EEG-based emotion-adaptive advertising

Nowadays, advertising is a part of our daily life driving consumer behavior, social behavior, personal preferences, etc. As volumes of advertisements increase people become more immune to different types of advertisements. To make the advertisements more efficient is a challenging problem. It is confirmed in the experiments that the emotions felt by the participants during the viewing of an advertisement influence on the effectiveness of the advertisement. In this paper, we propose an emotion-enabled algorithm that can be used to personalize an advertising movie according to the user's current emotions to make the advertisement more efficient. Electroencephalogram (EEG) signals are used to recognize emotions of the user in real time. The proposed emotion-enabled algorithm can adjust the scene of the movie based on the real-time emotion feedback. An advertising movie that applies the emotion-enabled algorithm is designed and implemented.