Effects of Data Augmentation Method Borderline-SMOTE on Emotion Recognition of EEG Signals Based on Convolutional Neural Network

• Published in: IEEE access Vol. 9; pp. 47491 - 47502
• Main Authors: Chen, Yu, Chang, Rui, Guo, Jifeng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Arousal; Artificial intelligence; Artificial neural networks; Borderline-Synthetic minority oversampling technique; Brain modeling; Classification algorithms; convolutional neural network; Data augmentation; Datasets; Electroencephalogram; Electroencephalography; Emotion recognition; Emotions; Feature extraction; Human-computer interface; Machine learning; Neural networks; Oversampling; Pattern recognition; Physiology; Standard data

In recent years, with the continuous development of artificial intelligence and brain-computer interface technology, emotion recognition based on physiological signals, especially electroencephalogram signals, has become a popular research topic and attracted wide attention. However, the imbalance o...