Image Discrimination of Human’s Visual Perception for Thought Translational Device
Abstract
Electroencephalography (EEG) signal is a biological signal which can be associated to the mental task of a person. A brain-computer interface (BCI) can be designed such that the mental activity accounted for the visual perception of a person can be recorded and subsequently converted into a control signal for controlling the movement of a wheelchair. Multi-layered perceptrons were designed to discriminate the different brain activities when the subject was being presented with different visual stimuli. The trained network models have yielded an average accuracy of 93.92%.
Keywords Brain Computer Interface (BCI); Electroencenphalography (EEG); Visual Perception;; Power Spectral Density (PSD); Multi-layered Perceptron Neural Network (MLP), Levenberg-Marquardt Training Algorithm (LM)
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