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This paper evaluates the single trial extraction of Visual Evoked Potential (VEP) signal. Single trial extraction of VEP contributes in the integration of fMRI-EEG application as well as in the Brain Computer Interface application. The extraction is performed by using the Fast Partial Least Square (PLS) algorithm. The extraction of the desired VEP signals, both in artificial and real Electroencephalography...
The electroencephalogram (EEG) is a common noninvasive method for detecting the brain injuries or functional disturbances. Clinical interpretation of the EEG is used for various applications that analyze the brain activity. In many cases it is necessary to have an EEG monitoring system to evaluate the brain activity and a key component of such a system is the acquisition circuitry. This paper presents...
Electroencephalography (EEG) signal between normal and special children is slightly different. Different types of special children will generate different shape of EEG patterns depend on their neurological function. This paper demonstrates the classification of EEG signal for special children: to determine and to classify level and pattern of EEG signal for autism and Down syndrome children. EEG signal...
The paper presents an on-line brain-computer interface (BCI) based on visual evoked potential (VEP) P300. The BCI is applied to control a multi-DOF manipulator. This BCI system includes five modules which are visual stimulator, signal acquisition, data processing, communication and motion control of manipulator. Stimulation program and experimental scheme are designed based on LabVIEW platform and...
Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is increasingly used to monitor the brain activity. The interactions between the scanner magnetic field, the patient's body, and the EEG electrodes generate a pulsation artifact called ballistocardiogram (BCG) which is synchronized with the patient's heart beat. The BCG artifact is considered here...
To develop a method of extract magnocellular (M) and parvocellular (P) components from VEP, the nonlinear system identification method using pseudorandom binary sequence (PRBS) stimulation combined with swept parameter technique was examined. VEP elicited by achromatic sinusoidal grating reverse based on PRBS was recorded and their binary kernels were calculated as cross-correlation between PRBS and...
The goal of this study was to experimentally investigate the influence of the white matter (WM) anisotropy on the EEG source localization. We acquired both visual evoked potential (VEP) and functional MRI (fMRI) data from three human subjects presented with identical visual stimuli. A finite element method (FEM) head model with or without incorporating the WM anisotropy was built to solve the EEG...
Engineering analysis has been utilized with great success over the past few decades to characterize physiological systems. For example, system identification approaches have been developed to describe the linear and nonlinear properties of such systems in a very general way, allowing for new insights to be made into physiological function. Recent work has seen the application of these techniques to...
Dominant rhythm in electroencephalographic (EEG) records is seen at the posterior to occipital region as a primary component of background activity during waking state with closed eyes and is decreased or disappeared by the exogenous factors such as visual stimuli to eyes and so on. Visual evoked potential (VEP) can also be seen in EEG at the posterior to occipital regions during photic stimulation...
A novel de-noising method based on wavelet transform is presented based on the good localization characteristic of the wavelet transform both in time and frequency domain, which can make happen the extraction of visual evoked potentials in single training sample from the EEG background noise in favor of studying the changes between the single sample response. The information is probably related with...
Based on the good localization characteristic of the wavelet transform both in time and frequency domain, a de-noising method based on wavelet transform is presented, which can make happen the extraction of visual evoked potentials in single training sample from the EEG background noise in favor of studying the changes between the single sample response. The information is probably related with the...
The activity generated in the brain in response to external stimulations which is named the evoked potential (EP) is typically buried in the background EEG. Because of the low signal to noise ratio of EPs, it is difficult to record single trial evoked potentials. The traditional technique which is based on ensemble averaging destroys the dynamic information of single trials. In this paper, a new method...
Based on the good localization characteristic of the wavelet transform both in time and frequency domain, a de-noising method based on wavelet transform is presented, which can make happen the extraction of visual evoked potentials in single training sample from the EEG background noise in favor of studying the changes between the single sample response. The information is probably related with the...
The goal of our research is to design an EEG BCI (brain computer interface) system and develop techniques for helping the serious disabled with spine/central nerve injury, motor neuron disease or without upper limb/foot. In our research, the brain wave amplifier we used is the NuAmps amplifier and the acquisitive/analytic software for EEG is named "Scan 4.3". Both of them were developed...
The aperture problem is the one of the experiments to analyze binding mechanism of the space recognition with the human visual pathway. Nishina has already insisted that recognition of visual perception by the aperture problem depends in display time. In this paper, we discuss how other experimental parameters, e.g., radius, distance between circles, and speed of bar depend with recognition rate by...
In this paper, we explore visually evoked potentials (VEPs) as a potential tool for biometric identification. Using a clinical stimulation paradigm, single channel pattern onset VEPs are recorded from raw EEG from 10 healthy male subjects aged between 20 and 24. Following this, two feature extraction techniques are employed to characterize the signals. Specifically, a novel, physiologically relevant...
The visual evoked potential (VEP) has long established itself as a useful diagnostic tool for clinical use. The VEP is typically recorded in clinical environments due to equipment and experimental set-up. An alternative is proposed in this paper, whereby a light-weight, portable neurological monitor using active dry-electrodes is proposed and VEP data compared against clinically recorded data. It...
We propose a system for estimating driver attention levels using Visually evoked potentials (VEP), computed from the EEG signals of the visual cortex. We investigate the use of both steady state VEP (SSVEP) and pattern onset VEP (POVEP) for this purpose. The subject fixates on a flickering stimulus, generating a Steady State VEP (SSVEP). Occasionally, a random stimulus is flashed on the screen, and...
Using imitating-natural-reading induced potentials as communication carriers, we are constructing a brain-computer interface based mental speller which enables users to interaction with computers. The carriers were induced in this way: in a trial, sentences consisted of target and non-target symbols were moving smoothly from right to left through a little visual window at the center of computer screen...
In single trial source separation problem of VEP signals, the selection of legitimate Principal Components (PCs) is an important phenomenon. The Spectral Power Ratio (SPR) method developed by us earlier for PCA has proven to be capable of selecting only the required PCs in a sophisticated manner. Our continuous enhancement has lead to the current development of the proposed method, Sandwich SPR (SSPR)...
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