Results 161 to 170 of about 50,188 (187)

Cardiogenic oscillations extraction in inductive plethysmography: Ensemble empirical mode decomposition

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
The purpose of this study is to investigate the potential of the ensemble empirical mode decomposition (EEMD) to extract cardiogenic oscillations from inductive plethysmography signals in order to measure cardiac stroke volume. First, a simple cardio-respiratory model is used to simulate cardiac, respiratory, and cardio-respiratory signals.
Abdulhay, Enas, Guméry, Pierre-Yves, Fontecave Jallon, Julie, Baconnier, Pierre   +3 more
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Ensemble Empirical Mode Decomposition and adaptive filtering for ECG signal enhancement

2012 IEEE International Symposium on Medical Measurements and Applications Proceedings, 2012
The morphologic analysis of electrocardiogram (ECG) signals, which are always contaminated by certain types of noise, is a very important standard for medical diagnosis of heart diseases and other pathological phenomena. In this paper a novel ECG enhancement method based on Ensemble Empirical Mode Decomposition (EEMD) and adaptive filtering is proposed
Xiaochuan He, Rafik A. Goubran, Xiaoping P. Liu   +2 more
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Mining anomalous electricity consumption using Ensemble Empirical Mode Decomposition

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
Sensor deployments in large buildings allow the administrators to supervise the building infrastructure and identify abnormalities. Nevertheless, the numerous data streams reported by the increasing number of sensors overwhelm the building administrators. We propose a methodology that assists them to identify abnormal devices usages.
Romain Fontugne, Nicolas Tremblay, Pierre Borgnat, Patrick Flandrin, Hiroshi Esaki   +4 more
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Quantitative diagnosis for bearing faults by improving ensemble empirical mode decomposition

ISA Transactions, 2018
In the bearing health assessment issues, using the adaptive nonstationary vibration signal processing methods in the time-frequency domain, lead to improving of early fault detection. On the other hand, the noise and random impulses which contaminates the input data, are a major challenge in extracting fault-related features.
Mohammad Sadegh, Hoseinzadeh, Siamak Esmaeilzadeh, Khadem, Mohammad Saleh, Sadooghi   +2 more
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A fast entropy assisted complete ensemble empirical mode decomposition algorithm

The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014), 2014
Empirical mode decomposition (EMD) is a simple and real-time procedure to adaptively decompose a signal into a set of oscillation scales, but it faces the serious problem of mode mixing. The improved complete ensemble EMD with adaptive noise (Improved CEEMDAN) can successfully eliminate the mode mixing by adding white noise's IMFs and utilizing an ...
Yihai Liu, Xiaomin Zhang, Yang Yu 0040
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Classification of epileptic EEG data by using ensemble empirical mode decomposition

2018 26th Signal Processing and Communications Applications Conference (SIU), 2018
In this study, our aim is to distinguish pre-seizure and seizure data from epileptic EEG signals using Ensemble Empirical Mode Decomposition (EEMD) and various classifiers. For this purpose, epileptic EEG data from 13 epileptic patients have been recorded using surface electrodes at Izmir Kâtip Celebi University School of Medicine, Neurology Department.
Ozlem Karabiber Cura, Sibel Kocaaslan Atli, Reza Sadighzadeh, Aydin Akan   +3 more
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Improvement of the Ensemble Empirical Mode Decomposition with Parallel Computing

2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), 2019
In this paper we propose a novel approach to increase a processing speed of the Ensemble Empirical Mode Decomposition algorithm and its Complementary version with usage of parallel computations. It is shown that this computational scheme is effective and leads to a significant increase in processing speed up to approximately 4.1 times with 8 parallel ...
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GPU-based Ensemble Empirical Mode Decomposition approach to spectrum discrimination

2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS), 2012
Because of the improvement of optical remote sensing instrument, hyperspectral images now collect information of the ground with hundreds of wavelengths. This spectral information can be used to identify different materials, since each material should have its unique absorption spectrum.
Yung-Ling Wang, Hsuan Ren, Min-Yu Huang, Yang-Lang Chang   +3 more
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TREND EXTRACTION FOR SEASONAL TIME SERIES USING ENSEMBLE EMPIRICAL MODE DECOMPOSITION

Advances in Adaptive Data Analysis, 2011
In this paper, we investigate eligibility of trend extraction through the empirical mode decomposition (EMD) and performance improvement of applying the ensemble EMD (EEMD) instead of the EMD for trend extraction from seasonal time series. The proposed method is an approach that can be applied on any time series with any time scales fluctuations.
Mhamdi, Farouk, Poggi, Jean-Michel, Jaidane, Mériem   +2 more
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Ensemble empirical mode decomposition for high frequency ECG noise reduction

Biomedizinische Technik/Biomedical Engineering, 2010
An 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,
openaire   +2 more sources