Method for detecting music to match the user’s mood in prefrontal cortex electroencephalogram activity based on individual characteristics
In this paper, we propose a method for detecting the music to match a user's mood in prefrontal cortex electroencephalogram (EEG) activity. The EEG frequencies analyzed are the components that contain significant and immaterial information. We focused on the combinations of the significant frequency. These frequency combinations are thought to express individual characteristics of EEG activity. In the proposed method, we calculate the percentage of the spectrum of these frequency combinations that does not include the noise frequency components and evaluates whether the music matches the user's mood through a simple threshold processing. Then, a genetic algorithm (GA) is used to specify the frequency of individual characteristics on the EEG. Threshold values that used the threshold processing is determined in the GA. Finally, the performance of the proposed method is evaluated using real EEG data.