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Ensemble empirical mode decomposition based feature enhancement of cardio signals
Medical Engineering & Physics, 2013This paper presents an application of ensemble empirical mode decomposition method for enhancement of specific biological signal features. The application for two types of cardiological signals is presented in this article. Detection of fiducial points is a routine task for analyzing these signals.
Artūras, Janušauskas +2 more
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An Optimal Ensemble Empirical Mode Decomposition Method for Vibration Signal Decomposition
Journal of Vibration and Acoustics, 2017The vibration signal decomposition is a critical step in the assessment of machine health condition. Though ensemble empirical mode decomposition (EEMD) method outperforms fast Fourier transform (FFT), wavelet transform, and empirical mode decomposition (EMD) on nonstationary signal decomposition, there exists a mode mixing problem if the two critical ...
Shi-Chang Du +3 more
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Detection of ECG beat using ensemble empirical mode decomposition
2015 7th International Conference on Modelling, Identification and Control (ICMIC), 2015The electrocardiogram (ECG) is the most common non-invasive test possessing a significant clinical value to cardiac disease diagnostic. In this paper, we developed a robust ECG delineation algorithm based on Ensemble Empirical Mode Decomposition (EEMD) which has very interesting properties on pseudo periodic signals.
Dhouha Rezgui, Zied Lachiri
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IMPROVEMENT OF ENSEMBLE EMPIRICAL MODE DECOMPOSITION BY OVER-SAMPLING
Advances in Adaptive Data Analysis, 2013The empirical mode decomposition (EMD) is a useful method for the analysis of nonlinear and nonstationary signals and found immediate applications in diverse areas of signal processing. However, the major inconvenience of EMD is the mode mixing. The ensemble EMD (EEMD) was proposed to solve the problem of mode-mixing with the assistance of added noises
RAÏS EL'HADI BEKKA, YAAKOUB BERROUCHE
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A complete ensemble empirical mode decomposition with adaptive noise
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011In this paper an algorithm based on the ensemble empirical mode decomposition (EEMD) is presented. The key idea on the EEMD relies on averaging the modes obtained by EMD applied to several realizations of Gaussian white noise added to the original signal. The resulting decomposition solves the EMD mode mixing problem, however it introduces new ones. In
Maria E. Torres +3 more
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Instantaneous Frequency Selective Filtering Using Ensemble Empirical Mode Decomposition
IETE Journal of Research, 2020In this paper, novel instantaneous frequency (IF) selective high-pass, low-pass and band-pass filtering techniques for multicomponent signals are developed using the ensemble empirical mode decompo...
Rinki Gupta, Arun Kumar, Rajendar Bahl
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Denoising ECG signal based on ensemble empirical mode decomposition
SPIE Proceedings, 2011The electrocardiogram (ECG) has been used extensively for detection of heart disease. Frequently the signal is corrupted by various kinds of noise such as muscle noise, electromyogram (EMG) interference, instrument noise etc. In this paper, a new ECG denoising method is proposed based on the recently developed ensemble empirical mode decomposition ...
Zhao Zhi-dong, Juan Liu, Sheng-tao Wang
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Ensemble empirical mode decomposition for high frequency ECG noise reduction
Biomedizinische Technik/Biomedical Engineering, 2010An electrocardiogram (ECG) is measured from the body surface and is often corrupted by various noises, such as high-frequency muscle contraction. Recently, empirical mode decomposition (EMD), a well-known analysis technique for nonlinear and non-stationary signals, has been employed for the purpose of ECG noise reduction. In this study, a modified EMD,
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BIDIMENSIONAL ENSEMBLE EMPIRICAL MODE DECOMPOSITION OF FUNCTIONAL BIOMEDICAL IMAGES
Advances in Adaptive Data Analysis, 2014Positron emission tomography (PET) provides a functional imaging modality to detect signs of dementias in human brains. Two-dimensional empirical mode decomposition (2D EMD) provides means to analyze such images. It extracts characteristic textures from these images which may be fed into powerful classifiers trained to group these textures into ...
A. NEUBAUER +5 more
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Purification of Axis Trace by Ensemble Empirical Mode Decomposition
Advanced Materials Research, 2013Aiming at the purification of axis trace, a novel method was proposed by using ensemble empirical mode decomposition (EEMD). Ensemble empirical mode decomposition decomposed a complicated signal into a collection of intrinsic mode functions (IMFs). Then according to prior knowledge of rotating machinery, chose intrinsic mode function components and ...
Jia Xing Zhu +3 more
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