Abstract:
The purpose of this paper is to analyze the
electroencephalogram (EEG) signals of imaginary left and
right hand movements, an application of Brain-Computer
Interface (BCI). We propose here to use an Adaptive Neuron-
Fuzzy Inference System (ANFIS) as the classification
algorithm. ANFIS has an advantage over many classification
algorithms in that it provides a set of parameters and linguistic
rules that can be useful in interpreting the relationship between
extracted features. The continuous wavelet transform will be
used to extract highly representative features from selected
scales. The performance of ANFIS will be compared with the
well-known support vector machine classifier.
