Results 1 to 10 of about 1,862 (208)

Arrhythmia ECG Noise Reduction by Ensemble Empirical Mode Decomposition [PDF]

Sensors, 2010
A novel noise filtering algorithm based on ensemble empirical mode decomposition (EEMD) is proposed to remove artifacts in electrocardiogram (ECG) traces.
Kang-Ming Chang
doaj   +5 more sources

An effective electrocardiogram segments denoising method combined with ensemble empirical mode decomposition, empirical mode decomposition, and wavelet packet

IET Signal Processing, 2023
Electrocardiogram (ECG) is the most extensively applied diagnostic approach for heart diseases. However, an ECG signal is a weak bioelectrical signal and is easily disturbed by baseline wander, powerline interference, and muscle artefacts, which make ...
Yaru Yue, Chengdong Chen, Xiaoyuan Wu, Xiaoguang Zhou   +3 more
doaj   +2 more sources

A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition [PDF]

Sensors, 2013
In this paper, a human electrocardiogram (ECG) identification system based on ensemble empirical mode decomposition (EEMD) is designed. A robust preprocessing method comprising noise elimination, heartbeat normalization and quality measurement is proposed to eliminate the effects of noise and heart rate variability.
Zhidong Zhao
exaly   +4 more sources

Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode Decomposition

Sensors, 2013
The vibration based signal processing technique is one of the principal tools for diagnosing faults of rotating machinery. Empirical mode decomposition (EMD), as a time-frequency analysis technique, has been widely used to process vibration signals of ...
Yaguo Lei, Naipeng Li, Jing Lin, Sizhe Wang   +3 more
doaj   +3 more sources

On the Use of Ensemble Empirical Mode Decomposition for the Identification of Bridge Frequency from the Responses Measured in a Passing Vehicle

Infrastructures, 2019
In this paper, ensemble empirical mode decomposition (EEMD) and empirical mode decomposition (EMD) methods are used for the effective identification of bridge natural frequencies from drive-by measurements.
Licheng Zhu, Abdollah Malekjafarian
doaj   +3 more sources

A comparative study of single-channel signal processing methods in fetal phonocardiography.

PLoS ONE, 2022
Fetal phonocardiography is a non-invasive, completely passive and low-cost method based on sensing acoustic signals from the maternal abdomen. However, different types of interference are sensed along with the desired fetal phonocardiography.
Katerina Barnova, Radana Kahankova, Rene Jaros, Martina Litschmannova, Radek Martinek   +4 more
doaj   +1 more source

Analysis of Vehicle Platform Vibration Based on Empirical Mode Decomposition

Shock and Vibration, 2021
Vehicle platform vibration (VPV) directly affects the measurement accuracy of precise measuring instrument (PMI) fixed on it. In order to reduce the influences of VPV on measurement accuracy, it is necessary to perform vibration isolation between vehicle
Chengwu Shen, Zhiqian Wang, Chang Liu, Qinwen Li, Jianrong Li, Shaojin Liu   +5 more
doaj   +1 more source

Effect of Multi-Scale Decomposition on Performance of Neural Networks in Short-Term Traffic Flow Prediction

IEEE Access, 2021
Numerous studies employ multi-scale decomposition to improve the prediction performance of neural networks, but the grounds for selecting the decomposition algorithm are not explained, and the effects of decomposition algorithms on other performance of ...
Haichao Huang, Jingya Chen, Xinting Huo, Yufei Qiao, Lei Ma   +4 more
doaj   +1 more source

Improving the prediction accuracy of river inflow using two data pre-processing techniques coupled with data-driven model [PDF]

PeerJ, 2019
River inflow prediction plays an important role in water resources management and power-generating systems. But the noises and multi-scale nature of river inflow data adds an extra layer of complexity towards accurate predictive model.
Hafiza Mamona Nazir, Ijaz Hussain, Muhammad Faisal, Elsayed Elsherbini Elashkar, Alaa Mohamd Shoukry   +4 more
doaj   +2 more sources

Electrocardiogram Analysis by Means of Empirical Mode Decomposition-Based Methods and Convolutional Neural Networks for Sudden Cardiac Death Detection

Applied Sciences, 2023
Sudden cardiac death (SCD) is a global health problem, which represents 15–20% of global deaths. This type of death can be due to different heart conditions, where ventricular fibrillation has been reported as the main one.
Manuel A. Centeno-Bautista, Angel H. Rangel-Rodriguez, Andrea V. Perez-Sanchez, Juan P. Amezquita-Sanchez, David Granados-Lieberman, Martin Valtierra-Rodriguez   +5 more
doaj   +1 more source