Conference Paper

Discrimination between Two Mental States (Rest and Motor Image) Using Wavelet Transform and Neural Networks.

DOI: 10.1007/3-540-45493-4_5 Conference: Computational Intelligence, Theory and Applications, International Conference, 7th Fuzzy Days, Dortmund, Germany, October 1-3, 2001, Proceedings
Source: DBLP

ABSTRACT This paper presents a method for the processing and classification of electroencephalographic (EEG) signals linked to mental
states (rest and motor image) using the wavelet transform of these signals as input information of an LVQ neural network.
This system obtained a 70% correct qualification rate in the first recording session, a 50% rate in the second and an 80%
rate in the third, with a 75% classification success rate for the whole set of data. These results fall within the average
range obtained by other systems which require more information.

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