The fNIRS-Based Emotion Recognition by Spatial Transformer and WGAN Data Augmentation Toward Developing a Novel Affective BCI

• Published in: IEEE transactions on affective computing Vol. 16; no. 2; pp. 875 - 890
• Main Authors: Si, Xiaopeng, Huang, He, Yu, Jiayue, Ming, Dong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.04.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Affective brain-computer interface (aBCI); Arousal; Artificial intelligence; Brain modeling; Brain research; cross-subject; Data augmentation; Decoding; Electroencephalography; Emotion recognition; Emotions; Functional near-infrared spectroscopy; functional near-infrared spectroscopy (fNIRS); Generative adversarial networks; Human-computer interface; Infrared spectra; Machine learning; Medical imaging; Near infrared radiation; self-attention; spatial; Spatial data; Spatial resolution; Spectroscopy; transformer; Transformers; wasserstein generative adversarial networks (WGAN)

The affective brain-computer interface (aBCI) facilitates the objective identification or regulation of human emotions. Current aBCI mainly relies on electroencephalography (EEG). However, research shows that emotions involve a large-scale distributed brain network. Compared to electroencephalograph...