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 pes in a sophisticated manner. Our continuous enhancement has lead to the current development of the proposed method, Sandwich SPR (SSPR). The SSPR performs the reconstruction of source signal in an effective way better than the related SPR method. When this technique was applied on artificial Visual Evoked Potential (VEP) signals contaminated with background electroencephalogram (EEG), with a focus on extracting P3 parameters, it was found to be feasible shown by the resulting ...
It is desirable to determine from electroencephalography (EEG) or magnetoencephalography (MEG) the t...
When decomposing single trial electroencephalography it is a challenge to incorporate prior physiolo...
The evoked potential (EP) is modeled as the sum of gaussian pulses whose amplitudes, latencies and w...
In single trial analysis, when using Principal Component Analysis (PCA) to extract Visual Evoked Pot...
Here we present a novel approach to detect P300 wave in single trial Visual Event Related Potential ...
In this paper, repeated applications of Principal Component Analysis (PCA) are proposed to reduce ba...
In this paper, Principal Component Analysis (PCA) is used to reduce noise from multi-channel Visual ...
Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-n...
Steady-state Visual Evoked Potential (SSVEP) outperforms the other types of ERPs for Brain-computer ...
This study presents an analysis on Visual Evoked Potentials (VEPs) recorded mainly from the occipita...
We describe a method to extract single trial Visual Evoked Potential (VEP) buried in ongoing Electro...
The most popular paradigm in BCIs is the steady-state visually evoked potential (SSVEP) due to their...
Steady-state Visual Evoked Potential (SSVEP) outperforms the other types of ERPs for Brain-computer ...
Contrasting event-related potentials (ERPs) generated under different experimental conditions and in...
Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-n...
It is desirable to determine from electroencephalography (EEG) or magnetoencephalography (MEG) the t...
When decomposing single trial electroencephalography it is a challenge to incorporate prior physiolo...
The evoked potential (EP) is modeled as the sum of gaussian pulses whose amplitudes, latencies and w...
In single trial analysis, when using Principal Component Analysis (PCA) to extract Visual Evoked Pot...
Here we present a novel approach to detect P300 wave in single trial Visual Event Related Potential ...
In this paper, repeated applications of Principal Component Analysis (PCA) are proposed to reduce ba...
In this paper, Principal Component Analysis (PCA) is used to reduce noise from multi-channel Visual ...
Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-n...
Steady-state Visual Evoked Potential (SSVEP) outperforms the other types of ERPs for Brain-computer ...
This study presents an analysis on Visual Evoked Potentials (VEPs) recorded mainly from the occipita...
We describe a method to extract single trial Visual Evoked Potential (VEP) buried in ongoing Electro...
The most popular paradigm in BCIs is the steady-state visually evoked potential (SSVEP) due to their...
Steady-state Visual Evoked Potential (SSVEP) outperforms the other types of ERPs for Brain-computer ...
Contrasting event-related potentials (ERPs) generated under different experimental conditions and in...
Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-n...
It is desirable to determine from electroencephalography (EEG) or magnetoencephalography (MEG) the t...
When decomposing single trial electroencephalography it is a challenge to incorporate prior physiolo...
The evoked potential (EP) is modeled as the sum of gaussian pulses whose amplitudes, latencies and w...