Open AccessA study on wavelet analysis of SSVEP Signals
Author(s) -
Bincy Babu,
R. Chandrasekaran,
Josline Elsa Joseph,
Thella Shalem Rahul,
T. R. Thamizhvani,
A Josephin Arockia Dhivya
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.25.12354
Subject(s) - electroencephalography , wavelet , pattern recognition (psychology) , brain–computer interface , feature extraction , computer science , feature (linguistics) , artificial intelligence , set (abstract data type) , speech recognition , wavelet transform , spectral analysis , psychology , neuroscience , linguistics , philosophy , physics , quantum mechanics , spectroscopy , programming language
Almost every Brain Control Interfcae (BCI) system is framed based on Steady State Visual Evoked Potential (SSVEP) which is predicted through distinguishing overriding frequency components in Electroencephalography (EEG) signals. The proposed system aims in accurate feature extraction of SSVEP signals. Power spectral analysis and wavelet analysis are done for feature analysis. The feature set variation for male and female subjects are obtained. Compared power spectral estimation and wavelet analysis, merits and demerits of each approach can be identified from the outcomes. It offers a theoretical reference of practical choice for BCI application.