scholarly journals Automatic Detection of Noisy Signals in sEMG Grids Using Statistical Thresholding

2021 ◽  
Vol 58 (1) ◽  
Author(s):  
Khalil Ullah ◽  
Khalid Shah
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Visual Inspection ◽  
Automatic Detection ◽  
Ground Truth ◽  
Noisy Channels ◽  
Perfect Agreement ◽  
Emg Signal ◽  
Signal Processing Algorithms ◽  
Processing Algorithms

Electromyogram (EMG) signal is often processed offline, after its acquisition, using digital signal processing algorithms to extract muscle anatomical and physiological information. As most of the signal processing algorithms work on an adequate quality of the signals, thus quality checking of the EMG in real-time during its acquisition is of immense importance. In multi-channel sEMG signals, usually there are some noisy or bad channels. If the noise is of low level, it is of little concern but high level of noise can limit the usefulness of the EMG. To make sure acquisition of a good quality EMG signal in terms of SNR, one way to detect noisy channels is through visual inspection by an expert human operator, however visual inspection of multiple electrodes in real-time is not possible and is also expensive both in terms of time and cost. In this research study, we propose a novel method for automatic detection of noisy channels in multi-channel surface EMG signals based on statistical thresholding of several parameters. The results of the proposed method are in perfect agreement with the ground truth for simulated EMG signals, with an accuracy of 98.6%.

FAULT-TOLERANT MATCHED-FIELD PROCESSING IN THE PRESENCE OF ELEMENT FAILURES

2006 ◽  
Vol 14 (03) ◽  
pp. 299-319
Author(s):  
KILSEOK CHO ◽  
ALAN D. GEORGE ◽  
RAJ SUBRAMANIYAN ◽  
KEONWOOK KIM
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Fault Tolerant ◽  
Signal To Noise Ratio ◽  
Matched Field Processing ◽  
Full Wave ◽  
Precise Knowledge ◽  
Operating Environments ◽  
Signal Processing Algorithms ◽  
Processing Algorithms

In the highly cluttered undersea environment, sonar array systems require enhanced acoustic signal processing algorithms and sophisticated architectures in order to meet dependability and real-time mission requirements. The probability of hydrophone and processing element failures is very high in such severe operating environments. Adaptive matched-field processing (MFP) algorithms localize sources accurately with moderate levels of signal-to-noise ratio (SNR) and precise knowledge about environments by employing full-wave acoustic propagation models. However, they highly distort output beam patterns with significant increase of sidelobes in the presence of environmental mismatches and element failures. These problems make the development of advanced fault-tolerant signal processing algorithms imperative to tolerate the element failures in cases where replacement of defective elements is impossible or impractical. In this paper, three fault-tolerant MFP algorithms are presented to compensate for the performance degradation generated by the inherent failure characteristics of vertical line arrays. The beamforming performance and computational complexities for these fault-tolerant algorithms are analyzed in terms of the number of faulty elements, their positions in the array, and SNRs. The simulation results demonstrate that these fault-tolerant techniques provide a feasible solution for real-time and highly reliable beamforming implementation on sonar array systems.

High Level Transformation Techniques for Designing Reliable and Secure DSP Architectures

2020 ◽  
pp. 164-174
Author(s):  
Jyotirmoy Pathak ◽  
Abhishek Kumar ◽  
Suman Lata Tripathi
Keyword(s):  
Signal Processing ◽  
Reverse Engineering ◽  
Real Time ◽  
Time Signal ◽  
Transformation Techniques ◽  
Signal Processing Algorithms ◽  
Processing Algorithms ◽  
High Level ◽  
Real Time Signal Processing

Reverse engineering (RE) has become a serious threat to the silicon industry. To overcome this threat, the ICs need to be made secure and non-obvious in order to find their functionality with their architecture. Real-time signal processing algorithms need to be faster and more reliable. Adding up additional circuits for increasing the security of the IC is not permittable due to increase in overhead of the IC. In this chapter, the authors introduce a few high-level transformations (HLT) that are used to make the circuit more reliable and secure against the reverse engineering without having overhead on the IC.

scholarly journals UNIVERSAL EMBEDDED RECONFIGURABLE HARDWARE PLATFORM FOR MULTIMEDIA APPLICATIONS IN REAL-TIME

2014 ◽  
pp. 38-46
Author(s):  
Michael Livshitz ◽  
Alexey Petrovsky ◽  
Andrey Stankevich ◽  
Mikhail Kachinsky ◽  
Alexander Petrovsky
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Audio Signal ◽  
Digital Signal ◽  
Reconfigurable Hardware ◽  
Audio Signal Processing ◽  
Hardware Platform ◽  
Signal Processing Algorithms ◽  
Processing Algorithms ◽  
External Interface

This paper deals with reconfigurable hardware platform for different purposes real-time speech and audio signal processing. A design conception and turnkey solution are described. Much attention is paid to reconfigurable peripheral processor meant for external interface realization, pre- and post- data processing as well as digital signal processing algorithms implementation with the object of the DSP unloads. Moreover, three applications implemented on the considered platform are demonstrated.

Analysis of Signal Processing Algorithms of Coriolis Mass Flowmeters

2014 ◽  
Vol 605 ◽  
pp. 408-411 ◽  
Author(s):  
Jürgen Ruoff ◽  
Wolfgang Gauchel ◽  
Heinz Kück
Keyword(s):  
Signal Processing ◽  
Computational Complexity ◽  
Real Time ◽  
Flow Measurement ◽  
Noise Shaping ◽  
Phase Tracking ◽  
Time Performance ◽  
Estimation Efficiency ◽  
Signal Processing Algorithms ◽  
Processing Algorithms

For fast and precise flow measurement using coriolis flowmeters it is necessary to accurately determinate the phase difference between two noisy position signals. These signals are digitized and filtered before being processed by phase tracking algorithms. This work investigates the influence of discretization and noise shaping on different phase tracking methods and their estimation efficiency, computational complexity, real-time performance and memory requirements.

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