An Approach to Emotion Recognition Using Brain Rhythm Sequencing and Asymmetric Features.

ABSTRACT: Emotion can be influenced during self-isolation, and to avoid severe mood swings, emotional regulation is meaningful. To achieve this, efficiently recognizing emotion is a vital step, which can be realized by electroencephalography signals. Previously, inspired by the knowledge of sequencing in bioinformatics, a method termed brain rhythm sequencing that analyzes electroencephalography as the sequence consisting of the dominant rhythm has been proposed for seizure detection. In this work, with the help of similarity measure methods, the asymmetric features are extracted from the sequences generated by different channel data. After evaluating all asymmetric features for emotion recognition, the optimal feature that yields remarkable accuracy is identified. Therefore, the classification task

SUBMITTER: Li JW 

PROVIDER: S-EPMC9415250 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature