An Efficient ECG Denoising Method Based on Empirical Mode Decomposition, Sample Entropy, and Improved Threshold Function

Zhang, Dengyong; Wang, Shanshan; Li, Feng; Tian, Shang; Wang, Jin; Ding, Xiangling; Gong, Rongrong

doi:10.1155/2020/8811962

Cited by 39 publications

(22 citation statements)

References 45 publications

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“…As a result, it should be combined with another approach to achieve the best results. The EMD's main flaws are its noise sensitivity and the mode mixing property, which introduces error into the observed signal [35]. To address these issues, Huang suggested an Ensemble Empirical Mode Decomposition (EEMD) system [20], which was later improved [21], resulting in a numerically negligible error.…”

Section: Literature Surveymentioning

confidence: 99%

ECG Denoising Using Artificial Neural Networks and Complete Ensemble Empirical Mode Decomposition

Birok¹

2021

TURCOMAT

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Electrocardiogram (ECG) is a documentation of the electrical activities of the heart. It is used to identify a number of cardiac faults such as arrhythmias, AF etc. Quite often the ECG gets corrupted by various kinds of artifacts, thus in order to gain correct information from them, they must first be denoised. This paper presents a novel approach for the filtering of low frequency artifacts of ECG signals by using Complete Ensemble Empirical Mode Decomposition (CEED) and Neural Networks, which removes most of the constituent noise while assuring no loss of information in terms of the morphology of the ECG signal. The contribution of the method lies in the fact that it combines the advantages of both EEMD and ANN. The use of CEEMD ensures that the Neural Network does not get over fitted. It also significantly helps in building better predictors at individual frequency levels. The proposed method is compared with other state-of-the-art methods in terms of Mean Square Error (MSE), Signal to Noise Ratio (SNR) and Correlation Coefficient. The results show that the proposed method has better performance as compared to other state-of-the-art methods for low frequency artifacts removal from EEG.

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Section: Literature Surveymentioning

confidence: 99%

ECG Denoising Using Artificial Neural Networks and Complete Ensemble Empirical Mode Decomposition

Birok¹

2021

TURCOMAT

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“…Heating equipment in process systems such as refineries is generally divided into two general categories of furnaces and heat exchangers [14][15][16][17][18][19]. The difference between a furnace and a heat exchanger is in the heating source [20][21][22][23], which means that the heating source is liquid and gas [24][25][26][27][28][29]. While in a heat exchanger, the heating source is a hot fluid.…”

Section: Introductionmentioning

confidence: 99%

Use of Organic and Copper-Based Nanoparticles on the Turbulator Installment in a Shell Tube Heat Exchanger: A CFD-Based Simulation Approach by Using Nanofluids

Chupradit

Jalil

Enina

et al. 2021

Journal of Nanomaterials

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Heat exchangers with unique specifications are administered in the food industry, which has expanded its sphere of influence even to the automotive industry due to this feature. It has been used for convenient maintenance and much easier cleaning. In this study, two different nanomaterials, such as Cu-based nanoparticles and an organic nanoparticle of Chloro-difluoromethane (R22), were used as nanofluids to enhance the efficiency of heat transfer in a turbulator. It is simulated by computational fluid dynamics software (Ansys-Fluent) to evaluate the Nusselt number versus Reynolds number for different variables. These variables are diameter ratio, torsion pitch ratio, and two different nanofluids through the shell tube heat exchanger. It is evident that for higher diameter ratios, the Nusselt number has been increased significantly in higher Reynolds numbers as the heat transfer has been increased in turbulators. For organic fluids (R22), the Nusselt number has been increased significantly in higher Reynolds numbers as the heat transfer has been increased in turbulators due to the proximity of heat transfer charges. At higher torsion pitch ratios, the Nusselt number has been increased significantly in the higher Reynolds number as the heat transfer has been increased in turbulators, especially in higher velocities and pipe turbulence torsions.

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“…The prominent influence of carbon dioxide-based enhanced oil recovery methods has been studied to enhance the recovery factor in tight oil reservoirs [95][96][97][98][99]. Based on several studies, carbon dioxide is stored in underground formations and helps to enhance oil recovery [100][101][102].…”

Section: Introductionmentioning

confidence: 99%

A Laboratory Approach to Measure Enhanced Gas Recovery from a Tight Gas Reservoir during Supercritical Carbon Dioxide Injection

et al. 2021

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Supercritical carbon dioxide injection in tight reservoirs is an efficient and prominent enhanced gas recovery method, as it can be more mobilized in low-permeable reservoirs due to its molecular size. This paper aimed to perform a set of laboratory experiments to evaluate the impacts of permeability and water saturation on enhanced gas recovery, carbon dioxide storage capacity, and carbon dioxide content during supercritical carbon dioxide injection. It is observed that supercritical carbon dioxide provides a higher gas recovery increase after the gas depletion drive mechanism is carried out in low permeable core samples. This corresponds to the feasible mobilization of the supercritical carbon dioxide phase through smaller pores. The maximum gas recovery increase for core samples with 0.1 mD is about 22.5%, while gas recovery increase has lower values with the increase in permeability. It is about 19.8%, 15.3%, 12.1%, and 10.9% for core samples with 0.22, 0.36, 0.54, and 0.78 mD permeability, respectively. Moreover, higher water saturations would be a crucial factor in the gas recovery enhancement, especially in the final pore volume injection, as it can increase the supercritical carbon dioxide dissolving in water, leading to more displacement efficiency. The minimum carbon dioxide storage for 0.1 mD core samples is about 50%, while it is about 38% for tight core samples with the permeability of 0.78 mD. By decreasing water saturation from 0.65 to 0.15, less volume of supercritical carbon dioxide is involved in water, and therefore, carbon dioxide storage capacity increases. This is indicative of a proper gas displacement front in lower water saturation and higher gas recovery factor. The findings of this study can help for a better understanding of the gas production mechanism and crucial parameters that affect gas recovery from tight reservoirs.

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An Efficient ECG Denoising Method Based on Empirical Mode Decomposition, Sample Entropy, and Improved Threshold Function

Cited by 39 publications

References 45 publications

ECG Denoising Using Artificial Neural Networks and Complete Ensemble Empirical Mode Decomposition

ECG Denoising Using Artificial Neural Networks and Complete Ensemble Empirical Mode Decomposition

Use of Organic and Copper-Based Nanoparticles on the Turbulator Installment in a Shell Tube Heat Exchanger: A CFD-Based Simulation Approach by Using Nanofluids

A Laboratory Approach to Measure Enhanced Gas Recovery from a Tight Gas Reservoir during Supercritical Carbon Dioxide Injection

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