scholarly journals A powerful notch filter for PLI cancelation

2021 ◽  
Author(s):  
Ali Mobaien ◽  
Arman Kheirati Roonizi ◽  
Reza Boostani
Keyword(s):  
Signal To Noise Ratio ◽  
Effective Means ◽  
Synthetic Data ◽  
Notch Filter ◽  
Least Square ◽  
Noise Levels ◽  
Signal To Noise ◽  
Power Line Interference ◽  
Zero Phase ◽  
Line Interference

<div>Abstract—In this work, we present a powerful notch filter for power-line interference (PLI) cancelation from biomedical signals. This filter has a unit gain and a zero-phase response. Moreover, the filter can be implemented adaptively to adjust its bandwidth based on the signal-to-noise ratio. To realize this filter, a dynamic model is defined for PLI based on its sinusoid property. Then, a constrained least square error estimation is used to emerge the PLI based on the observations while the constraint is the PLI dynamic. At last, the estimated PLI is subtracted from recordings. The proposed filter is assessed using synthetic data and real biomedical recordings in different noise levels. The results demonstrate this filter as a very powerful and effective means for canceling the PLI out.</div>

scholarly journals A powerful notch filter for PLI cancelation

2021 ◽  
Author(s):  
Ali Mobaien ◽  
Arman Kheirati Roonizi ◽  
Reza Boostani
Keyword(s):  
Signal To Noise Ratio ◽  
Effective Means ◽  
Synthetic Data ◽  
Notch Filter ◽  
Least Square ◽  
Noise Levels ◽  
Signal To Noise ◽  
Power Line Interference ◽  
Zero Phase ◽  
Line Interference

<div>Abstract—In this work, we present a powerful notch filter for power-line interference (PLI) cancelation from biomedical signals. This filter has a unit gain and a zero-phase response. Moreover, the filter can be implemented adaptively to adjust its bandwidth based on the signal-to-noise ratio. To realize this filter, a dynamic model is defined for PLI based on its sinusoid property. Then, a constrained least square error estimation is used to emerge the PLI based on the observations while the constraint is the PLI dynamic. At last, the estimated PLI is subtracted from recordings. The proposed filter is assessed using synthetic data and real biomedical recordings in different noise levels. The results demonstrate this filter as a very powerful and effective means for canceling the PLI out.</div>

scholarly journals Methods of Power Line Interference Elimination in EMG Signal

2019 ◽  
Vol 40 ◽  
pp. 64-70
Author(s):  
Martina Ladrova ◽  
Radek Martinek ◽  
Jan Nedoma ◽  
Marcel Fajkus
Keyword(s):  
Signal To Noise Ratio ◽  
Notch Filter ◽  
Correlation Coefficients ◽  
Power Line ◽  
Shape Distortion ◽  
Emg Signal ◽  
Wide Range ◽  
Interference Elimination ◽  
Power Line Interference ◽  
Line Interference

Electromyogram (EMG) recordings are often corrupted by the wide range of artifacts, which one of them is power line interference (PLI). The study focuses on some of the well-known signal processing approaches used to eliminate or attenuate PLI from EMG signal. The results are compared using signal-to-noise ratio (SNR), correlation coefficients and Bland-Altman analysis for each tested method: notch filter, adaptive noise canceller (ANC) and wavelet transform (WT). Thus, the power of the remaining noise and shape of the output signal are analysed. The results show that the ANC method gives the best output SNR and lowest shape distortion compared to the other methods.

scholarly journals Performance analysis of two stage adaptive FIR Filter Algorithms for PLI and BW artifact cancellation in ECG

2018 ◽  
Vol 7 (1.8) ◽  
pp. 123
Author(s):  
B. Bhaskara Rao ◽  
B. Prabhakara Rao
Keyword(s):  
Mean Square Error ◽  
Adaptive Filters ◽  
Signal To Noise Ratio ◽  
Adaptive Algorithms ◽  
Mean Square ◽  
Signal To Noise ◽  
Two Stage ◽  
Baseline Wander ◽  
Power Line Interference ◽  
Line Interference

Electrocardiogram (ECG) is a measure of the electrical movement of the heart, and is obtained by surface electrodes at standardized locations on the patient’s chest. During acquisition, various artifacts/noises such as power-line interference (PLI), baseline wander (BW), muscle artifacts (MA) and motion artifacts (EM) obscure the ECG. It is important that these artifacts are minimized for the clinicians to make better diagnosis on heart problems. This paper researches the creative idea of adaptive noise cancellation (ANC) using two stage form of adaptive filters. The concept of cascading and its algorithm for real-time application is simulated on MATLAB. The proposed algorithm utilizes two adaptive filters to estimate gradients accurately which results in good adaptation and performance. The objective of the present investigation is to provide solution in order to improve the performance of noise canceller in terms of filter parameters which are obtained with the help of adaptive algorithms. Different kinds of two stage ANC algorithms are used to eliminate artifacts in ECG by considering the noises such as power line interference and baseline wander. The simulation results show that the performance of the two stage ANC is superior to the conventional single stage ANC system in terms of higher signal-to-noise ratio. Two stage adaptive algorithms are applied on real time ECG signals and compared their performance with the conventional single stage adaptive algorithms in terms of parameters Signal-to-Noise Ratio (SNR), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Distortion.

Does Motion Perception Follow Weber's Law?

Perception ◽  
1995 ◽  
Vol 24 (4) ◽  
pp. 363-372 ◽  
Author(s):  
Johannes M Zanker
Keyword(s):  
Motion Perception ◽  
Stimulus Intensity ◽  
Signal To Noise Ratio ◽  
Weber’S Law ◽  
Noise Levels ◽  
Signal To Noise ◽  
Weber's Law ◽  
The Absolute ◽  
Noise Ratio ◽  
Random Dot Patterns

The subjective strength of a percept often depends on the stimulus intensity in a nonlinear way. Such coding is often reflected by the observation that the just-noticeable difference between two stimulus intensities (JND) is proportional to the absolute stimulus intensity. This behaviour, which is usually referred to as Weber's Law, can be interpreted as a compressive nonlinearity extending the operating range of a sensory system. When the noise superimposed on a motion stimulus is increased along a logarithmic scale (in order to provide linear steps in subjective difference) in motion-coherency measurements, observers often report that the subjective differences between the various noise levels increase together with the absolute level. This observation could indicate a deviation from Weber's Law for variation of motion strength as obtained by changing the signal-to-noise ratio in random-dot kinematograms. Thus JNDs were measured for the superposition of uncorrelated random-dot patterns on static random-dot patterns and three types of motion stimuli realised as random-dot kinematograms, namely large-field and object ‘Fourier’ motion (all or a group of dots move coherently), ‘drift-balanced’ motion (a travelling region of static dots), and paradoxical ‘theta’ motion (the dots on the surface of an object move in opposite direction to the object itself). For all classes of stimuli, the JNDs when expressed as differences in signal-to-noise ratio turned out to increase with the signal-to-noise ratio, whereas the JNDs given as percentage of superimposed noise appear to be similar for all tested noise levels. Thus motion perception is in accordance with Weber's Law when the signal-to-noise ratio is regarded as stimulus intensity, which in turn appears to be coded in a nonlinear fashion. In general the Weber fractions are very large, indicating a poor differential sensitivity in signal-to-noise measurements.

Improving Hearing Performance for Cochlear Implant Recipients with Use of a Digital, Wireless, Remote-Microphone, Audio-Streaming Accessory

2015 ◽  
Vol 26 (06) ◽  
pp. 532-539 ◽  
Author(s):  
Jace Wolfe ◽  
Mila Morais ◽  
Erin Schafer
Keyword(s):  
Speech Recognition ◽  
Cochlear Implant ◽  
Repeated Measures ◽  
Signal To Noise Ratio ◽  
Effective Means ◽  
Audio Signals ◽  
Noise Levels ◽  
Repeated Measures Design ◽  
Accessory Device ◽  
Sound Processor

Background: Cochlear implant (CI) recipients experience difficulty understanding speech in noise. Remote-microphone technology that improves the signal-to-noise ratio is recognized as an effective means to improve speech recognition in noise; however, there are no published studies evaluating the potential benefits of a wireless, remote-microphone, digital, audio-streaming accessory device (heretofore referred to as a remote-microphone accessory) designed to deliver audio signals directly to a CI sound processor. Purpose: The objective of this study was to compare speech recognition in quiet and in noise of recipients while using their CI alone and with a remote-microphone accessory. Research Design: A two-way repeated measures design was used to evaluate performance differences obtained in quiet and in increasing levels of competing noise with the CI sound processor alone and with the sound processor paired to the remote microphone accessory. Study Sample: Sixteen users of Cochlear Nucleus 24 Freedom, CI512, and CI422 implants were included in the study. Data Collection and Analysis: Participants were evaluated in 14 conditions including use of the sound processor alone and with the remote-microphone accessory in quiet and at the following signal levels: 65 dBA speech (at the location of the participant; 85 dBA at the location of the remote microphone) in quiet and competing noise at 50, 55, 60, 65, 70, and 75 dBA noise levels. Speech recognition was evaluated in each of these conditions with one full list of AzBio sentences. Results: Speech recognition in quiet and in all competing noise levels, except the 75 dBA condition, was significantly better with use of the remote-microphone accessory compared with participants’ performance with the CI sound processor alone. As expected, in all technology conditions, performance was significantly poorer as the competing noise level increased. Conclusions: Use of a remote-microphone accessory designed for a CI sound processor provides superior speech recognition in quiet and in noise when compared with performance obtained with the CI sound processor alone.

Power Line Interference Elimination in ECG Signals

2019 ◽  
Vol 41 ◽  
pp. 105-115
Author(s):  
Martina Ladrova ◽  
Radek Martinek ◽  
René Jaros
Keyword(s):  
Moving Average ◽  
Notch Filter ◽  
Power Line ◽  
Ecg Signal ◽  
Mode Decomposition ◽  
Wide Range ◽  
Interference Elimination ◽  
Power Line Interference ◽  
Adaptive Noise Canceller ◽  
Line Interference

The recordings of electrocardiogram (ECG), as an important biological signal which provides a valuable basis for the clinical diagnosis and treatment, are often corrupted by the wide range of artifacts. One important of them is power line interference (PLI). The overlapping interference affects the quality of ECG waveform, leading to the false detection and recognition of wave groups, and thus causing faulty treatment or diagnosis. The study deals with some of the signal processing approaches frequently used for elimination of PLI in ECG signal and compares the accuracy of methods by evaluation of the power of the remaining noise and comparing a filtered ECG signal with an original. The results are compared for three levels of interference and each tested method: Butterworth filter (BF), notch filter, moving average filter (MA), adaptive noise canceller (ANC), wavelet transform (WT) and empirical mode decomposition (EMD).

Application of frequency-dependent multichannel Wiener filters to detect events in 2D three-component seismometer arrays

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. V133-V141 ◽  
Author(s):  
J. Wang ◽  
F. Tilmann ◽  
R. S. White ◽  
P. Bordoni
Keyword(s):  
Least Squares Method ◽  
Signal To Noise Ratio ◽  
Noise Levels ◽  
Signal To Noise ◽  
Coherent Noise ◽  
Gas Field ◽  
Frequency Dependent ◽  
Wiener Filters ◽  
Noise Ratio

Hydraulic fracture-induced microseismic events in producing oil and gas fields are usually small, and noise levels are high at the surface as a result of the heavy equipment in use. Similarly, in nonhydrocarbon settings, arrays for detecting local earthquakes will benefit from reduced noise levels and the ability to detect smaller events will be increased. We propose a frequency-dependent multichannel Wiener filtering technique with linear constraints that uses an adaptive least-squares method to remove coherent noise in seismic array data. The noise records on several reference channels are used to predict the noise on a primary channel and then can be subtracted from the observed data. On a test with an unconstrained version of this filter, maximal noise suppression leads to signal distortion. Two methods of im-posing constraints then achieve signal preservation. In one case study, synthetic signals are added to noise from a pilot deployment of a hexagonal array (nine three-component seismometers, approximately [Formula: see text]) above a gas field; noise levels are suppressed by up to [Formula: see text] (at [Formula: see text]). In a second case study, natural seismicity recorded at a dense array ([Formula: see text] spacing) in Italy is used, where the application of the filter improves the signal-to-noise ratio (S/N) more than [Formula: see text] (at [Formula: see text]) using 35 stations. In both cases, the performance of the multichannel Wiener filters is significantly better than stacking, espe-cially at lower frequencies where stacking does not help to suppress the coherent noise. The unconstrained version of the filter yields the best improvement in signal-to-noise ratio, but the constrained filter is useful when waveform distortion is unacceptable.

scholarly journals Performance Evaluation of Frame based Adaptive Compressed Sensing and Non-Adaptive Compressed Sensing based on Average Frame Signal to Noise Ratio

2018 ◽  
Vol 7 (4.10) ◽  
pp. 202
Author(s):  
T. S. Arulananth ◽  
R. Satheesh ◽  
P. Bhaskara Reddy
Keyword(s):  
Performance Evaluation ◽  
Compressed Sensing ◽  
Signal To Noise Ratio ◽  
Projection Matrix ◽  
Noise Levels ◽  
Signal To Noise ◽  
Normal Frame ◽  
Noise Ratio

The primary inspiration of our work is to discovering upgrades in the current Compressed Sensing procedure that utilizations Non Adaptive Projection Matrix rule. Normal Frame Signal-to-Noise Ratio (AFSNR) is intended to evaluate the show of the Frame-Based Adaptive Compressed Sensing with the Non-Adaptive Compressed Sensing (CS). It is a developing sign securing strategy and straight gathers the signs in a compacted shape on the off chance that they are meager on some specific premise. Proposed approach utilizes Adaptive Projection Matrix in light of edge examination which gives fundamentally enhanced discourse recreation quality and decreases the noise levels.

scholarly journals Variable structures in M87* from space, time and frequency resolved interferometry

2022 ◽  
Author(s):  
Philipp Arras ◽  
Philipp Frank ◽  
Philipp Haim ◽  
Jakob Knollmüller ◽  
Reimar Leike ◽  
...  
Keyword(s):  
Event Horizon ◽  
Very Long Baseline Interferometry ◽  
Signal To Noise Ratio ◽  
Synthetic Data ◽  
Time Variable ◽  
Signal To Noise ◽  
Inference Problem ◽  
Long Baseline ◽  
Astrophysical Objects ◽  
Spectrally Resolved

AbstractThe immediate vicinity of an active supermassive black hole—with its event horizon, photon ring, accretion disk and relativistic jets—is an appropriate place to study physics under extreme conditions, particularly general relativity and magnetohydrodynamics. Observing the dynamics of such compact astrophysical objects provides insights into their inner workings, and the recent observations of M87* by the Event Horizon Telescope1–6 using very-long-baseline interferometry techniques allows us to investigate the dynamical processes of M87* on timescales of days. Compared with most radio interferometers, very-long-baseline interferometry networks typically have fewer antennas and low signal-to-noise ratios. Furthermore, the source is variable, prohibiting integration over time to improve signal-to-noise ratio. Here, we present an imaging algorithm7,8 that copes with the data scarcity and temporal evolution, while providing an uncertainty quantification. Our algorithm views the imaging task as a Bayesian inference problem of a time-varying brightness, exploits the correlation structure in time and reconstructs (2 + 1 + 1)-dimensional time-variable and spectrally resolved images. We apply this method to the Event Horizon Telescope observations of M87*9 and validate our approach on synthetic data. The time- and frequency-resolved reconstruction of M87* confirms variable structures on the emission ring and indicates extended and time-variable emission structures outside the ring itself.

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