DEEMD-SPP: A Novel Framework for Emotion Recognition Based on EEG Signals.

ABSTRACT: Electroencephalography (EEG) is one of the most widely-used biosignal capturing technology for investigating brain activities, cognitive diseases, and affective disorders. To understand the underlying principles of brain activities and affective disorders using EEG data, one of the fundamental tasks is to accurately identify emotions from EEG signals, which has attracted huge attention in the field of affective computing. To improve the accuracy and effectiveness of emotion recognition based on EEG data, previous studies have successfully developed numerous feature extraction methods and classifiers. Among them, ensemble empirical mode decomposition (EEMD) is an efficient signal decomposition technique for extracting EEG features. It can alleviate the mode-mixing problem by adding white no

SUBMITTER: Chen J 

PROVIDER: S-EPMC9091650 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature