EEG-Based Emotion Recognition Using Quadratic Time-Frequency Distribution.

ABSTRACT: Accurate recognition and understating of human emotions is an essential skill that can improve the collaboration between humans and machines. In this vein, electroencephalogram (EEG)-based emotion recognition is considered an active research field with challenging issues regarding the analyses of the nonstationary EEG signals and the extraction of salient features that can be used to achieve accurate emotion recognition. In this paper, an EEG-based emotion recognition approach with a novel time-frequency feature extraction technique is presented. In particular, a quadratic time-frequency distribution (QTFD) is employed to construct a high resolution time-frequency representation of the EEG signals and capture the spectral variations of the EEG signals over time. To reduce the dimensionalit

SUBMITTER: Alazrai R 

PROVIDER: S-EPMC6111567 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature