HD-sEMG Signal Denoising Method for Improved Classification Performance in Transhumeral Amputees Pros thesis Control

In this paper, a novel image denoising algorithm and novel input features are proposed. The algorithm is applied to phase-resolved partial discharge (PRPD) diagrams with a single dominant partial discharge (PD) source, preparing them for automatic artificial-intelligence-based classification. It was designed to mitigate several sources of distortions often observed in PRPDs obtained from fully operational hydroelectric generators. The capabilities of the denoising algorithm are the automatic removal of sparse noise and the suppression of non-dominant discharges, including those due to crosstalk. The input features are functions of PD distributions along amplitude and phase, which are calculated in a novel way to mitigate random effects inherent to PD measurements. The impact of the proposed contributions was statistically evaluated and compared to classification performance obtained using formerly published approaches. Higher recognition rates and reduced variances were obtained using the proposed methods, statistically outperforming autonomous classification techniques seen in earlier works. The values of the algorithm’s internal parameters are also validated by comparing the recognition performance obtained with different parameter combinations. All typical PD sources described in hydro-generators PD standards are considered and can be automatically detected.

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Analysis of ECG signal denoising method based on S-transform

IRBM ◽

10.1016/j.irbm.2013.07.012 ◽

2013 ◽

Vol 34 (6) ◽

pp. 362-370 ◽

Cited By ~ 24

Author(s):

M.K. Das ◽

S. Ari

Keyword(s):

Signal Denoising ◽

Ecg Signal ◽

Denoising Method ◽

S Transform

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Partial discharge signal denoising method based on frequency spectrum clustering and local mean decomposition

IET Science Measurement & Technology ◽

10.1049/iet-smt.2020.0061 ◽

2020 ◽

Vol 14 (10) ◽

pp. 853-861

Author(s):

Shanjun Li ◽

Sashuang Sun ◽

Qin Shu ◽

Minwei Chen ◽

Dakun Zhang ◽

...

Keyword(s):

Frequency Spectrum ◽

Partial Discharge ◽

Signal Denoising ◽

Denoising Method ◽

Local Mean Decomposition ◽

Local Mean

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Improved Wavelet Threshold Denoising Method

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.602-605.3177 ◽

2014 ◽

Vol 602-605 ◽

pp. 3177-3180

Author(s):

Wei Ping Cui ◽

Li Juan Du

Keyword(s):

Traditional Method ◽

Wavelet Denoising ◽

Threshold Function ◽

Signal Denoising ◽

Improved Method ◽

Denoising Method ◽

Comparison And Analysis ◽

Selection Of

In this paper, through comparison and analysis of various wavelet denoising methods, a new threshold function is constructed, and the selection of threshold is improved. Signal denoising simulation is made by the software MATLAB, the results show that the improved method is superior to the traditional method, and obtain a better denoising effect.

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Wavelet Analysis-Based Reconstruction for sEMG Signal Denoising

IFMBE Proceedings - XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019 ◽

10.1007/978-3-030-31635-8_29 ◽

2019 ◽

pp. 245-252

Author(s):

Annachiara Strazza ◽

Federica Verdini ◽

Alessandro Mengarelli ◽

Stefano Cardarelli ◽

Andrea Tigrini ◽

...

Keyword(s):

Wavelet Analysis ◽

Signal Denoising ◽

Semg Signal

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An Integrated Denoising Method for Sensor Mixed Noises Based on Wavelet Packet Transform and Energy-Correlation Analysis

Journal of Sensors ◽

10.1155/2014/650891 ◽

2014 ◽

Vol 2014 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

Chao Tan ◽

Yanping Wang ◽

Xin Zhou ◽

Zhongbin Wang ◽

Lin Zhang ◽

...

Keyword(s):

Correlation Analysis ◽

Wavelet Packet ◽

Wavelet Packet Transform ◽

Processing Method ◽

Signal Denoising ◽

Current Signal ◽

Energy Correlation ◽

Denoising Method ◽

Impact Noise ◽

Key Technologies

In order to solve the problem of industrial sensor signal denoising, an integrated denoising method for sensor mixed noises based on wavelet packet transform and energy-correlation analysis is proposed. The architecture of proposed method is designed and the key technologies, such as wavelet packet transformation, energy-correlation analysis, and processing method of wavelet packet coefficients based on energy-correlation analysis, are presented. Finally, a simulation example for a specific signal and an application of shearer cutting current signal, which mainly contain white Gaussian noise and impact noise, are carried out, and the simulation and application results show that the proposed method is effective and is outperforming others.

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