Recently, there has been a significant amount of work on the recognition of human emotions. The results of the work can be applied in real applications, for example in market surveyor neuromarketing. This interesting problem requires to recognize naturally human emotions. A popular approach uses key information from electroencephalography (EEG) signals to identify human emotions. In this paper, the authors proposed an emotion recognition model based on the Russell's circumplex model, Higuchi Fractal Dimension (HFD) algorithm and Support Vector Machine' (SVM) as a classifier. the authors extensively implemented the model in several test data. The experimental results showed that a model can recognize four basic states of human emotion in real-time with average accuracy 61 percent.