Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Continuous transformation”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources
PubMed2006

Time and frequency domain responses of the mechanomyogram and electromyogram during isometric ramp contractions: a comparison of the short-time Fourier and continuous wavelet transforms.

The purposes of this study were to examine the mechanomyographic (MMG) and electromyographic (EMG) time and frequency domain responses of the vastus lateralis (VL) and rectus femoris (RF) muscles during isometric ramp contractions and compare the time-frequency of the MMG and EMG signals generated by the short-time Fourier transform (STFT) and continuous wavelet transform (CWT). Nineteen healthy subjects (mean+/-SD age=24+/-4 years) performed two isometric maximal voluntary contractions (MVCs) before and after completing 2-3, 6-s isometric ramp contractions from 5% to 100% MVC with the right leg extensors. MMG and surface EMG signals were recorded from the VL and RF muscles. Time domains were represented as root mean squared amplitude values, and time-frequency representations were generated using the STFT and CWT. Polynomial regression analyses indicated cubic increases in MMG amplitude, MMG frequency, and EMG frequency, whereas EMG amplitude increased quadratically. From 5% to 24-28% MVC, MMG amplitude remained stable while MMG frequency increased. From 24-28% to 76-78% MVC, MMG amplitude increased rapidly while MMG frequency plateaued. From 76-78% to 100% MVC, MMG amplitude plateaued (VL) or decreased (RF) while MMG frequency increased. EMG amplitude increased while EMG frequency changed only marginally across the force spectrum with no clear deflection points. Overall, these findings suggested that MMG may offer more unique information regarding the interactions between motor unit recruitment and firing rate that control muscle force production during ramp contractions than traditional surface EMG. In addition, although the STFT frequency patterns were more pronounced than the CWT, both algorithms produced similar time-frequency representations for tracking changes in MMG or EMG frequency.

Adult↗
PubMed2000

Time-domain quantification of multiple-quantum-filtered (23)Na signal using continuous wavelet transform analysis.

The application of continuous wavelet transform (CWT) analysis technique is presented to analyze multiple-quantum-filtered (MQF) (23)Na magnetic resonance spectroscopy (MRS) data. CWT acts on the free-induction-decay (FID) signal as a time-frequency variable filter. The signal-to-noise ratio (SNR) and frequency resolution of the output filter are locally increased. As a result, MQF equilibrium longitudinal magnetization and the apparent fast and slow transverse relaxation times are accurately estimated. A developed iterative algorithm based on frequency signal detection and components extraction, already proposed, was used to estimate the values of the signal parameters by analyzing simulated time-domain MQF signals and data from an agarose gel. The results obtained were compared to those obtained by measurement of signal height in frequency domain as a function of MQF preparation time and those obtained by a simple time-domain curve fitting. The comparison indicates that the CWT approach provides better results than the other tested methods that are generally used for MQF (23)Na MRS data analysis, especially when the SNR is low. The mean error on the estimated values of the amplitude signal and the apparent fast and slow transverse relaxation times for the simulated data were 2.19, 6. 63, and 16.17% for CWT, signal height in frequency domain, and time-domain curve fitting methods, respectively. Another major advantage of the proposed technique is that it allows quantification of MQF (23)Na signal from a single FID and, thus, reduces the experiment time dramatically.

Magnetic Resonance Spectroscopy↗
PubMed2000

A novel method to calculate the approximate derivative photoacoustic spectrum using continuous wavelet transform.

A novel method based on continuous wavelet transform (CWT) using Haar wavelet function for approximate derivative calculation of analytical signals is proposed and successfully used in processing the photoacoustic signal. An approximate nth derivative of an analytical signal can be obtained by applying n times of the wavelet transform to the signal. The results obtained from four other different methods--the conventional numerical differentiation, the Fourier transform method, the Savitzky-Golay method, and the discrete wavelet transform (DWT) method--were compared with the proposed CWT method; it was demonstrated that all the results are almost the same for signals without noise, but the proposed CWT method is superior to the former four methods for noisy signals. The approximate first and second derivative of the photoacoustic spectrum of Pr(Gly)3Cl3.3H2O and PrCl3.6H2O were obtained using the proposed CWT method; the results are satisfactory.

Journal Article↗
PubMedDate not supplied

Prediction of transmembrane proteins based on the continuous wavelet transform.

A novel method based on continuous wavelet transform (CWT) for predicting the number and location of helices in membrane proteins is presented. Two bacteria proteins are chosen as examples to describe the prediction of transmembrane helices (HTM) by using this method. Selections of an appropriate dilation and hydrophobicity data types are discussed in the text. The results indicate that CWT is a promising approach for the prediction of HTM.

Algorithms↗
PubMed2004

Moiré interferogram phase extraction: a ridge detection algorithm for continuous wavelet transforms.

We present a procedure using continuous wavelet transforms (CWTs) to extract the phase information from moiré interferograms. The relationship between precise ridge detection of the two-dimensional CWT magnitude map and accurate phase extraction is detailed. A cost function is introduced for the adaptive selection of the ridge, and a computationally inexpensive implementation of the cost function ridge detection algorithm is explored with dynamic programming optimization. The results of the proposed ridge detection algorithm on actual interferograms are illustrated. Moreover, the resulting extracted phase is demonstrated to be smooth and accurate. As a result, the sensitivity of the moiré interferometry method is improved to obtain a pixel-by-pixel in-plane strain distribution map.

Journal Article↗
PubMed2004

[Pulse signal processing based on continuous wavelet transform].

Using the common algorithm and the Mellin algorithm of a continuous wavelet transform, we analyzed the pulse signals of 15 heroin addicts and 15 normal persons. With the use of two algorithms, every pulse signal was processed under 4 scales. From the analyzed results, we found that there was significant difference of wavelet transform coefficients in the time interval 0.2 to approximately 0.4 seconds between the heroin addicts and normal persons. In this paper, the critical parameter used to classify heroin addicts and normal persons is given to every algorithm. The research result of this paper shows that the continuous wavelet transform is really an effective method for processing pulse signals.

Algorithms↗
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↗
PubMed2004

Kullback-Leibler clustering of continuous wavelet transform measures of heart rate variability.

Power spectral analysis of beat-to-beat heart rate variability (HRV) has provided a useful means of understanding the interplay between autonomic and cardiovascular functionality. Despite their utility, commonly employed frequency-domain techniques are limited in their prerequisite for stationary signals and their inability to account for temporal changes in the power spectral and/or frequency properties of signals. The purpose of this study is to develop an algorithm that utilizes continuous wavelet transform (CWT) parameters as inputs to a Kohonen self-organizing map (SOM), providing a method of clustering subjects with similar wavelet transform signatures. Continuous interbeat-intervals were recorded (Portapres monitor at 200 Hz) during a perception of affect test in 79 African-American volunteers (ages 21-83), where after a 5-min baseline, participants evaluated emotional expressions in sentences and pictures of faces, followed by a 5-min recovery. Individual HRV biosignals from each session were pre-processed (artifact replacement and signal resampling at 2 Hz) and a CWT was applied (db9 wavelet basis function over 32 scales). Standard deviations of resulting wavelet coefficients at each scale were calculated, normalized, and used as inputs into a SOM with Kullback-Leibler divergence as the dissimilarity measure used for clustering. Differences in subject demographics between two final clusters were assessed via two-independent-groups t-tests or chi-square or Fisher's exact tests of contingency tables. Significant differences were found for age, initial systolic blood pressure, smoking status, and mean s.d. of coefficients in the high frequency band (0.15-0.4 Hz). These findings may have clinical significance and the developed algorithm provides an alternative means of analyzing HRV data originating from populations with complex covariates.

Adult↗
PubMedDate not supplied

Analysis of the second heart sound using continuous wavelet transform.

This paper is concerned with a synthesis study of Continuous Wavelet Transform (CWT) in analysing the second heart sound of the phonocardiogram (PCG). The second heart sound S2 consists of two major components (A2 and P2) with a time delay between them which is very important for a diagnosis. It is shown that CWT provides enough features of these components of time, frequency and time delay to aid diagnosis.

Aortic Coarctation↗
PubMedDate not supplied

Maximum spectrum of continuous wavelet transform and its application in resolving an overlapped signal.

To estimate the number of peaks and to find the individual peak positions in an overlapped signal, a new method called maximum spectrum of continuous wavelet transform (MSCWT) was developed by extracting the maximum coefficients of continuous wavelet transform (CWT). The peak position in MSCWT was the same as that in its original signal. In this process, CWT was performed not on a single dilation but on an appreciation dilation range. To obtain such a range, a new criterion was introduced to choose a center dilation, which was used to form the dilation range. If Cdilation denoted the center dilation, the proper dilation range was [Cdilation -6 +/- 2, Cdilation +1 +/- 1]. The Mexican Hat function was an analytical wavelet. Utilizing the information of the peak number and the position detected by MSCWT, a fitting route was performed to recover the original signal. One simulated and four true overlapped signals, including high performance liquid chromatography (HPLC), ultraviolet-visible (UV) spectrum, and differential pulse voltammetric (DPV), were processed, and the results indicated that MSCWT could detect an overlapped peak number and position, and the curve fitting based on information of MSCWT had a higher accuracy. The proposed method was an efficient one in resolving different types of overlapped signals.

Journal Article↗
PubMed2006

Spatial carrier fringe pattern demodulation by use of a two-dimensional continuous wavelet transform.

A novel technique that uses a fan two-dimensional (2D) continuous wavelet transform (CWT) to phase demodulate fringe patterns is proposed. The fan 2D CWT algorithm is tested by using computer generated and real fringe patterns. The result of this investigation reveals that the 2D CWT technique is capable of successfully demodulating fringe patterns. The proposed algorithm demodulates fringe patterns without the requirement of removing their background illumination prior to the demodulation process. Also, the algorithm is exceptionally robust against speckle noise. The performance of the 2D CWT technique in fringe pattern demodulation is compared with that of the 1D CWT algorithms. This comparison indicates that the 2D CWT outperforms its 1D counterpart for this application.

Journal Article↗
PubMedDate not supplied

Approximate derivative calculated by using continuous wavelet transform.

A novel method of calculating approximate derivative of signals in analytical chemistry by using the continuous wavelet transform (CWT) is proposed. As compared with numerical differentiation, FT method and DWT method, fast calculation, and simple mathematical operation are remarkable advantages of CWT method. The signal-to-noise ratio (SNR) of approximate derivative of signals calculated by CWT method is easily enhanced only through appropriately adjusting the dilation, even in the case of very low SNR. Therefore, CWT method is a powerful tool for performing the approximate derivative calculation of signals in analytical chemistry. Additionally, the approximate second derivative evaluated via CWT method can be used to determine the peak potentials of the overlapping square wave voltammogram (SWV) of Cd(II) and In(III), and the results are very satisfactory.

Journal Article↗
PubMedDate not supplied

Continuous wavelet transform applied to removing the fluctuating background in near-infrared spectra.

A novel method based on continuous wavelet transform (CWT) was proposed as a preprocessing tool for the near-infrared (NIR) spectra. Due to the property of the vanishing moments of the wavelet, the fluctuating background of the NIR spectra can be successfully removed through convolution of the spectra with an appropriate wavelet function. The vanishing moments of a wavelet and the scale parameter are two key factors that govern the result of the background elimination. The result of its application to both the simulated spectra and the NIR spectra of tobacco samples demonstrates that CWT is a competitive tool for removing fluctuating background in spectra.

Journal Article↗
PubMed2004

Continuous wavelet transform in the evaluation of stretch reflex responses from surface EMG.

OBJECTIVE: This is the first reported use of the continuous wavelet transform (CWT) of the surface EMG (sEMG) to extract the reflex response to muscle stretch. We used a modulus-based method to estimate instantaneous amplitude-envelopes from ridges of the CWT (referred in this work as sEMG intensity) to extract the dynamic reflex response from sEMG. We tested the method on tendon reflexes where excellent temporal resolution is required to identify the different latency components, and on the tonic stretch reflex (tonic SR) response to an ongoing perturbation that characteristically has a low signal to noise ratio. METHODS: Eight subjects without neurological impairment were subjected to a series of archilles tendon taps and a 2 min continuous perturbation of the ankle using a pseudo-sinusoidal stretch profile containing frequencies from 0.1 to 8.0 Hz. The tendon reflexes were assessed in the soleus muscle at 10% of MVC and the tonic SR in tibialis anterior while the muscle was relaxed, at 5 and 10% of maximal voluntary contraction. Root mean square (RMS) and wavelet ridge extraction was applied to the sEMG signal to extract sEMG amplitudes (RMS) and intensities for all reflexes. To obtain the tonic SR, these estimates and those from the sEMG-RMS were subsequently cross-correlated with the perturbation record to yield 2 sets of estimates of reflex gain and coherence for comparison. RESULTS: The sEMG intensities were highly correlated with the torques resulting from a ramped voluntary contraction. Following tendon taps, the method resolved the M1, M2, M3 response components at accurate latencies and with more complete reconstruction of the components than RMS-derived estimates. The wavelet ridge estimates extracted the tonic SR from resting and contracting muscles with significantly higher coherence than RMS estimates. Reflex gain, when estimated from sEMG intensity or sEMG-RMS, demonstrated similar relationships to the perturbation frequency and background contraction level. When the sEMG intensity reflex gain estimates from different subjects were pooled, they showed significantly lower variance about the mean than gain estimates derived from the rectified sEMG. CONCLUSIONS: Wavelet-ridge extraction provides a valid approach to reflex evaluation from sEMG that does not depend on the absolute amplitude of the potentials measured at the EMG electrodes. This may have substantial advantages in more directly comparing responses between subjects on an absolute frequency scale without the need for normalisation against maximal contraction levels.

Electromyography↗
PubMed2006

Band shape determination with robust estimator based on continuous wavelet transform.

The paper focuses on an alternative approach that allows one to identify overlapping band shapes with the help of the continuous wavelet transform (CWT). We show that less number of special points for determining a band shape is required unlike the fractional derivative spectrometry method [S.S. Kharintsev, M.Kh. Salakhov, Spectrochim. Acta Part A, 60 (2004) 2125]. Besides, the CWT-based derivative spectrometry can be successfully utilized in a case of complex spectra corrupted with a white and/or high-frequency noise. The power of this method is illustrated on model examples and experimental spectra of 1,2-diphenylethane in crystalline and melted phase.

Algorithms↗
PubMed2004

Identification of diesel front sound source based on continuous wavelet transform.

Acoustic signals from diesel engines contain useful information but also include considerable noise components. To extract information for condition monitoring purposes, continuous wavelet transform (CWT) is used for the characterization of engine acoustics. This paper first reviews CWT characteristics represented by short duration transient signals. Wavelet selection and CWT are then implemented and wavelet transform is used to analyze the major sources of the engine front's exterior radiation sound. The research provides a reliable basis for engineering practice to reduce vehicle sound level. Comparison of the identification results of the measured acoustic signals with the identification results of the measured surface vibration showed good agreement.

Algorithms↗
PubMed1997

Continuous wavelet transform of aortic pressure oscillations in anesthetized dogs: effects of 45 degrees tilting.

The time-frequency analysis of signals by means of continuous wavelet transform (CWT) was applied to blood pressure oscillations recorded from the aorta of anesthetized dogs. This method yielded two and three-dimensional representations of either the module or phase in function of time, in contrast with the fast Fourier transform (FFT) which gives the spectrum in the frequency domain. From the CWT of arterial pressure oscillations we obtained visual information on aortic valves closure, heart rate, respiratory rate and smooth muscle contractions in arterial and arteriolar walls (very low frequency component). The objective of this study was to analyze the frequency-time behavior in two and three-dimensional cardiovascular changes during 45 degrees head-up and head-down tilts, compared with zero degree supine position. In eight pentobarbitone anesthetized dogs, the postural changes were repeated for more than ten times in each one. Heart rate variability was derived by applying a new mathematical procedure. We utilized the pronounced changes of heart rate during each respiratory cycle (inspiratory tachycardia and expiratory bradycardia) to establish a correlation with the arterial pressure fluctuations during normal and tilting conditions. Significant differences in heart rate were observed between the 45 degrees head-up and head-down tilts, compared with the supine position. The results show that anesthetized dogs might constitute an appropriate model where to study orthostatic hypotension and microgravity blood shifts.

Anesthesia↗