As the communication between brain and computer becomes more accessible the extraction of important features of electrophysiological signals is an essential step in artificial communication systems. This paper proposes the usage of the Empirical Mode Decomposition to identify characteristics of the P300 signal and classify target and non-target signals using a feedforward neural network. The results show that through the usage of EMD method it is possible to identify the P300 signal using low volume of data.