scholarly journals An Instantaneous Correlation Coefficient and Simplified Coherent Averaging Method for Single-Channel Foetal ECG Extraction

2020 ◽  
Vol 10 (16) ◽  
pp. 5634
Author(s):  
Miao Zhang ◽  
Guo Wei
Keyword(s):  
Correlation Coefficient ◽  
Averaging Method ◽  
Single Channel ◽  
Synthetic Data ◽  
P Wave ◽  
Ecg Signal ◽  
Threshold Method ◽  
Residual Noise ◽  
Coherent Averaging ◽  
Foetal Ecg

In this paper, an instantaneous correlation coefficient and simplified coherent averaging method for single-channel foetal ECG (FECG) extraction is proposed. The instantaneous correlation coefficient is used to determine the position of the R peak of the measured ECG signal, and the simplified coherent averaging method is used to extract the main information of the ECG signal. The loss of the nonlinear and nonstationary characteristics by coherent averaging is recovered by threshold processing of the residual signal. The FECG signal extraction is performed in three steps. In the first step, the main information of the maternal electrocardiogram (MECG) is extracted from the abdomen electrocardiogram (AECG) signal by means of the instantaneous correlation coefficient and simplified coherent averaging method, and then the noisy FECG is obtained by subtracting the MECG obtained by simplified coherent averaging from the AECG. The second step is to extract the main information of the FECG by applying the instantaneous correlation coefficient and simplified coherent averaging method to the noisy FECG. The remaining signal is obtained by subtracting the simplified coherent averaging FECG from the noisy FECG. Thirdly, the threshold method is utilised to remove MECG residual noise and random gross value noise from the remaining signal to extract the nonlinear and nonstationary information, and the final FECG extraction is obtained by adding the nonlinear and nonstationary information to the simplified coherent averaging FECG. The validity of the proposed method is verified by experiments using synthetic data and real database data. FECG extracted by the method has the advantages of clear QRS complex wave, reasonable enhancement of P wave and T wave morphology, and no loss of nonlinear and nonstationary characteristics.

Application of complex-trace analysis to seismic data for random-noise suppression and temporal resolution improvement

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. V79-V86 ◽  
Author(s):  
Hakan Karsli ◽  
Derman Dondurur ◽  
Günay Çifçi
Keyword(s):  
Seismic Data ◽  
Trace Analysis ◽  
Noise Suppression ◽  
Single Channel ◽  
Random Noise ◽  
Synthetic Data ◽  
Low Frequency ◽  
Bright Spot ◽  
Phase Information ◽  
Resolution Improvement

Time-dependent amplitude and phase information of stacked seismic data are processed independently using complex trace analysis in order to facilitate interpretation by improving resolution and decreasing random noise. We represent seismic traces using their envelopes and instantaneous phases obtained by the Hilbert transform. The proposed method reduces the amplitudes of the low-frequency components of the envelope, while preserving the phase information. Several tests are performed in order to investigate the behavior of the present method for resolution improvement and noise suppression. Applications on both 1D and 2D synthetic data show that the method is capable of reducing the amplitudes and temporal widths of the side lobes of the input wavelets, and hence, the spectral bandwidth of the input seismic data is enhanced, resulting in an improvement in the signal-to-noise ratio. The bright-spot anomalies observed on the stacked sections become clearer because the output seismic traces have a simplified appearance allowing an easier data interpretation. We recommend applying this simple signal processing for signal enhancement prior to interpretation, especially for single channel and low-fold seismic data.

scholarly journals Phase stable swept-source optical coherence tomography with active mode-locking laser for contrast enhancements of retinal angiography

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kwan Seob Park ◽  
Eunwoo Park ◽  
Hwidon Lee ◽  
Hyun-Ji Lee ◽  
Sang-Won Lee ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Phase Stability ◽  
Averaging Method ◽  
Mode Locking ◽  
Optical Coherence ◽  
Swept Source ◽  
Active Mode ◽  
Coherent Averaging ◽  
Noise Ratio ◽  
High Phase

AbstractSwept-source optical coherence tomography (SS-OCT) is an attractive high-speed imaging technique for retinal angiography. However, conventional swept lasers vary the cavity length of the laser mechanically to tune the output wavelength. This causes sweep-timing jitter and hence low phase stability in OCT angiography. Here, we improve an earlier phase-stabilized, akinetic, SS-OCT angiography (OCTA) method by introducing coherent averaging. We develop an active mode-locking (AML) laser as a high phase-stable akinetic swept source for the OCTA system. The phase stability of the improved system was analyzed, and the effects of coherent averaging were validated using a retina phantom. The effectiveness of the coherent averaging method was further confirmed by comparing coherently and conventionally averaged en face images of human retinal vasculature for their contrast-to-noise ratio, signal-to-noise ratio, and vasculature connectivity. The contrast-to-noise ratio was approximately 1.3 times larger when applying the coherent averaging method in the human retinal experiment. Our coherent averaging method with the high phase-stability AML laser source for OCTA provides a valuable tool for studying healthy and diseased retinas.

3-D elastic prestack, reverse‐time depth migration

Geophysics ◽  
1994 ◽  
Vol 59 (4) ◽  
pp. 597-609 ◽  
Author(s):  
Wen‐Fong Chang ◽  
George A. McMechan
Keyword(s):  
Finite Differences ◽  
Synthetic Data ◽  
P Wave ◽  
Common Source ◽  
Reverse Time ◽  
Depth Migration ◽  
Full Wave ◽  
Source Data ◽  
Recorded Data ◽  
Time Extrapolation

By combining and extending previous algorithms for 2-D prestack elastic migration and 3-D prestack acoustic migration, a full 3-D elastic prestack depth migration algorithm is developed. Reverse‐time extrapolation of the recorded data is by 3-D elastic finite differences; computation of the image time for each point in the 3-D volume is by 3-D acoustic finite differences. The algorithm operates on three‐component, vector‐wavefield common‐source data and produces three‐component vector reflectivity distributions. Converted P‐to‐S reflections are automatically imaged with the primary P‐wave reflections. There are no dip restrictions as the full wave equation is used. The algorithm is illustrated by application to synthetic data from three models; a flat reflector, a dipping truncated wedge overlying a flat reflector, and the classical French double dome and fault model.

scholarly journals Convolution Neural Network Based Ecg Classifier

2019 ◽  
Vol 10 (3) ◽  
pp. 1626-1630
Author(s):  
Sharanya S ◽  
Sridhar PA ◽  
Poornakala J ◽  
Muppala Vasishta ◽  
Tharani U
Keyword(s):  
Neural Network ◽  
Noise Removal ◽  
Convolution Neural Network ◽  
P Wave ◽  
Time Interval ◽  
Ecg Signal ◽  
Related Condition ◽  
Simple Method ◽  
Medical Practitioners ◽  
Ecg Signals

Classification of Electrocardiogram (ECG) signals plays a significant role in the identification of the functioning of the heart. This work pertains with the ECG signals, where the classifier is developed for identification of normal or abnormal conditions of the heart. The raw ECG signals are collected from an online database (www.physioNet.org) for classification. The raw ECG signal is pre-processed for noise removal, and the frequency spectrum is analysed to compare raw and denoised ECG signal. Attributes (P, Q, R, S, T time intervals) from denoised ECG signal is analysed and classified using Convolution Neural Network (CNN). The paper reports a classification technique to differentiate ECG signals from the MIT-BIH database (arrhythmia database, arrhythmia p-wave annotations, atrial fibrillation). The CNN analyses the deviation between nominal ranges of attributes (amplitude and time interval) and classifies between the abnormality and normal ECG wave. This work provides a simple method for interpreting ECG related condition for the clinician and helps medical practitioners to make diagnostic decisions.

scholarly journals Seismic AVOA Inversion for Weak Anisotropy Parameters and Fracture Density in a Monoclinic Medium

2020 ◽  
Vol 10 (15) ◽  
pp. 5136 ◽  
Author(s):  
Zijian Ge ◽  
Shulin Pan ◽  
Jingye Li
Keyword(s):  
Fractured Rock ◽  
Synthetic Data ◽  
Transversely Isotropic ◽  
P Wave ◽  
Inversion Method ◽  
Fracture Density ◽  
Weak Anisotropy ◽  
Amplitude Versus Offset ◽  
Porosity And Permeability ◽  
Transverse Isotropic

In shale gas development, fracture density is an important lithologic parameter to properly characterize reservoir reconstruction, establish a fracturing scheme, and calculate porosity and permeability. The traditional methods usually assume that the fracture reservoir is one set of aligned vertical fractures, embedded in an isotropic background, and estimate some alternative parameters associated with fracture density. Thus, the low accuracy caused by this simplified model, and the intrinsic errors caused by the indirect substitution, affect the estimation of fracture density. In this paper, the fractured rock of monoclinic symmetry assumes two non-orthogonal vertical fracture sets, embedded in a transversely isotropic background. Firstly, assuming that the fracture radius, width, and orientation are known, a new form of P-wave reflection coefficient, in terms of weak anisotropy (WA) parameters and fracture density, was obtained by substituting the stiffness coefficients of vertical transverse isotropic (VTI) background, normal, and tangential fracture compliances. Then, a linear amplitude versus offset and azimuth (AVOA) inversion method, of WA parameters and fracture density, was constructed by using Bayesian theory. Tests on synthetic data showed that WA parameters, and fracture density, are stably estimated in the case of seismic data containing a moderate noise, which can provide a reliable tool in fracture prediction.

ECG SIGNAL GENERATION AND HEART RATE VARIABILITY SIGNAL EXTRACTION: SIGNAL PROCESSING, FEATURES DETECTION, AND THEIR CORRELATION WITH CARDIAC DISEASES

2012 ◽  
Vol 12 (04) ◽  
pp. 1240012 ◽  
Author(s):  
GOUTHAM SWAPNA ◽  
DHANJOO N. GHISTA ◽  
ROSHAN JOY MARTIS ◽  
ALVIN P. C. ANG ◽  
SUBBHURAAM VINITHA SREE
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sinus Bradycardia ◽  
Premature Ventricular Contraction ◽  
P Wave ◽  
Ecg Signal ◽  
Qrs Complex ◽  
T Wave ◽  
St Segment ◽  
Cardiac Disorders

The sum total of millions of cardiac cell depolarization potentials can be represented by an electrocardiogram (ECG). Inspection of the P–QRS–T wave allows for the identification of the cardiac bioelectrical health and disorders of a subject. In order to extract the important features of the ECG signal, the detection of the P wave, QRS complex, and ST segment is essential. Therefore, abnormalities of these ECG parameters are associated with cardiac disorders. In this work, an introduction to the genesis of the ECG is given, followed by a depiction of some abnormal ECG patterns and rhythms (associated with P–QRS–T wave parameters), which have come to be empirically correlated with cardiac disorders (such as sinus bradycardia, premature ventricular contraction, bundle-branch block, atrial flutter, and atrial fibrillation). We employed algorithms for ECG pattern analysis, for the accurate detection of the P wave, QRS complex, and ST segment of the ECG signal. We then catagorited and tabulated these cardiac disorders in terms of heart rate, PR interval, QRS width, and P wave amplitude. Finally, we discussed the characteristics and different methods (and their measures) of analyting the heart rate variability (HRV) signal, derived from the ECG waveform. The HRV signals are characterised in terms of these measures, then fed into classifiers for grouping into categories (for normal subjects and for disorders such as cardiac disorders and diabetes) for carrying out diagnosis.

Near-surface scattering phenomena and implications for tunnel detection

2015 ◽  
Vol 3 (1) ◽  
pp. SF43-SF54 ◽  
Author(s):  
Shelby L. Peterie ◽  
Richard D. Miller
Keyword(s):  
Synthetic Data ◽  
P Wave ◽  
S Wave ◽  
Seismic Line ◽  
Data Set ◽  
Near Surface ◽  
Tunnel Detection ◽  
Impedance Contrast ◽  
Diffraction Imaging ◽  
Imaging Algorithms

Tunnel locations are accurately interpreted from diffraction sections of focused mode converted P- to S-wave diffractions from a perpendicular tunnel and P-wave diffractions from a nonperpendicular (oblique) tunnel. Near-surface tunnels are ideal candidates for diffraction imaging due to their small size relative to the seismic wavelength and large acoustic impedance contrast at the tunnel interface. Diffraction imaging algorithms generally assume that the velocities of the primary wave and the diffracted wave are approximately equal, and that the diffraction apex is recorded directly above the scatterpoint. Scattering phenomena from shallow tunnels with kinematic properties that violate these assumptions were observed in one field data set and one synthetic data set. We developed the traveltime equations for mode-converted and oblique diffractions and demonstrated a diffraction imaging algorithm designed for the roll-along style of acquisition. Potential processing and interpretation pitfalls specific to these diffraction types were identified. Based on our observations, recommendations were made to recognize and image mode-converted and oblique diffractions and accurately interpret tunnel depth, horizontal location, and azimuth with respect to the seismic line.

The Development of Estimators for the Peaks-Over-Threshold Method

2002 ◽  
Author(s):  
A. Naess ◽  
P. H. Clausen
Keyword(s):  
Wind Speed ◽  
Synthetic Data ◽  
Distribution Functions ◽  
Statistical Distribution ◽  
Peaks Over Threshold ◽  
Threshold Method

The paper discusses the accuracy and efficiency of some of the standard estimators used in conjunction with the Peaks-Over-Threshold (POT) method. A comparison is made between some commonly adopted estimators and two types of estimators proposed by the authors. The comparison is based on an extensive set of synthetic data simulated from a range of different statistical distribution functions that have been assumed to describe wind speed processes.

scholarly journals Relative moment tensors and deep Yakutat seismicity

2019 ◽  
Vol 219 (2) ◽  
pp. 1447-1462 ◽  
Author(s):  
Alexandre P Plourde ◽  
Michael G Bostock
Keyword(s):  
Principal Components ◽  
Moment Tensor ◽  
Synthetic Data ◽  
Principal Component ◽  
P Wave ◽  
Inversion Method ◽  
Low Velocity ◽  
Stress Regime ◽  
Moment Tensors ◽  
S Waves

SUMMARY We introduce a new relative moment tensor (MT) inversion method for clusters of nearby earthquakes. The method extends previous work by introducing constraints from S-waves that do not require modal decomposition and by employing principal component analysis to produce robust estimates of excitation. At each receiver, P and S waves from each event are independently aligned and decomposed into principal components. P-wave constraints on MTs are obtained from a ratio of coefficients corresponding to the first principal component, equivalent to a relative amplitude. For S waves we produce constraints on MTs involving three events, where one event is described as a linear combination of the other two, and coefficients are derived from the first two principal components. Nonlinear optimization is applied to efficiently find best-fitting tensile-earthquake and double-couple solutions for relative MT systems. Using synthetic data, we demonstrate the effectiveness of the P and S constraints both individually and in combination. We then apply the relative MT inversion to a set of 16 earthquakes from southern Alaska, at ∼125 km depth within the subducted Yakutat terrane. Most events are compatible with a stress tensor dominated by downdip tension, however, we observe several pairs of earthquakes with nearly antiparallel slip implying that the stress regime is heterogeneous and/or faults are extremely weak. The location of these events near the abrupt downdip termination of seismicity and the low-velocity zone suggest that they are caused by weakening via grain-size and volume reduction associated with eclogitization of the lower crustal gabbro layer.

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