Feature extraction from EEG signals in SSVEP spelling system

It is known that Electroencephalograph (EEG) signal shows specific responses according to the event (e.g. visual stimulus, cognition and motor imagery). Especially, by classifying short time EEG signal, features are used to control an electronic device (such system is called brain computer interface...

Full description

Saved in:
Bibliographic Details
Main Authors: Yamaguchi, Tomonari, Omori, Kana, Irie, Jun, Inoue, Katsuhiro
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
AR-model
BCI
EEG
EEG-Speller
Electroencephalography
Feature extraction
Fourier analysis
Harmonic analysis
Laplace equations
Pattern recognition
SSVEP
Visualization
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:It is known that Electroencephalograph (EEG) signal shows specific responses according to the event (e.g. visual stimulus, cognition and motor imagery). Especially, by classifying short time EEG signal, features are used to control an electronic device (such system is called brain computer interface: BCI). In this study, we tried to construct SSVEP type EEG spelling system which uses response with cycle visual stimulus. Feature extraction methods from EEG signal during visual stimulus are discussed.