2.1.2. DEAP Dataset

The DEAP dataset (Koelstra et al., 2011) can be found at http://www.eecs.qmul.ac.uk/mmv/datasets/deap/. It includes 32-channel EEG signals and peripheral physiological signals such as GSR(galvanic skin response) signals, EOG(electro-oculogram) signals, EMG(electromyography) signals, PPG(photoplethysmograph) signals, temperature, and status. All data have been down-sampled to 128 Hz, whereby the EEG signal data became a 60 s test signal and a 3 s baseline. A zero-phase bandpass filter of 4–45 Hz was applied. In this study, the 32-channel EEG data were divided into two classes according to their arousal status: positive (more than 6) and negative (less than 4).

The DEAP dataset consists of two parts. The first part contains the ratings from an online self-assessment in which 120 1-min extracts of music videos were rated by 14–16 volunteers based on arousal, valence, and dominance. The second part includes the participant ratings, physiological recordings, and facial videos from an experiment in which 32 volunteers watched a subset of 40 of the above music videos. The EEG and physiological signals were recorded and each participant rated the videos as above. For 22 participants, frontal face videos were also recorded. At the end of each video, the participants were required to fill out a self-assessment form of their arousal, ranging from inactive (1) to active (9), their valence, ranging from unpleasant (1) to pleasant (9), and their dominance feelings, ranging from helpless and weak (1) to empowered (9). Figure 3 shows the two-dimensional emotional model of the DEAP dataset. Each dimension of DEAP is described in Table 3. In experiments with the DEAP dataset, we only used data from combined frequency bands.

Two-dimensional emotional model.

DEAP dataset.