This study focuses on emotion recognition technology. The input signals are EEG and facial expression. The stimuli are based on a subset of movie clips that correspond to four specific areas of valance-arousal emotional space. In facial expression detection, one of the four basic emotional states is determined. In EEG detection, one of the three emotional intensities is determined. Emotion recognition is based on a decision-level fusion of both EEG and facial expression detection. The results show that the accuracy of information fusion detection is 89.5%, which is higher than that of facial expression (81.35%) or EEG detection (71.53%).