In this study, we present a new application to the study of the N400 related event component applied to the Brain Computer Interfaces (BCI) field. The N400 is classically defined in literature as an index of semantic integration mechanisms and it is sensitive to the difficulty with which the reader integrates the input within the semantic context, based on their expectations. By varying the level of violation of expectations in the semantic context and presenting sentences lacking the final word (cloze probability test) we want to train a classifier so that it can always complete the sentences in accordance with the expectations of the participant. The online classification is based on the average peak differences in three different conditions (target, semantically related and unrelated), where the amplitude of the N400 should correlate with the progressive and greater violation of semantic expectation. The findings can contribute significantly to this area of research that is still left with several unanswered questions as this research is one of the first to exploit the N400 in an online experiment.