Results 161 to 170 of about 4,786,449 (207)
Some of the next articles are maybe not open access.
Control Engineering Practice, 2007
This paper focuses on a new method for characterizing oscillations in measurements from control loops in chemical processes. The proposed method uses a modified empirical mode decomposition (EMD) process to uncover all the zero-crossings in the data.
Raghunathan Rengaswamy +1 more
exaly +2 more sources
This paper focuses on a new method for characterizing oscillations in measurements from control loops in chemical processes. The proposed method uses a modified empirical mode decomposition (EMD) process to uncover all the zero-crossings in the data.
Raghunathan Rengaswamy +1 more
exaly +2 more sources
An empirical mode decomposition (EMD)-based scheme for alcoholism identification
Pattern Recognition Letters, 2019Abstract Alcohol addiction can severely affect the brain structure and function. The brain state is usually determined with the help of the ElectroEncephaloGram (EEG) signals, which consist of different neuronal activities that are recorded from the different regions of the brain.
M. Thilagaraj, M. Pallikonda Rajasekaran
openaire +1 more source
Removal of blink from EEG by Empirical Mode Decomposition (EMD)
The 5th 2012 Biomedical Engineering International Conference, 2012The electroencephalographic signals (EEG) are rather weak and contaminated with different artifacts that have biological and external sources. Among these artifacts, blinks and eye movements are the most common of them. In this paper, we introduce a new method, Empirical Mode Decomposition (EMD), for removal of blink contamination from EEG signal.
Mohammad Shahbakhti +2 more
openaire +1 more source
Dynamic body postures recognition with WiFi based on empirical mode decomposition (EMD)
2017 17th International Symposium on Communications and Information Technologies (ISCIT), 2017In this paper, a new method of dynamic posture recognition using Wi-Fi signal based on empirical mode decomposition (EMD) is proposed. Totally different from computer vision approach and traditional sensor-based approach, the proposed novel posture recognition method does not require line-of-sight and sensors placed in the body.
Min Ye, Ting Jiang
openaire +2 more sources
International Journal of Neural Systems, 2012
Epilepsy is a global disease with considerable incidence due to recurrent unprovoked seizures. These seizures can be noninvasively diagnosed using electroencephalogram (EEG), a measure of neuronal electrical activity in brain recorded along scalp. EEG is highly nonlinear, nonstationary and non-Gaussian in nature.
Roshan Joy Martis +7 more
openaire +5 more sources
Epilepsy is a global disease with considerable incidence due to recurrent unprovoked seizures. These seizures can be noninvasively diagnosed using electroencephalogram (EEG), a measure of neuronal electrical activity in brain recorded along scalp. EEG is highly nonlinear, nonstationary and non-Gaussian in nature.
Roshan Joy Martis +7 more
openaire +5 more sources
On the Use of Empirical Mode Decomposition (EMD) for Alzheimer’s Disease Diagnosis
2015Alzheimer’s Disease (AD) is considered one of the most common form of dementia; it involves a progressive decline in cognitive function because of pathological modifications or damage of the brain. One of the major challenges is to develop tools for early diagnosis and disease progression.
Domenico Labate +4 more
openaire +1 more source
Application of empirical mode decomposition (EMD) filtering at magnetotelluric time-series data
AIP Conference Proceedings, 2020A noise that recorded at magnetotelluric acquisition data makes the data quality not good enough, so the information obtained after data processing might not be correct or not suitable for the subsurface condition. Several characters of noisy magnetotelluric data are the spiky shaped and non-stationarity time-series curves.
Nugroho Syarif Setiawan +6 more
openaire +1 more source
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010
The pulstile components of photoplethysmography (PPG) contain valuable information about a subject's cardiovascular and metabolic systems. Pulse rate is one of the most significant vital signs that can be extracted from PPG signals. However, patient movement, especially movement at the measurement sites, such as fingers, can disturb the PPG's light ...
Qian, Wang, Ping, Yang, Yuanting, Zhang
openaire +2 more sources
The pulstile components of photoplethysmography (PPG) contain valuable information about a subject's cardiovascular and metabolic systems. Pulse rate is one of the most significant vital signs that can be extracted from PPG signals. However, patient movement, especially movement at the measurement sites, such as fingers, can disturb the PPG's light ...
Qian, Wang, Ping, Yang, Yuanting, Zhang
openaire +2 more sources
Analysis of Dynamic Test Signal for Bolt Using Empirical Mode Decomposition (EMD)
2010 International Conference on E-Product E-Service and E-Entertainment, 2010Based on the improved empirical mode decomposition (EMD) algorithm, a signal processing method for dynamic testing of the bolt anchorage system is proposed. As a self-adaptive approach, EMD method can be used to decompose the local characteristics of the no-stationary and nonlinear signals into several fluctuations and trend items with different time ...
Ying Li, Dongzi Pan
openaire +1 more source
Applying empirical mode decomposition (EMD) and entropy to diagnose circuit breaker faults
Optik, 2015Abstract In this paper, a new method to extract characteristic parameters from vibration signal of HV (high voltage) CB (circuit breakers) is proposed based on the empirical mode decomposition (EMD)-entropy. First, the normal signal and several fault signals are decomposed with empirical mode, and then extraction and selection the IMF function ...
Liu Mingliang +3 more
openaire +1 more source