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Single cycle analysis of the Steady State Visual Evoked Potential (SSVEP) response allows use of standard significance tests to determine a subject's gaze. This allows standard criterion levels to be set across all subjects rather than individually by empirical analysis. Furthermore once a subject's gaze has been classified it is possible to extract a notion of expected phase to a SSVEP stimulus....
In this paper, a novel method to recognise persons using their brain patterns is proposed. These brain patterns are obtained when the individuals perceive a picture. High frequency brain energy is used as features that are classified by Elman backpropagation neural network. The experimental results using 1600 brain signals from 40 individuals give average classification rate of 96.63%. This pilot...
We investigate the decision making ability of subjects with a history of long-term intoxicant (alcohol) consumption in relation to short-term visual memory using P3 amplitudes obtained from single trial visual evoked potential (VEP) signals. This is made possible by means of digital filtering and principal component analysis (PCA). The results show a significantly lower P3 amplitude for these subjects...
It has been shown previously that recognizing persons using 40 Hz electroencephalogram (EEG) oscillations is possible. In the method, features were computed from the visual evoked potential (VEP) signals recorded from 61 electrodes while subjects perceived a picture. Here, two modifications have been proposed to improve the classification performance: principal component analysis (PCA) to reduce the...
In this paper, repeated applications of principal component analysis (PCA) are proposed to reduce background electroencephalogram (EEC) artifact from multi-channel and multi-trial visual evoked potential (VEP) signals. This allows single trial analysis of VEP signals. PCA has been used for noise reduction but the method of repeated applications of PCA is novel. In the study here, PCA was applied in...
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