This paper proposes an emotion judgment system by using an electroencephalogram (EEG) feature concept base with premise of noises included. This method references the word concept association system, which associates one word with other plural words and decides the relationship between several words. In this proposed emotion judgment system, the source EEG is input and 42 EEG features are constructed by EEG data; the data are then calculated by spectrum analysis and normalization. All 2945 EEG data of 4 emotions in the EEG data emotion knowledge base are calculated by the degree of association for getting the nearest EEG data from the EEG feature concept base constructed by 2844 concepts. From the experiment, the accuracy of the proposed system was 55.9%, which was higher than the support vector machine (SVM) method. As this result, the chain structured feature of the EEG feature concept base and the efficiency by the calculation of degree of association for EEG data help reduce the influence of the noise.
electroencephalogram; EEG; emotion judgment; concept base; calculation of degree of association