Detecting response of somatosensory evoked potentials from averages with small number of epochs using Self-Organizing Map

The aim of this work was to use the Self-Organizing Map (SOM) algorithm to classify EEG signals collected during somatosensory stimulation. Third-six volunteers participated and the signals were classified as containing or not cortical stimuli-response. Five features were used to characterize the signals, referring to the averages' amplitude, latency and power spectral density using 500, 100 and 50 epochs. The SOM results clearly showed an adequate distinction between the two classes for 500 and 100 epochs. The SOM grid's sizes were determined by applying non-parametric bootstrap technique.