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At least 793 records · Page 44Linked to original sources
PubMed2001

Myo-electric signals to augment speech recognition.

It is proposed that myo-electric signals can be used to augment conventional speech-recognition systems to improve their performance under acoustically noisy conditions (e.g. in an aircraft cockpit). A preliminary study is performed to ascertain the presence of speech information within myo-electric signals from facial muscles. Five surface myo-electric signals are recorded during speech, using Ag-AgCl button electrodes embedded in a pilot oxygen mask. An acoustic channel is also recorded to enable segmentation of the recorded myo-electric signal. These segments are processed off-line, using a wavelet transform feature set, and classified with linear discriminant analysis. Two experiments are performed, using a ten-word vocabulary consisting of the numbers 'zero' to 'nine'. Five subjects are tested in the first experiment, where the vocabulary is not randomised. Subjects repeat each word continuously for 1 min; classification errors range from 0.0% to 6.1%. Two of the subjects perform the second experiment, saying words from the vocabulary randomly; classification errors are 2.7% and 10.4%. The results demonstrate that there is excellent potential for using surface myo-electric signals to enhance the performance of a conventional speech-recognition system.

Adult↗
PubMed2006

Spectral and wavelet based assessment of congestive heart failure patients.

Heart rate variability (HRV) can be quantified, among others, in the spectral and wavelet domain. The wavelet transform (WT) is an alternative method for the analysis of non-stationary signals. Some recent work shows that the scale-dependent WT standard deviation of the R-R intervals of human ECG can be used to distinguish patients with certain forms of cardiac pathological function from normal subjects. In this paper, we show an explicit relationship between variance of WT and corresponding spectral measure. Also, the statistics of the estimator for variance of WT is obtained. Numerical simulations support the theoretical results. By comparing expected value and variance and spectral measures, we conclude that WT measures are able to diagnose certain cardiac system function.

Analysis of Variance↗
PubMed2003

Experimental analysis of heart rate variability of long-recording electrocardiograms in normal subjects and patients with coronary artery disease and normal left ventricular function.

The heart rate signal contains valuable information about cardiac health, which cannot be extracted without the use of appropriate computerized methods. This paper presents an analysis of various electrocardiograms, the aim of which is to categorize them into two distinct groups. Group A represents young male subjects with no prior occurrence of coronary disease events and Group B represents middle-aged male subjects who have symptomatic coronary artery disease without myocardial infarction and whose 12-lead ECGs do not contain any abnormalities, thus wrongly indicating a normal subject. Electrocardiographic recordings are approximately 2h in length and acquired under conditions that favor the stationarity of collected data. Linear and nonlinear characteristics are studied by applying several techniques including Fourier analysis, Correlation Dimension Estimation, Approximate Entropy, and the Discrete Wavelet Transform. The small variations of the diagnostic information given by each one of the methods as well as the slightly different conclusions among similar studies indicate the necessity of further investigation, combined use, and complementary application of different approaches.

Adult↗
PubMed2005

Transient gamma-band response is dissociated from sensory memory as reflected by MMN.

The auditory gamma-band transient oscillatory response has been considered to reflect early cognitive processing and attention triggering, as has been suggested of the mismatch negativity (MMN). We examined whether the auditory gamma-band response was related to sensory memory as reflected by MMN. During the electroencephalogram (EEG) recordings, approximately 2000 click sounds were presented to nine healthy adult subjects with constant SOA of 120 or 170 ms in an ignored condition. At a probability of 10%, a click sound was randomly omitted from the stimulus sequence. EEG epochs responding to omitted clicks and to click sounds were averaged for analysis, respectively, and then those were convoluted by Gabor wavelet for the gamma-band response calculation. The MMN to a deviant omission in a sequence of click sounds was elicited with SOA of 120 ms which was shorter than the duration of temporal window of integration, whereas no MMN was elicited with SOA of 170 ms. In contrast with the MMN, the transient gamma-band response clearly commenced after the stimuli but not after the omissions, regardless whether SOA was short or long. The findings indicate that the brain process underlying the transient gamma-band response should be dissociated from the sensory memory function.

Adult↗
PubMed2000

Event-related desynchronization during an auditory oddball task.

OBJECTIVE: The present study addressed what kind of mental processes would be presented by the event-related desynchronization (ERD) relevant to the stimuli of an auditory oddball count task. METHODS: Electroencephalogram (EEG) was recorded from nine healthy subjects while target tones (2000 Hz, P = 0.2) and non-target tones (1000 Hz, P = 0.8) were presented randomly with constant stimulus onset asynchrony (SOA) of 3.3 s. To improve time resolution of ERD analysis, obtained EEG epochs were digitally convoluted by Gabor wavelet and averaged respectively. RESULTS: For target stimulus, prominent ERD was observed in left parieto-occipital areas (peak latency: 400-600 ms), but there were no significant ERD for non-target stimulus. CONCLUSION: Our result suggests that magnitude of ERD would reflect amount of mental effort which was associated with intentional and voluntary processes rather than automatically sensory process.

Acoustic Stimulation↗
PubMed2001

Long-range correlations in genomic DNA: a signature of the nucleosomal structure.

We use the "wavelet transform microscope" to carry out a comparative statistical analysis of DNA bending profiles and of the corresponding DNA texts. In the three kingdoms, one reveals on both signals a characteristic scale of 100-200 bp that separates two different regimes of power-law correlations (PLC). In the small-scale regime, PLC are observed in eukaryotic, in double-strand DNA viral, and in archaeal genomes, which contrasts with their total absence in the genomes of eubacteria and their viruses. This strongly suggests that small-scale PLC are related to the mechanisms underlying the wrapping of DNA in the nucleosomal structure. We further speculate that the large scale PLC are the signature of the higher-order structure and dynamics of chromatin.

Biophysical Phenomena↗
PubMed2006

[Stellar spectral recognition based on wavelet de-noising and SVM].

The present paper describes a new technique for stellar spectral recognition. Considering the characteristics of stellar spectral data, support vector machine (SVM) was adopted to build a recognition system as kernel. Because stellar spectral data sets are usually extremely noisy, the correct classification rate of direct applying SVM is low. Consequently, wavelet de-noising method was proposed to reduce noise first and extract the main characteristics of stellar spectra. Then SVM was used for the recognition. Based on the real-world stellar spectra contributed by Jacoby et al. (1984), it has proven that there will be a better performance using this composite classifier which combines wavelet and SVM than using SVM with principle component analysis data dimension reduction technique. From the experiment of comparison of discriminant analysis and SVM based on stellar spectra for evolutionary synthesis, we can see that the correct classification rate of SVM is higher than that of discriminant analysis methods, and a well generalization ability is achieved.

English Abstract↗
PubMed2001

Early seizure detection.

For patients with medically intractable epilepsy, there have been few effective alternatives to resective surgery, a destructive, irreversible treatment. A strategy receiving increased attention is using interictal spike patterns and continuous EEG measurements from epileptic patients to predict and ultimately control seizure activity via chemical or electrical control systems. This work compares results of seven linear and nonlinear methods (analysis of power spectra, cross-correlation, principal components, phase, wavelets, correlation integral, and mutual prediction) in detecting the earliest dynamical changes preceding 12 intracranially-recorded seizures from 4 patients. A method of counting standard deviations was used to compare across methods, and the earliest departures from thresholds determined from non-seizure EEG were compared to a neurologist's judgement. For these data, the nonlinear methods offered no predictive advantage over the linear methods. All the methods described here were successful in detecting changes leading to a seizure between one and two minutes before the first changes noted by the neurologist, although analysis of phase correlation proved the most robust. The success of phase analysis may be due in part to its complete insensitivity to amplitude, which may provide a significant source of error.

Brain Mapping↗
PubMed1997

Impact during equine locomotion: techniques for measurement and analysis.

Impact is implicated in the development of several types of musculoskeletal injury in the horse. Characterisation of impact experienced during strenuous exercise is an important first step towards understanding the mechanism for injury. Measurement and analysis of large, short duration impacts is difficult. The measurement system must be able to record transient peaks and high frequencies accurately. The analysis technique must be able to characterise the impact signal in time and frequency. This paper presents a measurement system and analysis technique for the characterisation of large impacts. A piezo-electric accelerometer was securely mounted on the dorsal surface of the horses hoof. Saddle mounted charge amplifiers and a 20 m coaxial cable transferred these data to a PC based logging system. Data were down-loaded onto a UNIX workstation and analysed using a proprietary statistics package. The values of parameters calculated from the time series data were comparable to those of other authors. A wavelet decomposition showed that the frequency profile of the signal changed with time. While most spectral energy was seen at impact, a significant amount of energy was contained in the signal immediately following impact. Over 99% of this energy was contained in frequencies less than 1250 Hz. The sampling rate and the frequency response of a measurement system for recording impact should be chosen carefully to prevent loss or corruption of data. Time scale analysis using a wavelet decomposition is a powerful technique which can be used to characterise impact data. The use of contour plots provides a highly visual representation of the time and frequency localisation of power during impact.

Acceleration↗
PubMed2000

Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study.

In this paper, we introduce the nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner-Ville distribution, the Choi-Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates provided by the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined.

Action Potentials↗
PubMed1995

Classification of mass and normal breast tissue on digital mammograms: multiresolution texture analysis.

We investigated the feasibility of using multiresolution texture analysis for differentiation of masses from normal breast tissue on mammograms. The wavelet transform was used to decompose regions of interest (ROIs) on digitized mammograms into several scales. Multiresolution texture features were calculated from the spatial gray level dependence matrices of (1) the original images at variable distances between the pixel pairs, (2) the wavelet coefficients at different scales, and (3) the wavelet coefficients up to certain scale and then at variable distances between the pixel pairs. In this study, 168 ROIs containing biopsy-proven masses and 504 ROIs containing normal parenchyma were used as the data set. The mass ROIs were randomly and equally divided into training and test groups along with corresponding normal ROIs from the same film. Stepwise linear discriminant analysis was used to select optimal features from the multiresolution texture feature space to maximize the separation of mass and normal tissue for all ROIs. We found that texture features at large pixel distances are important for the classification task. The wavelet transform can effectively condense the image information into its coefficients. With texture features based on the wavelet coefficients and variable distances, the area Az under the receiver operating characteristic curve reached 0.89 and 0.86 for the training and test groups, respectively. The results demonstrate that a linear discriminant classifier using the multiresolution texture features can effectively classify masses from normal tissue on mammograms.

Biopsy↗
PubMed2000

Multivariate statistical analysis of flat vowel spectra with a view to characterizing dysphonic voices.

The aim of this article is to show how dysphonic voices can be characterized by means of a multivariate statistical analysis of flat vowel spectra. The spectral contour was obtained by means of a wavelet transform of the logarithmic magnitude spectrum, which was subsequently flattened to remove interspeaker variability related to the excitation and vocal tract filter functions. The results of the statistical analysis of flat spectra were the following. Firstly, principal components analysis produced markers that separated noisy from clean spectra. Secondly, the heuristic search for harmonic peaks or interharmonic dips could be omitted. Thirdly, conventional spectral markers of noise appeared as special instances of the markers that were derived statistically. Fourthly, the levels of visually assigned hoarseness and the first two principal components were significantly correlated. The assignment of different levels of (visual) hoarseness to different vowel timbres could be explained by the variability associated with the spectral contour.

Algorithms↗
PubMed1998

Quantification of plasma lipoprotein fractions by wavelet transform time-domain data processing of the proton nuclear magnetic resonance methylene spectral region.

Quantitative analysis of lipoprotein major fractions, LDL, VLDL and HDL, is of great interest for medical purposes, for instance in liver or heart diseases, diet management or cancer. The presently available biochemical methods require time consuming ultracentrifugation. A potentially automated method is proposed, using time domain quantification by Wavelet Transform (WT-NMR) method. The aim of the present study was to evaluate, on a preliminary series of nine human plasmas, the potential interest of WT-NMR in the quantification of both NMR-visible lipids and total lipoprotein fractions. The correlation coefficients between low and intermediate density (LDL+IDL), very low density (VLDL) and high density (HDL) lipoprotein visible lipid quantifications, obtained on nine human plasmas with WT-NMR and standard biochemical methods, were 0.79, 0.84 and 0.92, respectively. For the total lipoprotein assay, i.e. including an estimation of non NMR-visible protein and free cholesterol, the correlation between WT-NMR and the biochemistry were 0.87 for LDL+IDL, 0.81 for VLDL and 0.88 for HDL.

Blood Proteins↗
PubMed1996

Temporal and spatial analysis of potential maps via multiresolution decompositions.

Cardiac potentials recorded on the epicardium or the body surface by an array of electrodes are usually analyzed either as spatial distributions or temporal waveforms. Thus, the analysis often involves temporal descriptors (eg. max dV/dt) or spatial descriptors (eg. location of local extrema) only. The best known transform technique that has been applied to these data that combines both spatial and temporal characteristics is the Karhunen-Loeve transform, a global transform applied to temporal and/or spatial bases obtained by statistical analysis of a database. As an alternative, multiresolution decompositions and related wavelet-type transforms have recently seen great development in signal processing and related fields. They offer flexibility, employing transformations onto local (rather than global) and fixed (rather than data-dependent) databases, and allow transformation of distributions, waveforms, or both, as desired. The utility of this method as applied to temporal and spatial segmentation and analysis of map data from both epicardial plaques and body surface potentials recorded during percutaneous transluminal coronary angioplasty is illustrated.

Body Surface Potential Mapping↗
PubMed2001

Representation of strong baseline contributions in 1H MR spectra.

A comparison is made between two optimization procedures and two data models for automated analysis of in vivo proton MR spectra of brain, typical of that obtained using MR spectroscopic imaging at 1.5 Tesla. First, a shift invariant wavelet filter is presented that provides improved performance over a conventional wavelet filter method for characterizing smoothly varying baseline signals. Next, two spectral fitting methods are described: an iterative spectral analysis method that alternates between optimizing a parametric description of metabolite signals and nonparametric characterization of baseline contributions, and a single-pass method that optimizes a complete spectral and baseline model. Both methods are evaluated using wavelet and spline models of the baseline function. Results are shown for Monte Carlo simulations of data representative of both long and short TE, in vivo 1H acquisitions.

Brain↗
PubMed2004

The relationship between the auditory brain-stem response and its reconstructed waveforms following discrete wavelet transformation.

OBJECTIVE: To examine the relationship between the auditory brain-stem response (ABR) and its reconstructed waveforms following discrete wavelet transformation (DWT), and to comment on the resulting implications for ABR DWT time-frequency analysis. METHODS: ABR waveforms were recorded from 120 normal hearing subjects at 90, 70, 50, 30, 10 and 0 dBnHL, decomposed using a 6 level discrete wavelet transformation (DWT), and reconstructed at individual wavelet scales (frequency ranges) A6, D6, D5 and D4. These waveforms were then compared for general correlations, and for patterns of change due to stimulus level, and subject age, gender and test ear. RESULTS: The reconstructed ABR DWT waveforms showed 3 primary components: a large-amplitude waveform in the low-frequency A6 scale (0-266.6 Hz) with its single peak corresponding in latency with ABR waves III and V; a mid-amplitude waveform in the mid-frequency D6 scale (266.6-533.3 Hz) with its first 5 waves corresponding in latency to ABR waves I, III, V, VI and VII; and a small-amplitude, multiple-peaked waveform in the high-frequency D5 scale (533.3-1066.6 Hz) with its first 7 waves corresponding in latency to ABR waves I, II, III, IV, V, VI and VII. Comparisons between ABR waves I, III and V and their corresponding reconstructed ABR DWT waves showed strong correlations and similar, reliable, and statistically robust changes due to stimulus level and subject age, gender and test ear groupings. Limiting these findings, however, was the unexplained absence of a small number (2%, or 117/6720) of reconstructed ABR DWT waves, despite their corresponding ABR waves being present. CONCLUSIONS: Reconstructed ABR DWT waveforms can be used as valid time-frequency representations of the normal ABR, but with some limitations. In particular, the unexplained absence of a small number of reconstructed ABR DWT waves in some subjects, probably resulting from 'shift invariance' inherent to the DWT process, needs to be addressed. SIGNIFICANCE: This is the first report of the relationship between the ABR and its reconstructed ABR DWT waveforms in a large normative sample.

Adult↗
PubMed2005

Wavelet transforms and the ECG: a review.

The wavelet transform has emerged over recent years as a powerful time-frequency analysis and signal coding tool favoured for the interrogation of complex nonstationary signals. Its application to biosignal processing has been at the forefront of these developments where it has been found particularly useful in the study of these, often problematic, signals: none more so than the ECG. In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the continuous and the discrete transform are considered in turn.

Arrhythmias, Cardiac↗
PubMed2006

Global universe anisotropy probed by the alignment of structures in the cosmic microwave background.

We question the global universe isotropy by probing the alignment of local structures in the cosmic microwave background (CMB) radiation. The original method proposed relies on a steerable wavelet decomposition of the CMB signal on the sphere. The analysis of the first-year Wilkinson Microwave Anisotropy Probe data identifies a mean preferred plane with a normal direction close to the CMB dipole axis, and a mean preferred direction in this plane, very close to the ecliptic poles axis. Previous statistical anisotropy results are thereby synthesized, but further analyses are still required to establish their origin.

Journal Article↗