An Improved Denoising of Electrocardiogram Signals Based on Wavelet Thresholding

2021 ◽  
Vol 51 ◽  
pp. 117-129
Author(s):  
Pinjala N. Malleswari ◽  
Ch. Hima Bindu ◽  
K. Satya Prasad
Keyword(s):  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Ecg Signal ◽  
Noise Power ◽  
Signal To Noise ◽  
Noise Elimination ◽  
Electrocardiogram Signals ◽  
Conventional Methods ◽  
Noise Ratio ◽  
Power Line Interference

Electrocardiogram (ECG) is the most important signal in the biomedical field for the diagnosis of Cardiac Arrhythmia (CA). ECG signal often interrupted with various noises due to non-stationary nature which leads to poor diagnosis. Denoising process helps the physicians for accurate decision making in treatment. In many papers various noise elimination techniques are tried to enhance the signal quality. In this paper a novel hybrid denoising technique using EMD-DWT for the removal of various noises such as Additive White Gaussian Noise (AWGN), Baseline Wander (BW) noise, Power Line Interference (PLI) noise at various concentrations are compared to the conventional methods in terms of Root Mean Square Error (RSME), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Cross-Correlation (CC) and Percent Root Square Difference (PRD). The average values of RMSE, SNR, PSNR, CC and PRD are 0.0890, 9.8821, 14.4464, 0.9872 and 10.9036 for the EMD approach, respectively, and 0.0707, 10.7181, 16.2824, 0.9874 and 10.7245 for the proposed EMD-DWT approach, respectively, by removing AWGN noise. Similarly BW noise and PLI are removed from the ECG signal by calculating the same quality metrics. The proposed methodology has lower RMSE and PRD values, higher SNR, PSNR and CC values than the conventional methods.

The Noise Analysis of Fluid Systemsin Solid-State Nanopore Sensors

2013 ◽  
Vol 419 ◽  
pp. 517-520 ◽  
Author(s):  
Song Ying ◽  
Lei Wang ◽  
Wen Yuan Zhao
Keyword(s):  
Solid State ◽  
Signal To Noise Ratio ◽  
Noise Analysis ◽  
Power Spectra ◽  
Noise Power ◽  
Label Free ◽  
Signal To Noise ◽  
Fluid Systems ◽  
Noise Ratio ◽  
Nanopore Sensors

The solid-state nanopore sensor offers a versatile platform for the rapid, label-free electrical detection and analysis of single molecules, especially on DNA sequencing. However, the overall signal-to-noise ratio (SNA) is a major challenge in sequencing applications. In our work, two different fluid systems made by metal and plexiglass have been designed to improve the signal to noise ratio of the solid-state nanopore sensor. From the measurements on the noise power spectra with a variety of conditions, it is found that plexiglass fluid system coupled with shielding box produces a good quality of electric signals on nanopore sensors.

scholarly journals Design of an Indigenised Electronic Lock-In Amplifier

2000 ◽  
Vol 23 (1) ◽  
pp. 53-60
Author(s):  
Umesh Kumar
Keyword(s):  
Narrow Band ◽  
Signal To Noise Ratio ◽  
Broad Band ◽  
Power Line ◽  
Frequency Drift ◽  
Noise Power ◽  
Signal To Noise ◽  
Band Noise ◽  
Noise Ratio ◽  
Lock In

An indigenised lock-in amplifier is designed that enables the accurate measurement of signals contaminated by broad-band noise, power-line pick-up, frequency drift, or other sources of interference. It does this by means of an extremely narrow band detector which has the centre of its passband locked to the frequency of the signal to be measured. Large improvements in signal-to-noise ratio are achieved.

scholarly journals Coherent Power Measurements with a Compact Airborne Ka-Band Precipitation Radar

2018 ◽  
Vol 35 (1) ◽  
pp. 3-20 ◽  
Author(s):  
Andrew L. Pazmany ◽  
Samuel J. Haimov
Keyword(s):  
Signal To Noise Ratio ◽  
Power Estimation ◽  
Noise Power ◽  
Signal Power ◽  
Signal To Noise ◽  
Precipitation Radar ◽  
Noise Component ◽  
Ka Band ◽  
Noise Ratio ◽  
Conventional Signal

AbstractCoherent power is an alternative to the conventional noise-subtracted power technique for measuring weather radar signal power. The inherent noise-canceling feature of coherent power eliminates the need for estimating and subtracting the noise component, which is required when performing conventional signal power estimation at low signal-to-noise ratio. The coherent power technique is particularly useful when averaging a high number of samples to improve sensitivity to weak signals. In such cases, the signal power is small compared to the noise power and the required accuracy of the estimated noise power may be difficult to achieve. This paper compares conventional signal power estimation with the coherent power measurement technique by investigating bias, standard deviation, and probability of false alarm and detection rates as a function of signal-to-noise ratio and threshold level. This comparison is performed using analytical expressions, numerical simulations, and analysis of cloud and precipitation data collected with the airborne solid-state Ka-band precipitation radar (KPR) operated by the University of Wyoming.

Increasing of the Signal-To-Noise Ratio in Precision Spectroscopy

2012 ◽  
Vol 7 (4) ◽  
pp. 19-24
Author(s):  
Evgeny Baklanov ◽  
Aleksandr Kurbatov
Keyword(s):  
Signal To Noise Ratio ◽  
Noise Power ◽  
Doppler Broadening ◽  
Precision Spectroscopy ◽  
Signal To Noise ◽  
Narrow Resonance ◽  
Signal Noise ◽  
Radiation Noise ◽  
Noise Ratio ◽  
Multimode Regime

Is considered the possibility of increasing the signal / noise ratio in one of the main methods of laser spectroscopy without Doppler broadening – the method of saturated absorption. The colliding beam of laser radiation in a multimode regime is expected to be used. Interaction of counter propagating modes with different frequencies will increase the number of gas atoms effectively interact with the field and, consequently, the value of a narrow resonance line shape. It is shown that the photon noise, which is essentially unavoidable, signal / noise ratio can be increased in a time where – the number of modes. For other noise (power fluctuations of the radiation, noise, photo detector, etc.) the magnitude of the signal / noise ratio may increase again

Noise elimination by the use of vector resolution

Geophysics ◽  
1990 ◽  
Vol 55 (9) ◽  
pp. 1191-1201 ◽  
Author(s):  
Hongwei Wang
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Data Sets ◽  
Signal To Noise ◽  
Noise Elimination ◽  
Vsp Data ◽  
Noise Ratio ◽  
Adjacent Channels

This paper introduces the concept of the Unit Similarity Vector (USV) which is based on the hypothesis that signals on adjacent channels are similar, and then discusses how the amplitude vector formed in a multichannel environment, is resolved into two components—the similarity component and the dissimilarity component. The signal‐to‐noise ratio can be enhanced by compressing the dissimilarity component. Excellent results are obtained using the method with surface seismic data, and satisfactory results are also obtained with three‐component VSP data sets.

scholarly journals HEART BEAT DETECTION IN NOISY ECG SIGNALS USING STATISTICAL ANALYSIS OF THE AUTOMATICALLY DETECTED ANNOTATIONS / ŠIRDIES DŪŽIŲ NUSTATYMAS IŠ IŠKRAIPYTŲ EKG SIGNALŲ ATLIEKANT AUTOMATIŠKAI APTIKTŲ ATSKAITŲ STATISTINĘ ANALIZĘ

2015 ◽  
Vol 7 (3) ◽  
pp. 300-303
Author(s):  
Andrius Gudiškis
Keyword(s):  
Signal To Noise Ratio ◽  
Heart Beat ◽  
High Signal ◽  
Detection Accuracy ◽  
Ecg Signal ◽  
Signal To Noise ◽  
Ecg Signals ◽  
Arterial Blood ◽  
Boundary Estimation ◽  
Noise Ratio

This paper proposes an algorithm to reduce the noise distortion influence in heartbeat annotation detection in electrocardiogram (ECG) signals. Boundary estimation module is based on energy detector. Heartbeat detection is usually performed by QRS detectors that are able to find QRS regions in a ECG signal that are a direct representation of a heartbeat. However, QRS performs as intended only in cases where ECG signals have high signal to noise ratio, when there are more noticeable signal distortion detectors accuracy decreases. Proposed algorithm uses additional data, taken from arterial blood pressure signal which was recorded in parallel to ECG signal, and uses it to support the QRS detection process in distorted signal areas. Proposed algorithm performs as well as classical QRS detectors in cases where signal to noise ratio is high, compared to the heartbeat annotations provided by experts. In signals with considerably lower signal to noise ratio proposed algorithm improved the detection accuracy to up to 6%. Širdies ritmas yra vienas svarbiausių ir daugiausia informacijos apie pacientų būklę teikiančių fiziologinių parametrų. Širdies ritmas nustatomas iš elektrokardiogramos (EKG), atliekant QRS regionų, kurie yra interpretuojami kaip širdies dūžio ãtskaitos, paiešką. QRS regionų aptikimas yra klasikinis uždavinys, nagrinėjamas jau keletą dešimtmečių, todėl širdies dūžių nustatymo iš EKG signalų metodų yra labai daug. Deja, šie metodai tikslūs ir patikimi tik esant dideliam signalo ir triukšmo santykiui. Kai EKG signalai labai iškraipomi, QRS aptiktuvai ne visada gali atskirti QRS regioną, o kartais jį randa ten, kur iš tikro jo būti neturėtų. Straipsnyje siūlomas algoritmas, kurį taikant sumažinama triukšmo įtaka nustatant iš EKG signalų QRS regionus. Tam naudojamas QRS aptiktuvas, kartu prognozuojantis širdies dūžio atskaitą. Remiamasi arterinio kraujo spaudimo signalo duomenimis, renkama atskaitų statistika ir atliekama jos analizė.

Analysis of parameters for smoothing electrocardiographic signals Aleksandr A. Fedotov

2019 ◽  
pp. 47-51
Author(s):  
A.A. Fedotov
Keyword(s):  
Measurement Error ◽  
Wavelet Transforms ◽  
Measurement Errors ◽  
Signal To Noise Ratio ◽  
Ecg Signal ◽  
Optimal Parameters ◽  
Signal To Noise ◽  
Optimal Method ◽  
Rr Intervals ◽  
Noise Ratio

The article is devoted to the consideration of the features of smoothing filtering of ECG signal against the background of electromyographic distortions of various magnitude. The main goal of the research is comparative analysis of various options for the implementation of smoothing filtering of an ECG signal contaminated by myographic interference in order to determine the optimal approach in terms of minimizing biosignal distortions and measurement errors of its amplitude-time characteristics. To obtain quantitative characteristics of effectiveness of various methods for smoothing filtering of the ECG signal, we used an approach based on simulation models of the ECG signal and distortions. A criterion for choosing the optimal parameters for smoothing filtering of the ECG signal based on minimizing the errors in determining the durations of RR-intervals and distortions of the ECG signal was proposed. Various options for smoothing filters are considered: low-pass filtering, multiscale wavelet transform, Savitzky–Golay filtering, moving average filtering. The optimal parameters for each type of filter are determined in terms of minimizing the distortion of the ECG signal and the measurement error of the durations of RR-intervals. The dependences of the change in the measurement error of the durations of RR-intervals on the signal-to-noise ratio, the dependences of the change in the signal distortion coefficient on the signal-to-noise ratio, the plots of processing the noisy fragment of ECG signal by various types of filters are presented. Research have shown that multiscale wavelet transforms of ECG signal with myographic interference is the optimal method for processing an ECG signal, providing minimal measurement errors of RR-intervals with minimal distortion of the ECG signal.

Microphone array speech enhancement based on optimized IMCRA

2021 ◽  
Vol 69 (6) ◽  
pp. 468-476
Author(s):  
Qiuying Li ◽  
Tao Zhang ◽  
Yanzhang Geng ◽  
Zhen Gao
Keyword(s):  
Power Spectrum ◽  
Speech Enhancement ◽  
Signal To Noise Ratio ◽  
Microphone Array ◽  
Noise Power ◽  
Noise Power Spectrum ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Speech Segments ◽  
Enhancement Algorithm

Microphone array speech enhancement algorithm uses temporal and spatial informa- tion to improve the performance of speech noise reduction significantly. By combining noise estimation algorithm with microphone array speech enhancement, the accuracy of noise estimation is improved, and the computation is reduced. In traditional noise es- timation algorithms, the noise power spectrum is not updated in the presence of speech, which leads to the delay and deviation of noise spectrum estimation. An optimized im- proved minimum controlled recursion average speech enhancement algorithm, based on a microphone matrix is proposed in this paper. It consists of three parts. The first part is the preprocessing, divided into two branches: the upper branch enhances the speech signal, and the lower branch gets the noise. The second part is the optimized improved minimum controlled recursive averaging. The noise power spectrum is updated not only in the non-speech segments but also in the speech segments. Fi- nally, according to the estimated noise power spectrum, the minimum mean-square error log-spectral amplitude algorithm is used to enhance speech. Testing data are from TIMIT and Noisex-92 databases. Short-time objective intelligibility and seg- mental signal-to-noise ratio are chosen as evaluation metrics. Experimental results show that the proposed speech enhancement algorithm can improve the segmental signal-to-noise ratio and short-time objective intelligibility for various noise types at different signal-to-noise ratio levels.

Efficient Artifact Elimination in Cardiac Signals using Variable Step Size Adaptive Noise Cancellers

2012 ◽  
Vol 2 (1) ◽  
pp. 35-51 ◽  
Author(s):  
S. Yasmin Fathima ◽  
G. V. S. Karthik ◽  
M. Zia Ur Rahman ◽  
A. Lay-Ekuakille
Keyword(s):  
Signal To Noise Ratio ◽  
Motion Artifacts ◽  
Variable Step Size ◽  
Ecg Signal ◽  
Large Signal ◽  
Signal To Noise ◽  
Step Size ◽  
Variable Step ◽  
Adaptive Noise ◽  
Power Line Interference

In this paper several variable step size adaptive filter structures for extracting high resolution electrocardiographic (ECG) signals are presented which estimates the deterministic components of the ECG signal and removes the artifacts. The noise canceller minimizes the mean square error (MSE) between the input noisy ECG signal and noise reference. Different noise canceller structures are proposed to remove diverse forms of artifacts: power line interference, baseline wander, muscle artifacts and electrode motion artifacts. The proposed implementation is suitable real time applications, where large signal to noise ratios with fast convergence are required. Simulation studies shows that the proposed realization gives better performance compared to existing realizations in terms of signal to noise ratio, convergence rate and MSE.

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