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PubMed2002

Estimating the time-course of coherence between single-trial brain signals: an introduction to wavelet coherence.

This paper introduces the use of wavelet analysis to follow the temporal variations in the coupling between oscillatory neural signals. Coherence, based on Fourier analysis, has been commonly used as a first approximation to track such coupling under the assumption that neural signals are stationary. Yet, stationary neural processing may be the exception rather than the rule. In this context, the recent application to physical systems of a wavelet-based coherence, which does not depend on the stationarity of the signals, is highly relevant. This paper fully develops the method of wavelet coherence and its statistical properties so that it can be practically applied to continuous neural signals. In realistic simulations, we show that, in contrast to Fourier coherence, wavelet coherence can detect short, significant episodes of coherence between non-stationary neural signals. This method can be directly applied for an 'online' quantification of the instantaneous coherence between two signals.

Algorithms↗
PubMed2006

A time-frequency based electromyographic analysis technique for use in cerebral palsy.

Surface electromyography (sEMG) is part of an instrumented gait assessment, however, the interpretation of the data in a clinically meaningful manner is often limited to the extraction of individual sEMG characteristics. The purpose of this study was to develop an assessment methodology using sEMG time and frequency characteristics extracted using wavelet analyses to provide clinically relevant information in children with cerebral palsy (CP). A retrospective study was conducted with 37 children (16 children with typical development (TD) and 21 children with spastic CP). sEMG signals were examined from selected musculature of the lower extremities during level ground walking. Wavelet analysis techniques, along with functional principal component analyses, were employed to calculate a sEMG index. The data indicated a grouping in the EMG index based on the level of motor impairment and the clinical diagnosis of spastic hemiplegia or diplegia. Further analyses of the index exhibited moderate to high (r=-0.43 to -0.74 and r=0.62-0.65) correlations with the existing gait kinetics, kinematics, and clinical measures of motor impairment, and was sensitive to walking ability according to the Gross Motor Functional Classification Scale (GMFCS). Overall, this methodology may have the potential to provide additional insight into the outcome of a clinical intervention that was not available previously, and may find use as a predictive tool that can be utilized for clinical decision making.

Adolescent↗
PubMed2004

[A new ST segment analysis scheme for Holter system].

A new ST segment analysis scheme is developed for helping the doctors to browse the electrocardiogram (ECG) signals rapidly and then give a correct diagnosis. The preprocessing consists of baseline wander attenuation using median filter, high frequency noise rejection using order statistic filter, and then QRS complexes detection using wavelet analysis. In this paper, after the beginnings and the ends of the ST segments are mutually chosen by doctor, we compute the total deviations between ST segments and the modified baselines using mean value, and then plot the whole trend of the deviations. Doctors can browse the original ECG signals handily by our browsing system, and then give a diagnosis colligating other clinic features of the patient.

Electrocardiography, Ambulatory↗
PubMed2001

Muscle activity in the leg is tuned in response to ground reaction forces.

During walking and running, the human body reacts to its external environment. One such response is to the impact forces that occur at heel strike. This study tested previous speculation that the levels of muscle activity in the lower extremities are adjusted in response to the loading rate of the impact forces. A pendulum apparatus was used to deliver repetitive impacts to the heels of 20 subjects. Impact forces were of similar magnitude to those experienced during running, but the loading rate was varied by 13% using different materials in the subjects' shoes. Myoelectric patterns were measured in the tibialis anterior, medial gastrocnemius, vastus medialis, and biceps femoris muscles. Wavelet analysis was used to resolve intensity of the myoelectric patterns into time and frequency space. Substantial and significant differences in the myoelectric activity occurred between the impact conditions for the 50 ms before and the 50 ms after impact, reaching 3 ms in timing, 16% in wavelet number, and 154% in the intensity of the muscle activity.

Adult↗
PubMed2000

Renal SNA as the primary mediator of slow oscillations in blood pressure during hemorrhage.

Blood pressure contains a distinct low-frequency oscillation often termed the Mayer wave. This oscillation is caused by the action of the sympathetic nervous system on the vasculature and results from time delays in the baroreflex feedback loop for the control of sympathetic nerve activity (SNA) in response to changes in blood pressure. In this study, we used bilateral renal denervation to test the hypothesis that it is SNA to the kidney that contributes a large portion of the vascular resistance associated with changes in the strength of the slow oscillation in blood pressure. In conscious rabbits, SNA and blood pressure were measured during hemorrhage (blood withdrawal at 1.35 ml. min(-1). kg(-1) for 20 min). Spectral analysis identified a strong increase in power at 0.3 Hz in SNA and blood pressure in the initial compensatory phase of hemorrhage before blood pressure started to fall. However, in a separate group of renal denervated rabbits, although the power of the 0.3-Hz oscillation under control conditions in blood pressure was similar, it was not altered during hemorrhage. Wavelet analysis revealed the development of low-frequency oscillations at 0.1 Hz in both intact and denervated animals. In conclusion, we propose that changes in the strength of the oscillation at 0.3 Hz in arterial pressure during hemorrhage are primarily mediated by sympathetic activity directed to the kidney.

Animals↗
PubMed2005

Ovarian cancer identification based on dimensionality reduction for high-throughput mass spectrometry data.

MOTIVATION: High-throughput and high-resolution mass spectrometry instruments are increasingly used for disease classification and therapeutic guidance. However, the analysis of immense amount of data poses considerable challenges. We have therefore developed a novel method for dimensionality reduction and tested on a published ovarian high-resolution SELDI-TOF dataset. RESULTS: We have developed a four-step strategy for data preprocessing based on: (1) binning, (2) Kolmogorov-Smirnov test, (3) restriction of coefficient of variation and (4) wavelet analysis. Subsequently, support vector machines were used for classification. The developed method achieves an average sensitivity of 97.38% (sd = 0.0125) and an average specificity of 93.30% (sd = 0.0174) in 1000 independent k-fold cross-validations, where k = 2, ..., 10. AVAILABILITY: The software is available for academic and non-commercial institutions.

Algorithms↗
PubMed2002

Automatic P-wave analysis of patients prone to atrial fibrillation.

A method is presented for automatic analysis of the P-wave, based on lead II of a 12-lead standard ECG, in resting conditions during a routine examination for the detection of patients prone to atrial fibrillation (AF), one of the most prevalent arrhythmias. First, the P-wave was delineated, and this was achieved in two steps: the detection of the QRS complexes for ECG segmentation, using a wavelet analysis method, and a hidden Markov model to represent one beat of the signal for P-wave isolation. Then, a set of parameters to detect patients prone to AF was calculated from the P-wave. The detection efficiency was validated on an ECG database of 145 patients, including a control group of 63 people and a study group of 82 patients with documented AF. A discriminant analysis was applied, and the results obtained showed a specificity and a sensitivity between 65% and 70%.

Adult↗
PubMed2004

An algorithm for the detection of individual breaths from the pulse oximeter waveform.

OBJECTIVES: To determine if wavelet analysis techniques can be used to reliably identify individual breaths from the photoplethysmogram (PPG). METHODS: Photoplethysmograms were obtained from 22 healthy adult volunteers timing their respiration rate in synchronisation with a metronome. A secondary timing signal was obtained by asking the volunteers to actuate a small push button switch, held in their right hand, in synchronisation with their respiration. Each PPG was analyzed using primary wavelet decomposition and two new, related, secondary decompositions to determine the accuracy of individual breath detection. RESULTS: The optimal breath capture was obtained by manually polling the three techniques, allowing detection of 466 out of the 472 breaths studied; a detection rate of 98.7% with no false positive breaths detected. CONCLUSION: Our technique allows the accurate capture of individual breaths from the photoplethysmogram, and leads the way for developing a simple non-invasive combined respiration and saturation monitor.

Algorithms↗
PubMed2006

Megakaryocytic features useful for the diagnosis of myeloproliferative disorders can be obtained by a novel unsupervised software analysis.

An unsupervised method for megakaryocyte detection and analysis is proposed, in order to validate supplementary tools which can be of help in supporting the pathologist in the classification of Philadelphia negative chronic myeloproliferative disorders with thrombocytosis. The experiment was conducted on high power magnification photomicrographs taken from hematoxylin-and-eosin 3 micrometer thick sections of formalin fixed, paraffin embedded bone marrow biopsies from patients with reactive thrombocytosis or chronic myeloproliferative disorders. Each megakaryocyte has been isolated in the photos through an image segmentation process, mainly based on mathematical morphology and wavelet analysis. A set of features (e.g. area, perimeter and fractal dimension of the cell and its nucleus, shape complexity via elliptic Fourier transform, and so on) is used to characterize the disorders and discriminate between essential thrombocythemia and idiopathic myelofibrosis. Features related to the general contour of the cell like cytoplasmic area and perimeter are good markers in distinguishing between normal or reactive and pathologic megakaryocytes while nuclear features and global circularity are helpful in the differential diagnosis between ET and prefibrotic IMF. The method proposed should be considered as a fast preprocessing tool for the diagnostic phase and its use can be extended to solve different object recognition problems.

Bone Marrow Cells↗
PubMed2003

Wavelet to predict bacterial ori and ter: a tendency towards a physical balance.

BACKGROUND: Chromosomal DNA replication in bacteria starts at the origin (ori) and the two replicores propagate in opposite directions up to the terminus (ter) region. We hypothesize that the two replicores need to reach ter at the same time to maintain a physical balance; DNA insertion would disrupt such a balance, requiring chromosomal rearrangements to restore the balance. To test this hypothesis, we needed to demonstrate that ori and ter are in a physical balance in bacterial chromosomes. Using wavelet analysis, we documented GC skew, AT skew, purine excess and keto excess on the published bacterial genomic sequences to locate the turning (minimum and maximum) points on the curves. Previously, the minimum point had been supposed to correlate with ori and the maximum to correlate with ter. RESULTS: We observed a strong tendency of the bacterial chromosomes towards a physical balance, with the minima and maxima corresponding to the known or putative ori and ter and being about half chromosome separated in most of the bacteria studied. A nonparametric method based on wavelet transformation was employed to perform significance tests for the predicted loci. CONCLUSIONS: The wavelet approach can reliably predict the ori and ter regions and the bacterial chromosomes have a strong tendency towards a physical balance between ori and ter.

AT Rich Sequence↗
PubMed2004

A novel spectral ultrasonic differentiation method for marking regions of interest in biological tissue: in vitro results for prostate.

OBJECTIVE: The aim of the present study was to evaluate the effectiveness of a new method of spectral analysis of the radiofrequency (RF) ultrasonic echo signal in discriminating neoplastic from non-neoplastic tissue of the prostate gland. MATERIAL AND METHODS: The proposed method was previously set up on ten prostatic glands where cancer had been detected by histology in order to correlate the tumour areas with specific spectral parameters. In the present study sixty prostate specimens of patients undergoing radical retropubic prostatectomy for clinically localized prostate cancer were examined. The surgically removed prostate glands were scanned using an echo signal acquisition apparatus and the spectral parameters were obtained by the wavelet transform. The echographic scans of all cases were then compared with the whole-mount histological sections of the prostate in order to evaluate sensitivity and specificity of the proposed method. RESULTS: The sensitivity and specificity for cancer detection were 93% and 91%, respectively. The specificity was invalidated by the fact that in some of the cases studied, the tumour was located in areas of benign prostatic hyperplasia (BPH). As for the sensitivity, of the three false negative cases two were due to the coexistence of cancer foci and BPH. CONCLUSIONS: Our proposed method, named WAMBLE (Wavelet Analysis Multi Band Local Estimator), is accurate in detecting prostate cancer. Further in vivo studies are warranted to confirm the clinical value of this technique.

Diagnosis, Differential↗
PubMed2002

Hair-MAP: a prototype automated system for forensic hair comparison and analysis.

This paper demonstrates the feasibility of the automation of forensic hair analysis and comparison task using neural network explanation systems (NNESs). Our system takes as input microscopic images of two hairs and produces a classification decision as to whether or not the hairs came from the same person. Hair images were captured using a NEXTDimension video board in a NEXTDimension color turbo computer, connected to a video camera. Image processing was done on an SGI indigo workstation. Each image is segmented into a number of pieces appropriate for classification of different features. A variety of image processing techniques are used to enhance this information. Use of wavelet analysis and the Haralick texture algorithm to pre-process data has allowed us to compress large amounts of data into smaller, yet representative data. Neural networks are then used for feature classification. Finally, statistical tests determine the degree of match between the resulting collection of hair feature vectors. An important issue in automation of any task in criminal investigations is the reliability and understandability of the resulting system. To address this concern, we have developed methods to facilitate explanation of neural network's behavior using a decision tree. The system was able to achieve a performance of 83% hair match accuracy, using 5 of the 21 morphological characteristics used by experts. This shows promise for the usefulness of a fuller scale system. While an automated system would not replace the expert, it would make the task easier by providing a means for pre-processing the large amount of data with which the expert must contend.

Algorithms↗
PubMed1994

Investigating the effects of vasodilator drugs on the turbulent sound caused by femoral artery stenosis using short-term Fourier and wavelet transform methods.

In this study, the effects of vasodilator drugs on the turbulent sound generation mechanisms during femoral artery stenoses were investigated using the wavelet analysis of the turbulent sounds to characterize these sounds before and after the injection of vasodilator drugs. Results showed that the injection of drugs drastically improved the diagnostic performance of the turbulent sounds in detecting stenoses by increasing the signal-to-noise ratio of the sounds. Results also suggested that the sound above 250 Hz was drastically increased in response to the injection of the vasodilator drug for the partially occluded cases. The turbulence sounds caused by partially occluded femoral arteries are directly related to the slope of baseline of blood flow and to the velocity of the flow. For the 0% occlusion case, initially, sounds were produced with the injection of drugs. However, the sounds totally disappeared when the slope of average blood flow was zero. These results show that the diagnostic performance of diastolic heart sounds associated with occluded arteries can be improved by using vasodilator drugs, which increase the acoustic energy in the first and second wavelet bandwidths due to the turbulence. The short-term Fourier transform (STFT) method was also applied to the same data base. Results using the STFT showed somewhat similar power distributions in that the acoustical power above 250 Hz was increased after the injection of drugs for the occluded cases. However, the WT method provided better time-frequency resolution than the STFT method, showing details of the change in the frequency characteristics with respect to time after the injection of drug.

Animals↗
PubMed2005

Statistical analysis of correlations and intermittency of a turbulent rotating column in a magnetoplasma device.

A statistical analysis of density fluctuations in a cylindrical non-fusion device is performed. The experimental setup is implemented in order to reach a turbulent behavior of the linear plasma column. Two different turbulent regimes are obtained corresponding to two selected sets of values for the discharge parameters. The first regime displays a rotating column characterized by the presence of a shear layer separating the plasma bulk from the tenuous plasma in the shadow of the limiter, the latter showing a strong intermittent behavior and superdiffusion. The second regime corresponds to a weakly rotating column in which coherence is lost in the plasma bulk and a standard diffusive process takes place in the shadow region. These findings are supported by the calculation of the Hurst's exponent using wavelet-analysis techniques. Furthermore the intermittent behavior is characterized and related to the diffusive process. Finally the shape of the probability distribution function of density fluctuations seems to be well described by an analytical form suggested on the basis of Tsallis generalized statistics.

Journal Article↗
PubMed2006

Cardiac autonomic modulation following high-intensity static muscle contractions.

BACKGROUND: The purpose of this investigation was to examine cardiac autonomic modulation, as measured by wavelet analysis of heart rate variability, following a series of high-intensity static muscle contractions. METHODS: After 10 minutes of rest, electrocardiograms (ECGs) were collected in 17 participants (age, 24.5 +/- 1 yr) 2.5 minutes before (REST) and 10 minutes after a series of static contractions of the knee extensors. Participants performed contractions with the nondominant leg (knee fixed at 90 degrees) at either 70% or 85% (randomized order) of their maximal voluntary contraction (MVC) on two separate visits. The postexercise ECGs were further divided into four consecutive 2.5-minute segments (POST 1-POST 4) to evaluate the time course of any possible autonomic changes after exercise. Each 2.5-minute segment was evaluated for the standard deviation of normal RR intervals (SDNN) and the percentage of successive RR intervals that differed by more than 50 ms (pNN50). Frequency-domain indices were obtained via wavelet transformation giving coefficients that reflected high- and low-frequency fluctuations in heart period (HFw and LFw). RESULTS: SDNN was elevated during POST-1 and pNN50 was reduced during POST-3 and POST-4 (P < 0.05) compared to REST for both intensities. Furthermore, HFw and LFw were increased during POST-1 and reduced during POST-3 and POST-4 compared to REST for both intensities (P < 0.05). CONCLUSION: These data suggest that complex alterations cardiac autonomic modulation exist for at least 10 minutes following a series of high-intensity static contractions performed at either 70% or 85% of MVC.

Adult↗
PubMed2006

EEG analysis using wavelet-based information tools.

Wavelet-based informational tools for quantitative electroencephalogram (EEG) record analysis are reviewed. Relative wavelet energies, wavelet entropies and wavelet statistical complexities are used in the characterization of scalp EEG records corresponding to secondary generalized tonic-clonic epileptic seizures. In particular, we show that the epileptic recruitment rhythm observed during seizure development is well described in terms of the relative wavelet energies. In addition, during the concomitant time-period the entropy diminishes while complexity grows. This is construed as evidence supporting the conjecture that an epileptic focus, for this kind of seizures, triggers a self-organized brain state characterized by both order and maximal complexity.

Adolescent↗
PubMed2002

Shift-invariant, DWT-based "projection" method for estimation of ultrasound pulse power spectrum.

An approach to computing estimates of the ultrasound pulse spectrum from echo-ultrasound RF sequences, measured from biological tissues, is proposed. It is computed by a "projection" algorithm based on the Discrete Wavelet Transform (DWT) using averaging over a range of linear shifts. It is shown that the robust, shift invariant estimate of the ultrasound pulse power spectrum can be obtained by the projection of RF line log spectrum on an appropriately chosen subspace of L2(R) (i.e., the space of square-integrable functions) that is spanned by a redundant collection of compactly supported, scaling functions. This redundant set is formed from the traditional (in Wavelet analysis) orthogonal set of scaling functions and also by all its linear (discrete) shifts. A proof is given that the estimate, so obtained, could be viewed as the average of the orthogonal projections of the RF line log spectrum, computed for all significant linear shifts of the RF line log spectrum in frequency domain. It implies that the estimate is shift-invariant. A computationally efficient scheme is presented for calculating the estimate. Proof is given that the averaged, shift-invariant estimate can be obtained simply by a convolution with a kernel, which can be viewed as the discretized auto-correlation function of the scaling function, appropriate to the particular subspace being considered. It implies that the computational burden is at most O(n log2 n), where n is the problem size, making the estimate quite suitable for real-time processing. Because of the property of the wavelet transform to suppress polynomials of orders lower than the number of the vanishing moments of the wavelet used, the presented approach can be considered as a local polynomial fitting. This locality plays a crucial role in the performance of the algorithm, improving the robustness of the estimation. Moreover, it is shown that the "averaging" nature of the proposed estimation allows using (relatively) poorly regular wavelets (i.e., short filters), without affecting the estimation quality. The latter is of importance whenever the number of calculations is crucial.

Algorithms↗
PubMed2001

Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: a feasibility study.

BACKGROUND: Differentiation of melanoma from melanocytic nevi is difficult even for skin cancer specialists. This motivates interest in computer-assisted analysis of lesion images. OBJECTIVE: Our purpose was to offer fully automatic differentiation of melanoma from dysplastic and other melanocytic nevi through multispectral digital dermoscopy. METHOD: At 4 clinical centers, images were taken of pigmented lesions suspected of being melanoma before biopsy. Ten gray-level (MelaFind) images of each lesion were acquired, each in a different portion of the visible and near-infrared spectrum. The images of 63 melanomas (33 invasive, 30 in situ) and 183 melanocytic nevi (of which 111 were dysplastic) were processed automatically through a computer expert system to separate melanomas from nevi. The expert system used either a linear or a nonlinear classifier. The "gold standard" for training and testing these classifiers was concordant diagnosis by two dermatopathologists. RESULTS: On resubstitution, 100% sensitivity was achieved at 85% specificity with a 13-parameter linear classifier and 100%/73% with a 12-parameter nonlinear classifier. Under leave-one-out cross-validation, the linear classifier gave 100%/84% (sensitivity/specificity), whereas the nonlinear classifier gave 95%/68%. Infrared image features were significant, as were features based on wavelet analysis. CONCLUSION: Automatic differentiation of invasive and in situ melanomas from melanocytic nevi is feasible, through multispectral digital dermoscopy.

Diagnosis, Differential↗