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Cross-Subject Emotion Recognition Brain-Computer Interface Based on fNIRS and DBJNet.

Xiaopeng Si1,2, Huang He1,2, Jiayue Yu2,3

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Functional near-infrared spectroscopy (fNIRS) effectively decodes emotions across subjects using a novel deep learning model. This brain-computer interface advancement shows promise for real-world affective computing applications.

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Area of Science:

  • Neuroscience
  • Brain-Computer Interfaces
  • Affective Computing

Background:

  • Functional near-infrared spectroscopy (fNIRS) is a noninvasive brain imaging technique increasingly used for emotion recognition.
  • Current fNIRS emotion recognition research is primarily limited to within-subject analyses, lacking cross-subject generalization.
  • There is a need for robust methods to decode emotions across different individuals using fNIRS.

Purpose of the Study:

  • To develop and validate a cross-subject emotion recognition model using fNIRS data.
  • To construct a novel fNIRS emotion recognition database using video stimuli.
  • To introduce deep learning for cross-subject emotion decoding with fNIRS.

Main Methods:

  • Designed an emotion-evoking experiment using videos as stimuli.
  • Constructed a new fNIRS emotion recognition database.
  • Developed a dual-branch joint network (DBJNet) incorporating deep learning for cross-subject generalization.

Main Results:

  • The proposed DBJNet achieved 74.8% accuracy and 72.9% F1 score for distinguishing positive, neutral, and negative emotions.
  • High accuracy was observed in 2-category tasks: 89.5% (positive vs. neutral) and 91.7% (negative vs. neutral).
  • Ablation studies confirmed that the combined convolutional neural network and statistical branches yielded the best performance.

Conclusions:

  • fNIRS demonstrates significant potential for effective cross-subject emotion decoding.
  • The developed DBJNet model enables generalization to new participants, advancing fNIRS-based emotion recognition.
  • This research facilitates the development of fNIRS-based affective brain-computer interfaces.