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PubMed2005

Identification of the defective transmission devices using the wavelet transform.

In this paper, a system is described that uses the wavelet transform to automatically identify the particular failure mode of a known defective transmission device. The problem of identifying a particular failure mode within a costly failed assembly is of benefit in practical applications. In this system, external acoustic sensors, instead of intrusive vibrometers, are used to record the acoustic data of the operating transmission device. A skilled factory worker, who is unfamiliar with statistical classification, helps to determine the feature vector of the particular failure mode in the feature extraction process. In the automatic identification part, an improved learning vector quantization (LVQ) method with normalizing the inputting feature vectors is proposed to compensate for variations in practical data. Some acoustic data, which are collected from the manufacturing site, are utilized to test the effectiveness of the described identification system. The experimental results show that this system can identify the particular failure mode of a defective transmission device and find out the causes of failure successfully.

Acoustics↗
PubMed2005

Dynamic contrast-based quantization for lossy wavelet image compression.

This paper presents a contrast-based quantization strategy for use in lossy wavelet image compression that attempts to preserve visual quality at any bit rate. Based on the results of recent psychophysical experiments using near-threshold and suprathreshold wavelet subband quantization distortions presented against natural-image backgrounds, subbands are quantized such that the distortions in the reconstructed image exhibit root-mean-squared contrasts selected based on image, subband, and display characteristics and on a measure of total visual distortion so as to preserve the visual system's ability to integrate edge structure across scale space. Within a single, unified framework, the proposed contrast-based strategy yields images which are competitive in visual quality with results from current visually lossless approaches at high bit rates and which demonstrate improved visual quality over current visually lossy approaches at low bit rates. This strategy operates in the context of both nonembedded and embedded quantization, the latter of which yields a highly scalable codestream which attempts to maintain visual quality at all bit rates; a specific application of the proposed algorithm to JPEG-2000 is presented.

Algorithms↗
PubMed2005

Optimization of integer wavelet transforms based on difference correlation structures.

In this paper, a novel lifting integer wavelet transform based on difference correlation structure (DCCS-LIWT) is proposed. First, we establish a relationship between the performance of a linear predictor and the difference correlations of an image. The obtained results provide a theoretical foundation for the following construction of the optimal lifting filters. Then, the optimal prediction lifting coefficients in the sense of least-square prediction error are derived. DCCS-LIWT puts heavy emphasis on image inherent dependence. A distinct feature of this method is the use of the variance-normalized autocorrelation function of the difference image to construct a linear predictor and adapt the predictor to varying image sources. The proposed scheme also allows respective calculations of the lifting filters for the horizontal and vertical orientations. Experimental evaluation shows that the proposed method produces better results than the other well-known integer transforms for the lossless image compression.

Algorithms↗
PubMed2000

Temporal organization of atrial activity and irregular ventricular rhythm during spontaneous atrial fibrillation: an in vivo study in the horse.

INTRODUCTION: Atrial fibrillation (AF) is common in healthy horses. We studied the temporal organization of AF to test the hypothesis that the arrhythmia is governed by a high degree of periodicity and therefore is not random in the horse. Further, we surmised that concealed conduction of AF impulses in the AV node results in an inverse relationship between AF frequency and ventricular frequency. METHODS AND RESULTS: Fast Fourier transform (FFT) analysis of atrial activity was done on signal-averaged ECGs (n = 11) and atrial electrograms (n = 3) of horses with AF at control (C), after quinidine sulfate (22 mg/kg by mouth every 2 hours) at 50% time to conversion (T50), and immediately before conversion (T90) to sinus rhythm. FFT always revealed a single dominant frequency peak. The mean dominant frequency decreased until conversion (C = 6.84 +/- 0.85 Hz, T50 = 4.87 +/- 1.5 Hz, T90 = 3.41 +/- 1.18 Hz; P < 0.001). Mean AA intervals (n = 500) gradually increased after quinidine. Mean RR intervals (n = 500), standard deviation of the mean (SDM), Poincaré plots, and serial autocorrelograms (SACs) of 500 RR intervals were measured at C and T90 to determine the ventricular response to AF and quinidine-induced changes in the variability of the ventricular response. Mean RR interval and SDM were reduced after quinidine (C = 1431 +/- 266 msec and 695 +/- 23 msec; T90 = 974 +/- 116 msec and 273 +/- 158 msec, respectively; P < 0.01). Poincaré plots and SAC at C and at T90 revealed a significant correlation of consecutive RR intervals typical of a system with a deterministic behavior. At T90, the variability of RR intervals was reduced and the overall periodicity of RR intervals was increased after quinidine administration. CONCLUSION: In the horse, AF is a complex arrhythmia characterized by a high degree of underlying periodicity. The inverse AA-to-RR interval relationship and reduced variability of RR intervals after quinidine suggest that the ventricular response during AF results from rate-dependent concealment of AF wavelets bombarding the AV node, which nevertheless results in a significant degree of short-term predictability of beat-to-beat changes in RR intervals.

Animals↗
PubMed2006

Detecting time-dependent coherence between non-stationary electrophysiological signals--a combined statistical and time-frequency approach.

Various time-frequency methods have been used to study time-varying properties of non-stationary neurophysiological signals. In the present study, a time-frequency coherence estimate using continuous wavelet transform (CWT) together with its confidence intervals are proposed to evaluate the correlation between two non-stationary processes. The approach is based on averaging over repeat trials. A systematic comparison between approaches using CWT and short-time Fourier transform (STFT) is carried out. Simulated data are generated to test the performance of these methods when estimating time-frequency based coherence. In contrast to some recent studies, we find that CWT based coherence estimates do not supersede STFT based estimates. We suggest that a combination of STFT and CWT would be most suitable for analysing non-stationary neural data. Tests are presented to investigate the time and frequency discrimination capabilities of the two approaches. The methods are applied to two experimental data sets: electroencephalogram (EEG) and surface electromyogram (EMG) during wrist movements in a healthy subject, and local field potential (LFP) and surface EMG recordings during resting tremor in a Parkinsonian patient. Supporting software is available at and .

Algorithms↗
PubMed2005

Optical clearing for improved contrast in second harmonic generation imaging of skeletal muscle.

Using second harmonic generation (SHG) imaging microscopy, we have examined the effect of optical clearing with glycerol to achieve greater penetration into specimens of skeletal muscle tissue. We find that treatment with 50% glycerol results in a 2.5-fold increase in achievable SHG imaging depth. Signal processing analyses using fast Fourier transform and continuous wavelet transforms show quantitatively that the periodicity of the sarcomere structure is unaltered by the clearing process and that image quality deep in the tissue is improved with clearing. Comparison of the SHG angular polarization dependence also shows no change in the supramolecular organization of acto-myosin complexes. By contrast, identical treatment of mouse tendon (collagen based) resulted in a strong decrease in SHG response. We suggest that the primary mechanism of optical clearing in muscle with glycerol treatment results from the reduction of cytoplasmic protein concentration and concomitant decrease in the secondary inner filter effect on the SHG signal. The lack of glycerol concentration dependence on the imaging depth indicates that refractive index matching plays only a minor role in the optical clearing of muscle. SHG and optical clearing may provide an ideal mechanism to study physiology in highly scattering skeletal or cardiac muscle tissue with significantly improved depth of penetration and achievable imaging depth.

Animals↗
PubMed2004

Morphological classification of brains via high-dimensional shape transformations and machine learning methods.

A high-dimensional shape transformation posed in a mass-preserving framework is used as a morphological signature of a brain image. Population differences with complex spatial patterns are then determined by applying a nonlinear support vector machine (SVM) pattern classification method to the morphological signatures. Significant reduction of the dimensionality of the morphological signatures is achieved via wavelet decomposition and feature reduction methods. Applying the method to MR images with simulated atrophy shows that the method can correctly detect subtle and spatially complex atrophy, even when the simulated atrophy represents only a 5% variation from the original image. Applying this method to actual MR images shows that brains can be correctly determined to be male or female with a successful classification rate of 97%, using the leave-one-out method. This proposed method also shows a high classification rate for old adults' age classification, even under difficult test scenarios. The main characteristic of the proposed methodology is that, by applying multivariate pattern classification methods, it can detect subtle and spatially complex patterns of morphological group differences which are often not detectable by voxel-based morphometric methods, because these methods analyze morphological measurements voxel-by-voxel and do not consider the entirety of the data simultaneously.

Aged↗
PubMed2005

Brain oscillatory responses to an auditory-verbal working memory task in mild cognitive impairment and Alzheimer's disease.

We report preliminary findings on EEG oscillatory correlates of working memory in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Event-related desynchronization (ERD) and synchronization (ERS) of the 1-20 Hz EEG frequencies were studied using wavelet transforms in elderly controls, MCI patients and mild probable AD patients performing an auditory-verbal Sternberg memory task. Behaviourally, the AD patients made more errors than the controls and the MCI group. Statistically significant differences during the encoding of the memory set were found between the controls and the MCI group, such that the latter group showed ERD in the approximately 10-20 Hz frequencies. The findings may reflect different, compensatory encoding strategies in MCI. During retrieval, the most obvious differences were observed between the controls and the AD group: the ERD in the approximately 7-17 Hz frequencies was absent in the AD group particularly in anterior and left temporal electrode locations. This finding might indicate that AD is associated with deficient lexical-semantic processing during the retrieval phase in working memory tasks. Future studies with larger patient groups are needed to establish the diagnostic value of ERD/ERS patterns in MCI and AD.

Acoustic Stimulation↗
PubMed2002

Blind deconvolution of ultrasound sequences using nonparametric local polynomial estimates of the pulse.

The problem of reconstructing the reflectivity of a biological tissue is examined by means of blind deconvolution of the echo ultrasound signals. It is shown that the quality of the reconstruction procedure can be significantly improved when initially the ultrasonic pulse is accurately estimated. A new approach to the estimation of the ultrasound pulse echo sequences is proposed, using local polynomial approximation, which is closely related to the wavelet transform theory. This approach can be viewed as a modification of homomorphic deconvolution, by using bases different from the Fourier basis of the space of square-integrable functions L2. The bases used here are the orthogonal compactly supported wavelet bases. It is shown that the locality of the estimate can be extremely useful in number of cases of practical interest, resulting in estimates with smaller root-mean squared (rms) errors, as compared with estimates employing the Fourier basis. This approach is applied to ultrasound signals, for estimation of the ultrasound pulse log-spectrum from the log-spectrum of radio-frequency (RF) sequences. It is shown, conceptually and experimentally, that the proposed approach can provide robust and rapidly computed estimates of the ultrasound pulses from the RF-sequences, as obtained in the process of tissue scanning. The pulse phase was recovered using the minimum-phase assumption, which was found to hold for the transducers in use. The obtained pulse estimates are used for the deconvolution of the RF-sequences, which result in stable estimates of the tissue reflectivity function, fairly independent of the properties of the imaging system. Simulated data, data obtained from several phantoms and from in vitro experiments have been processed and the results seem to be quite promising.

Animals↗
PubMed2005

Normalization of multicolor fluorescence in situ hybridization (M-FISH) images for improving color karyotyping.

BACKGROUND: Multiplex or multicolor fluorescence in situ hybridization (M-FISH) is a recently developed cytogenetic technique for cancer diagnosis and research on genetic disorders. By simultaneously viewing the multiply labeled specimens in different color channels, M-FISH facilitates the detection of subtle chromosomal aberrations. The success of this technique largely depends on the accuracy of pixel classification (color karyotyping). Improvements in classifier performance would allow the elucidation of more complex and more subtle chromosomal rearrangements. Normalization of M-FISH images has a significant effect on the accuracy of classification. In particular, misalignment or misregistration across multiple channels seriously affects classification accuracy. Image normalization, including automated registration, must be done before pixel classification. METHODS AND RESULTS: We studied several image normalization approaches that affect image classification. In particular, we developed an automated registration technique to correct misalignment across the different fluor images (caused by chromatic aberration and other factors). This new registration algorithm is based on wavelets and spline approximations that have computational advantages and improved accuracy. To evaluate the performance improvement brought about by these data normalization approaches, we used the downstream pixel classification accuracy as a measurement. A Bayesian classifier assumed that each of 24 chromosome classes had a normal probability distribution. The effects that this registration and other normalization steps have on subsequent classification accuracy were evaluated on a comprehensive M-FISH database established by Advanced Digital Imaging Research (http://www.adires.com/05/Project/MFISH_DB/MFISH_DB.shtml). CONCLUSIONS: Pixel misclassification errors result from different factors. These include uneven hybridization, spectral overlap among fluors, and image misregistration. Effective preprocessing of M-FISH images can decrease the effects of those factors and thereby increase pixel classification accuracy. The data normalization steps described in this report, such as image registration and background flattening, can significantly improve subsequent classification accuracy. An improved classifier in turn would allow subtle DNA rearrangements to be identified in genetic diagnosis and cancer research.

Algorithms↗
PubMed2006

Measurement of phase gradients in the EEG.

Previous research has shown that spatio-temporal waves in the EEG are generally of long spatial wavelength and form smooth patterns of phase gradients at particular time-samples. This paper describes a method to measure smooth phase gradients of long spatial wavelength in the EEG. The method depends on the global pattern of phase at a given frequency and time and is therefore robust to variations, over time, in phase-lag between particular sites. Phases were estimated in the EEG signal using wavelet or short time-series Fourier methods. During an auditory oddball task, phases across the scalp tend to fall within a limited circular range, a range that is not indicative of phase-synchrony nor waves with multiple periods. At times the phases tended to maintain a spatially and temporally ordered relationship. The relative phases were analysed using three phase gradient basis functions, providing a measure of the amount of variance explained, across the electrodes, by smooth changes in relative phase from a single minimum or single maximum. The data from 586 adult subjects were analysed and it was found that the probability of phase gradient events varies with time and frequency in the stimulus-locked average, and with task demands. The temporal extent of spatio-temporal waves was measured by detecting smoothly changing patterns of phase latencies across the scalp. The specific spatial pattern and timing of phase gradients correspond closely to the latency distributions of certain ERPs.

Acoustic Stimulation↗
PubMed2006

Assessment of QT-measurement accuracy using the 12-lead electrocardiogram derived from EASI leads.

The purpose of the present study is to assess QT-interval measurements from the EASI 12-lead electrocardiogram (ECG) as compared with the standard 12-lead ECG. The QT interval was automatically determined in simultaneously recorded standard and EASI 12-lead ECGs, using a validated wavelet-based delineator. The agreement between the 2 sets of measurements was quantified both on a lead-by-lead basis and a multilead basis with global definitions of QRS onset and T-wave end. The results show that the agreement between QT-interval measurements from the 2 lead systems is acceptable, with negligible mean differences and with correlation coefficients ranging from 0.91 to 0.98 depending on the lead studied. Although the SD shows a clear dependence on the selected lead (ranging from 9.2 to 26.4 milliseconds), differences are within the accepted tolerances for automatic delineation. In a few patients, large differences were found, mainly because of changes in morphology present in both lead systems. QT intervals measured by the multilead approach were considerably more stable than single-lead measurements and resulted in a much better agreement between the 2 lead systems (correlation coefficient, 0.98; QT difference, 1.1 +/- 9.8 milliseconds). Thus, the EASI 12-lead ECG may be used for reliable QT monitoring when the multilead delineation approach is adopted.

Diagnosis, Computer-Assisted↗
PubMed2004

Blood pressure power within frequency range approximately 0.4 Hz in rat conforms to self-similar scaling following spinal cord transection.

This study quantified the effect of interrupting the descending input to the sympathetic preganglionic neurons on the dynamic behavior of arterial blood pressure (BP) in the unanesthetized rat. BP was recorded for approximately 4-h intervals in six rats in the neurally intact state and in the same animals after complete spinal cord transection (SCT) between T(4) and T(5). In the intact state, power within the frequency range of 0.35-0.45 Hz was 1.53 +/- 0.38 mmHg(2)/Hz (mean +/- SD by fast Fourier transform). One week after SCT, power within this range decreased significantly (P < 0.05) to 0.43 +/- 0.62 mmHg(2)/Hz. To test for self-similarity before and after SCT, we analyzed data using a wavelet (i.e., functionally, a digital bandpass filter) tuned to be maximally sensitive to fluctuations with periods of approximately 2, 4, 8, 16, 32, or 64 s. In the control state, all fluctuations with periods of >/=4 s conformed to a "self-similar" (i.e., fractal) distribution. In marked contrast, the oscillations with a period of approximately 2 s (i.e., approximately 0.4 Hz) were significantly set apart from those at lower frequencies. One day and seven days after the complete SCT, however, the BP fluctuations at approximately 0.4 Hz now also conformed to the same self-similar behavior characteristic of the lower frequencies. We conclude that 1) an intact sympathetic nervous system endows that portion of the power spectrum centered around approximately 0.4 Hz with properties (e.g., a periodicity) that differ significantly from the self-similar behavior that characterizes the lower frequencies and 2) even within the relatively high frequency range at 0.4 Hz self-similarity is the "default" condition after sympathetic influences have been eliminated.

Animals↗
PubMed1996

Stratification of time-frequency abnormalities in the signal-averaged high-resolution ECG in postinfarction patients with and without ventricular tachycardia and congenital long QT syndrome.

Having developed sound mathematical techniques that allow precise mapping of cardiac signals in the time-frequency (TF) and time-scale planes, the next important issue is to extract from these representations information that best reflects the electrophysiologic and anatomic derangement unique to patients at risk of arrhythmias and other cardiac diseases. In this study, the authors present a new method that stratifies the magnitude of the TF transforms of abnormal cardiac signals into distinguishing features by comparing the means of the coefficients of the TF transforms of any study population to the corresponding means of a control population using a standard ANOVA technique. This results in a three-dimensional mapping of the high-resolution ECG into time, frequency, and P value components. Significant energy increases are given positive P values and depressed energies are given negative P values: these are ranked according to a color scale. The method was tested on two study populations: postmyocardial infarction patients with documented ventricular tachycardia (MI+VT, n = 23) and without (MI-VT, n = 40) and patients with congenital long QT syndrome (LQTS, n = 19). Two groups of healthy control subjects (n = 31 and n = 40) were used as a reference group matched for sex. The study results were based on the Morlet analyzing wavelets, with frequencies ranging from 40 to 250 Hz in 10 logarithmically progressing scales, and computed millisecond per millisecond over a 350-ms analyzing time window, starting from 100 ms before the onset of the QRS. The patients with MI+VT displayed significantly increased high-frequency components in the 40-250-Hz frequency range, corresponding to prolonged QRS duration and late potentials in the area from 80 to 150 ms after QRS onset. Significantly depressed energy (P < 10(-4)) was also observed for the 40-106-Hz frequency range in the first 50 ms of the QRS complex, mainly in lead Y and in the magnitude vector. In patients with LQTS, significant modifications (P < 10(-2)) were observed in the first half of the QRS and in the ST-segment, in all leads, revealing anomalies in the genesis of the ventricular depolarization and repolarization processes. In conclusion, the authors propose a new method for the stratification of abnormal TF components occurring in the signal-averaged high-resolution electrocardiogram of patients at risk of VT and fibrillation under different pathologic conditions.

Adult↗
PubMed2006

Bayesian wavelet-based image deconvolution: a GEM algorithm exploiting a class of heavy-tailed priors.

Image deconvolution is formulated in the wavelet domain under the Bayesian framework. The well-known sparsity of the wavelet coefficients of real-world images is modeled by heavy-tailed priors belonging to the Gaussian scale mixture (GSM) class; i.e., priors given by a linear (finite of infinite) combination of Gaussian densities. This class includes, among others, the generalized Gaussian, the Jeffreys, and the Gaussian mixture priors. Necessary and sufficient conditions are stated under which the prior induced by a thresholding/shrinking denoising rule is a GSM. This result is then used to show that the prior induced by the "nonnegative garrote" thresholding/shrinking rule, herein termed the garrote prior, is a GSM. To compute the maximum a posteriori estimate, we propose a new generalized expectation maximization (GEM) algorithm, where the missing variables are the scale factors of the GSM densities. The maximization step of the underlying expectation maximization algorithm is replaced with a linear stationary second-order iterative method. The result is a GEM algorithm of O(N log N) computational complexity. In a series of benchmark tests, the proposed approach outperforms or performs similarly to state-of-the art methods, demanding comparable (in some cases, much less) computational complexity.

Algorithms↗
PubMed2000

Relation between heart rate variability and training load in middle-distance runners.

PURPOSE: Monitoring physical performance is of major importance in competitive sports. Indices commonly used, like resting heart rate, VO2max, and hormones, cannot be easily used because of difficulties in routine use, of variations too small to be reliable, or of technical challenges in acquiring the data. METHODS: We chose to assess autonomic nervous system activity using heart rate variability in seven middle-distance runners, aged 24.6 +/- 4.8 yr, during their usual training cycle composed of 3 wk of heavy training periods, followed by a relative resting week. The electrocardiogram was recorded overnight twice a week and temporal and frequency indices of heart rate variability, using Fourier and Wavelet transforms, were calculated. Daily training loads and fatigue sensations were estimated with a questionnaire. Similar recordings were performed in a sedentary control group. RESULTS: The results demonstrated a significant and progressive decrease in parasympathetic indices of up to -41% (P < 0.05) during the 3 wk of heavy training, followed by a significant increase during the relative resting week of up to +46% (P < 0.05). The indices of sympathetic activity followed the opposite trend, first up to +31% and then -24% (P < 0.05), respectively. The percentage increasing mean nocturnal heart rate variation remained below 12% (P < 0.05). There was no significant variation in the control group. CONCLUSION: This study confirmed that heavy training shifted the cardiac autonomic balance toward a predominance of the sympathetic over the parasympathetic drive. When recorded during the night, heart rate variability appeared to be a better tool than resting heart rate to evaluate cumulated physical fatigue, as it magnified the induced changes in autonomic nervous system activity. These results could be of interest for optimizing individual training profiles.

Adult↗
PubMed2003

Electrophysiological mapping and histological examinations of the swine atrium with sustained (> or =24 h) atrial fibrillation: a suitable animal model for studying human atrial fibrillation.

OBJECTIVES: Interventional elimination of chronic persistent atrial fibrillation (AFib) remains difficult. An animal model mimicking the clinical situation is important. METHODS AND RESULTS: Twenty-five adult pigs were implanted with a high-speed atrial pacemaker. After continuous pacing at 600 bpm for 6 weeks, 20 (91%) of the 22 survivals developed sustained AFib lasting for at least 24 h. Epicardial dense mapping revealed multiple coexisting reentrant wavelets in the left and the right atrium (LA and RA, respectively; 10.6 +/- 2.9 vs. 7.6 +/- 2.4 wavelets/cm(2)/s; p < 0.002). The mean local A-A intervals were 87.2 +/- 14.6 ms in the LA and 103.3 +/- 19.0 ms in the RA (p < 0.0002). Acute termination of sustained AFib was successful in 3 of the 5 pigs by propafenone, but in none of the 6 by dl-sotalol. Epicardial cryothermal ablation failed to terminate any AFib by compartmentalization of the RA free wall alone (4 pigs) or together with the LA appendage (4 pigs). Electron microscopic examination demonstrated diffuse perinuclear myolysis, myofibrillar fragmentation and mitochondrial crystal disruption in the atrium. CONCLUSIONS: Pacing-induced sustained AFib (> or =24 h) in adult pigs is a feasible and efficient animal model with electrophysiological and histological characteristics closely similar to those seen in humans.

Animals↗
PubMed2005

Comparison of Fourier and wavelet transform procedures for examining the mechanomyographic and electromyographic frequency domain responses during fatiguing isokinetic muscle actions of the biceps brachii.

The primary purpose of the present study was to compare the fast Fourier transform (FFT) with the discrete wavelet transform (DWT) for determining the mechanomyographic (MMG) and electromyographic (EMG) center frequency [mean power frequency (mpf), median frequency (mdf), or wavelet center frequency (cf)] patterns during fatiguing isokinetic muscle actions of the biceps brachii. Seven men (mean+/-SD age=23+/-3 years) volunteered to perform 50 consecutive maximal, concentric isokinetic muscle actions of the dominant forearm flexors at a velocity of 180 degrees s(-1). Non-parametric "run" tests indicated significant (p<0.05) trends in the MMG and EMG signals for the 5th, 25th, and 45th muscle actions for all subjects, thereby confirming non-stationarity of the MMG and EMG signals. There were significant (p<0.05) correlations among the average normalized mpf, mdf, and cf values for contractions 1-50 for both MMG (r=0.671-0.935) and EMG (r=0.956-0.987). Polynomial regression analyses demonstrated quadratic decreases in normalized MMG mpf (R2=0.439), MMG mdf (R2=0.258), MMG cf (R2=0.359), EMG mpf (R2=0.952), EMG mdf (R2=0.914) and EMG cf (R2=0.888) across repetitions. The primary finding of this study was the similarity in the mpf, mdf, and cf patterns for both MMG and EMG, which suggested that, despite the concerns over non-stationarity, Fourier based methods are acceptable for determining the patterns for normalized MMG and EMG center frequency during fatiguing dynamic muscle actions at moderate velocities.

Adult↗