem function in the face of anthropogenic change. We examined dynamics of the Little Rock Lake (Wisconsin, USA) zooplankton community in the context of an experimental pH manipulation conducted in one basin of the lake. A novel application of wavelets was used to partition patterns of synchrony and compensation by time scale. We find interestingly that some time series show both patterns of synchrony and compensation depending on the scale of analysis. Within the unmanipulated basin, we found subtle patterns of synchrony and compensation within the community, largely at a one-year time scale corresponding to seasonal variation. Within the acidified lake basin, dynamics shifted to longer time scales corresponding to the pattern of pH manipulation. Comparisons between pairs of species in different functional groups showed both strong compensatory and synchronous responses to disturbance. The strongest compensatory signal was observed for two species of Daphnia whose life history traits lead to synchrony at annual time scales, but whose differential sensitivity to acidification led to compensation at multiannual time scales. The separation of time scales inherent in the wavelet method greatly facilitated interpretation as patterns resulting from seasonal drivers could be separated from patterns driven by pH manipulation.

Animals↗
PubMed2004

Preserving properties of object shape by computations in primary visual cortex.

Although our visual system is extremely good at extracting objects from the visual scene, this process involves complicated computations that are thought to require image processing by many successive cortical areas. Thus, intermediate stages in object extraction should not eliminate essential properties of the objects that are still required by later stages. A particularly important characteristic of an object is its shape, and shape has the property that it is unchanged by translations, rotations, and magnifications of the image. I show that the requirement for this property of shape to be preserved in the image, as represented by the firing of neurons in the primary visual cortex (V1), is equivalent to a particular type of computation, known as a wavelet transform, determining the firing rate of V1 neurons in response to an image on the retina. Experimental data support the conclusion that the neural representation of images in V1 is described by a wavelet transform and, therefore, that the properties of shape are preserved.

Fourier Analysis↗
PubMed2006

A comparison of methods for ERP assessment in a P300-based GKT.

P300-based GKT (guilty knowledge test) has been suggested as an alternative approach for conventional polygraphy. The purpose of this study is to evaluate three classifying methods for this approach and compare their performances in a lab analogue. Several subjects went through the designed GKT paradigm and their respective brain signals were recorded. For the analysis of signals, BAD (bootstrapped amplitude difference) and BCD (bootstrapped correlation difference) methods as two predefined methods alongside a new approach consisting of wavelet features and a statistical classifier were implemented. The rates of correct detection in guilty and innocent subjects were 74-80%. The results indicate the potential of P300-based GKT for detecting concealed information, although further research is required to increase its accuracy and precision and evaluating its vulnerability to countermeasures.

Electroencephalography↗
PubMed1998

High-frequency (600 Hz) SEP activities originating in the subcortical and cortical human somatosensory system.

Digitally high-pass filtered median nerve SEP show an oscillatory burst of low-amplitude high-frequency (600 Hz) wavelets superimposed on the N20 component which itself is generated by excitatory postsynaptic potentials of area 3b pyramidal cells. Prior studies using magnetoencephalography (MEG) localized one wavelet generator close to the primary somatosensory hand cortex. Since MEG recordings are biased towards tangentially oriented and superficial generators, a dipole source analysis of 32-channel electric SEP recordings was employed here to test for the possibility of deep and/or radially oriented burst generators: in 10 normal subjects low noise (16,000 averages) median nerve SEP were evaluated using dipole source analysis before and after applying a digital 475 Hz high-pass filter. Two main oscillatory 600 Hz burst sources were modeled; (i) a deep burst source close to the thalamus, most active in a time window between the brain-stem P14 and the cortical N20 sources, detectable in 7 of 10 subjects; most probably, this activity originates from deep axon segments of thalamocortical fibers; and (ii) a subsequent burst source timed around the N20 and located in the vicinity of the primary somatosensory hand cortex in all subjects, which was already known from MEG data. This superficial oscillatory source may be dominated by repetitive activity conducted in the terminal segments of the thalamocortical projection fibers initiated by the thalamic burst generator.

Brain Stem↗
PubMed2000

Micro-emboli detection: an ultrasound Doppler signal processing viewpoint.

Several studies have been carried out in the last twenty years on the characterization and detection of cerebral artery emboli. From the detection point of view, the existing methods are largely based on the classical Fourier analysis of which the well known limitations provide poor accuracy. This paper first recalls existing methods based on Fourier, Wigner-Ville and wavelet approaches. It then presents new emboli detection methods based on parametric signal processing approaches. The basic idea of these parametric methods is to compare the Doppler embolic signal to its autoregressive model. The detection principle consists in constructing a decision information which contains the signature of the micro-embolus being sought. The detection is finally evaluated using receiver operating characteristic (ROC) curves. Comparison between the new methods and classical approaches is performed using a realistic embolic signal simulation. Furthermore, to validate our theoretical study, we tested our new algorithms using in vivo signals. This comparison shows the significant inaccuracy of existing methods to detect micro-emboli.

Algorithms↗
PubMed2005

Clinical detection and movement recognition of neuro signals.

Neuro signal has many more advantages than myoelectricity in providing information for prosthesis control, and can be an ideal source for developing new prosthesis. In this work, by implanting intrafascicular electrode clinically in the amputee's upper extremity, collective signals from fascicules of three main nerves (radial nerve, ulnar nerve and medium nerve) were successfully detected with sufficient fidelity and without infection. Initial analysis of features under different actions was performed and movement recognition of detected samples was attempted. Singular value decomposition features (SVD) extracted from wavelet coefficients were used as inputs for neural network classifier to predict amputee's movement intentions. The whole training rate was up to 80.94% and the test rate was 56.87% without over-training. This result gives inspiring prospect that collective signals from fascicules of the three main nerves are feasible sources for controlling prosthesis. Ways for improving accuracy in developing prosthesis controlled by neuro signals are discussed in the end.

Amputation, Surgical↗
PubMed2003

Detection of lameness and determination of the affected forelimb in horses by use of continuous wavelet transformation and neural network classification of kinematic data.

OBJECTIVE: To investigate continuous wavelet transformation and neural network classification of gait data for detecting forelimb lameness in horses. ANIMALS: 12 adult horses with mild forelimb lameness. PROCEDURE: Position of the head and right forelimb foot, metacarpophalangeal (ie, fetlock), carpal, and elbow joints was determined by use of kinematic analysis before and after palmar digital nerve blocks. We obtained 8 recordings from horses without lameness, 8 with right forelimb lameness, and 8 with left forelimb lameness. Vertical and horizontal position of the head and vertical position of the foot, fetlock, carpal, and elbow joints were processed by continuous wavelet transformation. Feature vectors were created from the transformed signals and a neural network trained with data from 6 horses, which was then tested on the remaining 2 horses for each category until each horse was used twice for training and testing. Correct classification percentage (CCP) was calculated for each combination of gait signals tested. RESULTS: Wavelet-transformed vertical position of the head and right forelimb foot had greater CCP (85%) than untransformed data (21%). Adding data from the fetlock, carpal, or elbow joints did not improve CCP over that for the head and foot alone. CONCLUSIONS AND CLINICAL RELEVANCE: Wavelet transformation of gait data extracts information that is important for the detection and differentiation of forelimb lameness of horses. All of the necessary information to detect lameness and differentiate the side of lameness can be obtained by observation of vertical head movement in concert with movement of the foot of 1 forelimb.

Animals↗
PubMed2005

Spectral analysis of blood perfusion in the free latissimus dorsi myocutaneous flap and in normal skin.

To find the properties in the oscillatory components of the cutaneous blood flow on the successful free flap, a wavelet transform was applied to the laser Doppler flowmetry (LDF) signals which were measured simultaneously on the surfaces of the free latissimus dorsi myocutaneous flap and on the adjacent intact skin of the healthy limb, of 18 patients. The frequency interval from 0.0095 to 1.6 Hz was examined and was divided into five subintervals (I: 0.0095-0.021 Hz; II: 0.021-0.052 Hz; III: 0.052-0.145 Hz; IV: 0.145-0.6 Hz and V: 0.6-1.6 Hz) corresponding to endothelial metabolic, neurogenic, myogenic, respiratory and cardiac origins. The average amplitude and total power in the frequency range 0.0095-1.6 Hz as well as within subintervals I, II, IV and V were significantly lower for signals measured on the free flap than those obtained in the healthy limb. However in interval III, they were significantly higher. The normalized spectral amplitude and power in the free flap were significantly lower in only two intervals, I and II, yet in interval III they were significantly higher; no statistical significance was observed in intervals IV and V. The distinctive finding made in this study, aside from the decrease of endothelial metabolic processes and sympathetic control, was the significant increase of myogenic activity in the free flap. It is hoped that this work will contribute towards knowledge on blood circulation in free flaps and make the monitoring by LDF more reliable.

Adolescent↗
PubMed1998

Total least-squares reconstruction with wavelets for optical tomography.

In a previous paper [Zhu et al., J. Opt. Soc. Am. A 14, 799 (1997)] an iterative algorithm for obtaining the total least-squares (TLS) solution of a linear system based on the Rayleigh quotient formulation was presented. Here we derive what to our knowledge are the first statistical properties of this solution. It is shown that the Rayleigh-quotient-form TLS (RQF-TLS) estimator is equivalent to the maximum-likelihood estimator when noise terms in both data and operator elements are independent and identically distributed Gaussian. A perturbation analysis of the RQF-TLS solution is derived, and from it the mean square error of the RQF-TLS solution is obtained in closed form, which is valid at small noise levels. We then present a wavelet-based multiresolution scheme for obtaining the TLS solution. This method was employed with a multigrid algorithm to solve the linear perturbation equation encountered in optical tomography. Results from numerical simulations show that this method requires substantially less computation than the previously reported one-grid TLS algorithm. The method also allows one to identify regions of interest quickly from a coarse-level reconstruction and restrict the reconstruction in the following fine resolutions to those regions. Finally, the method is less sensitive to noise than the one-grid TLS and multigrid least-squares algorithms.

Algorithms↗