Understanding human implicit intention based on frontal electroencephalography (EEG)

The objective of human computer interface (HCI) research is to make machine that understands human intention with high accuracy. In the future, machine will be able to understand human intention and communicate with human even though there is no explicit expression such as speech, gesture, etc. In this study, a new experiment design is proposed to understand human intention by using electroencephalography (EEG). Two types of stimulus are given to the subjects; affirmative and negative sentences. Each sentence was separated by two blocks which are contents and sentence end. Subjects were asked to make a decision of agreement or disagreement after sentence end is shown. Based on the EEG analysis, intention to the sentences was found while seeing contents, i.e., before giving an explicit answer. It is shown that decision making is done before the end of the sentence, and answering “Yes” or “No” is determined only up to the sentence end. This study shows the relationship of implicit intention and average event-related potentials (ERPs) at the frontal sites and how to predict implicit intention based on the central frontal ERPs using support vector machine (SVM).