scholarly journals Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios

2021 ◽  
Vol 6 (3) ◽  
pp. 70
Author(s):  
Erik Kowalski ◽  
Danilo S. Catelli ◽  
Mario Lamontagne
Keyword(s):  
Visual Inspection ◽  
Visual Detection ◽  
Signal To Noise Ratio ◽  
Detection Methods ◽  
Onset Detection ◽  
Signal To Noise ◽  
Quality Signals ◽  
Electromyography Signals ◽  
Double Threshold ◽  
Better Than

Electromyography (EMG) onsets determined by computerized detection methods have been compared against the onsets selected by experts through visual inspection. However, with this type of approach, the true onset remains unknown, making it impossible to determine if computerized detection methods are better than visual detection (VD) as they can only be as good as what the experts select. The use of simulated signals allows for all aspects of the signal to be precisely controlled, including the onset and the signal-to-noise ratio (SNR). This study compared three onset detection methods: approximated generalized likelihood ratio, double threshold (DT), and VD determined by eight trained individuals. The selected onset was compared against the true onset in simulated signals which varied in the SNR from 5 to 40 dB. For signals with 5 dB SNR, the VD method was significantly better, but for SNRs of 20 dB or greater, no differences existed between the VD and DT methods. The DT method is recommended as it can improve objectivity and reduce time of analysis when determining EMG onsets. Even for the best-quality signals (SNR of 40 dB), all the detection methods were off by 15–30 ms from the true onset and became progressively more inaccurate as the SNR decreased. Therefore, although all the detection methods provided similar results, they can be off by 50–80 ms from the true onset as the SNR decreases to 10 dB. Caution must be used when interpreting EMG onsets, especially on signals where the SNR is low or not reported at all.

Weak Transient Electromagnetic Radiation Signal Detection Method Considering the New Watershed Image Segmentation Algorithm

2019 ◽  
Vol 34 (03) ◽  
pp. 2054009
Author(s):  
Wenjun Huo ◽  
Peng Chu ◽  
Kai Wang ◽  
Liangting Fu ◽  
Zhigang Niu ◽  
...  
Keyword(s):  
Electromagnetic Radiation ◽  
Cross Correlation ◽  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Detection Methods ◽  
Signal To Noise ◽  
Long Distance ◽  
Transient Electromagnetic ◽  
Noise Ratio

In order to study the detection methods of weak transient electromagnetic radiation signals, a detection algorithm integrating generalized cross-correlation and chaotic sequence prediction is proposed in this paper. Based on the dual-antenna test and cross-correlation information estimation method, the detection of aperiodic weak discharge signals under low signal-to-noise ratio is transformed into the estimation of periodic delay parameters, and the noise is reduced at the same time. The feasibility of this method is verified by simulation and experimental analysis. The results show that under the condition of low signal-to-noise ratio, the integrated method can effectively suppress the influence of 10 noise disturbances. It has a high detection probability for weak transient electromagnetic radiation signals, and needs fewer pulse accumulation times, which improves the detection efficiency and is more suitable for long-distance detection of weak electromagnetic radiation sources.

MIMO Detectors: A Comprehensive Performance Analysis

2021 ◽  
Vol 16 (3) ◽  
pp. 24-27
Author(s):  
E. Obi ◽  
B.O. Sadiq ◽  
O.S . Zakariyya ◽  
A. Theresa
Keyword(s):  
Error Rate ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Signal To Noise ◽  
High Data ◽  
Noise Ratio ◽  
Better Than

Multiple-input multiple-output (MIMO) systems are increasingly becoming popular due to their ability to multiply data rates without any expansion in the bandwidth. This is critical in this era of high-data rate applications but limited bandwidth. MIMO detectors play an important role in ensuring effective communication in such systems and as such the performance of the following are compared in this paper with respect to symbol error rate (SER) versus signal-to-noise ratio (SNR): maximum likelihood (ML), zero forcing (ZF), minimum mean square error (MMSE) and vertical Bell laboratories layered space time (VBLAST). Results showed that the ML has the best performance as it has the least Symbol Error Rate (SER) for all values of Signal to Noise Ratio (SNR) as it was 91.9% better than MMSE, 99.6% better than VBLAST and 99.8% better than ZF at 20db for a 2x2 antenna configuration., it can also be deduced that the performance increased with increase in number of antenna for all detectors except the V-BLAST detector.

Signal-to-Noise Ratio Estimation in Electromyography Signals Contaminated with Electrocardiography Signals

2020 ◽  
Vol 19 (03) ◽  
pp. 2050027
Author(s):  
Thandar Oo ◽  
Pornchai Phukpattaranont
Keyword(s):  
Signal To Noise Ratio ◽  
Training Data ◽  
Signal To Noise ◽  
Zero Crossing ◽  
Ecg Signals ◽  
Average Value ◽  
Emg Signal ◽  
Recognition Systems ◽  
Noise Ratio ◽  
Electromyography Signals

When electromyography (EMG) signals are collected from muscles in the torso, they can be perturbed by the electrocardiography (ECG) signals from heart activity. In this paper, we present a novel signal-to-noise ratio (SNR) estimate for an EMG signal contaminated by an ECG signal. We use six features that are popular in assessing EMG signals, namely skewness, kurtosis, mean average value, waveform length, zero crossing and mean frequency. The features were calculated from the raw EMG signals and the detail coefficients of the discrete stationary wavelet transform. Then, these features are used as inputs to a neural network that outputs the estimate of SNR. While we used simulated EMG signals artificially contaminated with simulated ECG signals as the training data, the testing was done with simulated EMG signals artificially contaminated with real ECG signals. The results showed that the waveform length determined with raw EMG signals was the best feature for estimating SNR. It gave the highest average correlation coefficient of 0.9663. These results suggest that the waveform length could be deployed not only in EMG recognition systems but also in EMG signal quality measurements when the EMG signals are contaminated by ECG interference.

Study on Threshold Detection of Micro-Seismic Signal Based on Constraint Judgment

2011 ◽  
Vol 255-260 ◽  
pp. 2898-2903
Author(s):  
Chang Peng Ji ◽  
Mo Gao ◽  
Jie Yang
Keyword(s):  
Signal To Noise Ratio ◽  
Seismic Signal ◽  
Probability Of Detection ◽  
Identification Accuracy ◽  
Signal To Noise ◽  
Threshold Detection ◽  
Probability Of False Alarm ◽  
Improvement Effect ◽  
The Mathematical Model ◽  
Double Threshold

Double threshold detection based on constraint judgment is proposed for micro-seismic signal detection. The improvement effect on Probability of False Alarm and influence on Probability of Detection are quantitatively analyzed with constraint judgment. The mathematical models of total PFA and PD of double threshold detection based on constraint judgment are built, and the validity of the mathematical model is verified by simulation tests and experiments. The results show that the signal-to-noise ratio under scheduled PFA and PD Call be decreased by introducing constraint judgment to double threshold detection, and improve the identification accuracy of micro-seismic signal.

A Comparison of 25 Gbps NRZ & PAM-4 Modulation Used in Reference, Legacy, & Premium Backplane Channels

2012 ◽  
Vol 2012 (1) ◽  
pp. 000283-000294 ◽  
Author(s):  
Chad Morgan ◽  
Adam Healey
Keyword(s):  
Insertion Loss ◽  
Signal To Noise Ratio ◽  
High Density ◽  
Advanced Materials ◽  
Signal To Noise ◽  
Baud Rate ◽  
Noise Ratio ◽  
Better Than

Standards bodies are now examining how to increase the throughput of high-density backplane links to 25 Gbps. One method for achieving this is to construct premium backplane links utilizing advanced materials and connectors. Another approach is to re-use legacy backplanes by employing PAM-4 signaling at half of the baud rate. For PAM-4 to offer an advantage over NRZ, the signal-to-noise ratio (SNR) at the slicer input, i.e. after equalization, must be ∼9.5 dB better than NRZ to overcome loss of separation between signal levels. This paper will examine 25 Gbaud NRZ and 12.5 Gbaud PAM-4 signaling across varying levels of channel insertion loss and crosstalk. The paper provides a reliable reference for engineers to use when considering when it is appropriate to use NRZ signaling at 25 Gbaud and when it is appropriate to use PAM-4 signaling at 12.5 Gbaud for successful high-density backplane operation.

Frequency resolution of Fourier and maximum entropy spectral estimates

Geophysics ◽  
1982 ◽  
Vol 47 (9) ◽  
pp. 1303-1307 ◽  
Author(s):  
S. L. Marple
Keyword(s):  
Maximum Entropy ◽  
Signal To Noise Ratio ◽  
Frequency Resolution ◽  
Sampled Data ◽  
Signal To Noise ◽  
Analytic Determination ◽  
Spectral Estimates ◽  
The Mean ◽  
Better Than

An analytic determination of the frequency resolution for maximum entropy and conventional Blackman‐Tukey spectral estimates is made for the case of known autocorrelation. As the signal‐to‐noise ratio decreases, the maximum entropy resolution is no better than that achievable by the Blackman‐Tukey spectral estimate. The mean resolution of an ensemble of spectra constructed from sampled data sequences agrees with the analytic result.

FRFT Based Method to Estimate DOA for Wideband Signal

2013 ◽  
Vol 712-715 ◽  
pp. 2716-2720 ◽  
Author(s):  
Wei Yang ◽  
Yao Wu Shi
Keyword(s):  
Fractional Fourier Transform ◽  
Signal To Noise Ratio ◽  
Doa Estimation ◽  
New Method ◽  
New Technique ◽  
Signal Frequency ◽  
Signal To Noise ◽  
One Dimensional ◽  
Time Frequency ◽  
Better Than

This paper presents a new direction-of-arrival (DOA) estimation for wideband sources, using fractional Fourier transform with fitting angle (F3A). Unlike other coherent wideband methods, the new method does not require any preprocessing for initial values and decomposing into narrowband components. This new technique estimates DOA by rotating the time frequency plate with the fitting angle to fit the time frequency distribution approximately. The algorithm can be applied to arbitrary shaped one dimensional or two dimensional arrays. The signal frequency can be higher than the frequencies in many wideband algorithms. The performance of this wideband technique is compared with that of the new method through simulations. The simulations show that this new technique performs better than others, while this algorithm does not apparently vary with signal-to-noise ratio (SNR).

An Optimized Particle Filter for Signal De-Noising Processing

2013 ◽  
Vol 589-590 ◽  
pp. 629-633
Author(s):  
Han Xin Chen ◽  
Ling Tu ◽  
Kui Sun ◽  
Cen Liu
Keyword(s):  
Particle Filter ◽  
Basis Function ◽  
Signal To Noise Ratio ◽  
Radial Basis Function Network ◽  
Noise Signal ◽  
Signal To Noise ◽  
Estimation Errors ◽  
Function Network ◽  
Particle Impoverishment ◽  
Better Than

The traditional particle filter (PF) algorithm is well known for signal noise reduction processing, but it exists problems of particle impoverishment and cumulation of estimation errors. An optimized PF algorithm called RBF-PF is proposed in this paper, which uses radial basis function network for training and optimizing the process of particle filter in the sampling. Experimental analysis verifies that the new method used to gain the signal-to-noise ratio is better than traditional PF algorithm during dealing with the added noise signal.

SEARCH FOR STEADY AND TRANSIENT POINT-LIKE SOURCES OF NEUTRINOS WITH ANTARES

2009 ◽  
Vol 18 (10) ◽  
pp. 1505-1509
Author(s):  
◽  
CIRO BIGONGIARI
Keyword(s):  
Short Duration ◽  
Angular Resolution ◽  
Signal To Noise Ratio ◽  
High Energy ◽  
Neutrino Telescope ◽  
Signal To Noise ◽  
Transient Sources ◽  
High Energy Neutrinos ◽  
Noise Ratio ◽  
Better Than

The ANTARES underwater neutrino telescope has been completed in May 2008 and is now taking data continuously. Thanks to its very good angular resolution (better than 0.3° for neutrinos with energy above 10 TeV) ANTARES is especially suited for the search of astrophysical point-like sources of high energy neutrinos. Data taken with a limited detector (5 out of 12 lines) between January and December 2007 have been analyzed to look for a possible neutrino excess from a list of prospective neutrino sources. In the case of transient sources, like GRBs, the short duration of the expected neutrino signal can be exploited to enhance the signal to noise ratio. ANTARES strategy for both steady and transient point-like sources is discussed. The methodology adopted and the results obtained are shown.

scholarly journals RapidHRV: an open-source toolbox for extracting heart rate and heart rate variability

2021 ◽  
Author(s):  
Peter Kirk ◽  
Sarah Garfinkel ◽  
Oliver Joe Robinson
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Oximetry ◽  
Open Source ◽  
Visual Inspection ◽  
Signal To Noise Ratio ◽  
Simulated Data ◽  
Signal To Noise ◽  
Python Package ◽  
Insight Into

Heart rate and its variability have enabled insight into a myriad of psychophysiological phenomena. There is now an influx of research attempting using these metrics within both laboratory settings (typically derived through electrocardiography or pulse oximetry) and ecologically-rich contexts (via wearable photoplethysmography, i.e. smartwatches). However, these signals can be prone to artifacts and a low signal to noise ratio, which traditionally are detected and removed through visual inspection. Here, we developed an open-source Python package, RapidHRV, dedicated to the preprocessing, analysis, and visualization of time-domain heart rate and heart rate variability. Each of these modules can be executed with one line of code and includes automated cleaning. In simulated data, RapidHRV demonstrated excellent recovery of heart rate across most levels of noise (>= 10dB) and moderate-to-excellent recovery of heart rate variability even at relatively low signal to noise ratios (>=20dB) and sampling rates (>=20Hz). Validation in real datasets shows good-to-excellent recovery of heart rate and heart rate variability in electrocardiography and pulse oximetry recordings. Validation in real photoplethysmography demonstrated RapidHRV estimations were sensitive to heart rate and its variability under low motion conditions, but estimates were less stable under higher movement settings.

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