Brain-computer Interfaces (BCI) is a significant communication channel, support a handicap people from suffering of disabilities such as amyotrophic lateral sclerosis (ALS). A multi-pattern of visual stimulus based on Steady-state Evoked Potential (SSVEP) is extract a particular stimulation to continuous pragmatic brain response. In this empirical study, which is depend on EEG signals by evoke ...

An efficient frequency recognition method is very important for SSVEP-based BCI systems to improve the information transfer rate (ITR). To address this aspect, for the first time, likelihood ratio test (LRT) was utilized to propose a novel multichannel frequency recognition method for SSVEP data. The essence of this new method is to calculate the association between multichannel EEG signals and...

OBJECTIVE The steady-state visual evoked potential (SSVEP) is an electroencephalographic response to flickering stimuli generated partly in primary visual area V1. The typical 'cruciform' geometry and retinotopic organization of V1 is such that certain neighboring visual regions project to neighboring cortical regions of opposite orientation. Here, we explored ways to exploit this organization ...

The present study examined if viewing affective stimuli alters subsequent visual processing, as indexed by steady-state visual potentials (ssVEPs) and behavioral performance in an orientation discrimination task. Participants viewed task-irrelevant but emotionally arousing pictures from the International Affective Picture System (1 s) followed by a target stimulus stream consisting of low (2 cp...

A brain-machine interface (BMI) is an interface technology that uses neurophysiological signals from the brain to control external machines. Recent invasive BMI technologies have succeeded in the asynchronous control of robot arms for a useful series of actions, such as reaching and grasping. In this study, we developed non-invasive BMI technologies aiming to make such useful movements using th...

How to encode as many targets possible with a limited-frequency resource is difficult problem in the practical use of steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) speller. To solve this problem, study developed novel method called dual-frequency biased coding (DFBC) tag SSVEP-based 48-character virtual speller, which each target encoded permutation sequence ...

Various spatial filters have been proposed to enhance the target identification performance of steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). The current methods only extract target-related information from corresponding stimulus learn filter parameter. However, SSVEP data neighboring stimuli also contain frequency stimulus, which could be utilized further ...

The stability of the steady-state visual evoked potentials (SSVEPs) across trials and subjects makes them a suitable tool for the investigation of the visual system. The reproducible pattern of the frequency characteristics of SSVEPs shows a global amplitude maximum around 10 Hz and additional local maxima around 20 and 40 Hz, which have been argued to represent resonant behavior of damped neur...

SSVEP is a kind of BCI technology with advantage of high information transfer rate. However, due to its nature, frequencies could be used as stimuli are scarce. To solve such problem, a stimuli encoding method which encodes SSVEP signal using Frequency Shift-Keying (FSK) method is developed. In this method, each stimulus is controlled by a FSK signal which contains three different frequencies t...

This paper describes some new approaches for the feature extraction of SSVEP signal in EEG signal processing. One of them is Canonical Correlation Analysis (CCA) and another one is CWT along with ANN. Basically CCA is applied to analyze the frequency components of SSVEP in EEG. The essence of this method is to extract narrowband frequency components of SSVEP in EEG. The CWT offers a valuable to...