What question did this study set out to answer?

To develop a multisource associate domain adaptation network capable of capturing both domain-invariant and domain-specific features for EEG emotion recognition across diverse subjects and sessions.

January 1, 2023IEEE Transactions on Instrumentation and Measurement

Multisource Associate Domain Adaptation for Cross-Subject and Cross-Session EEG Emotion Recognition

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To develop a multisource associate domain adaptation network capable of capturing both domain-invariant and domain-specific features for EEG emotion recognition across diverse subjects and sessions.
Constructed separate branches for multiple source domains under the assumption that distinct EEG recordings share common low-level features.
Extracted domain-specific features via one-to-one associate domain adaptation and computed weighted classifier scores based on distribution distance.
Evaluated model performance in cross-subject and cross-session setups using the SEED, DEAP, and SEED-IV benchmark datasets.
Cross-subject average classification accuracy reached 86.16% on SEED, 65.59% on DEAP, and 59.29% on SEED-IV.
Cross-session average classification accuracy reached 91.10% on SEED and 66.68% on SEED-IV, outperforming existing state-of-the-art domain adaptation methods.

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Implication

Algorithmic analysis demonstrates improved EEG emotion recognition across diverse subjects and sessions using multisource domain adaptation, indicating enhanced robustness for brain-computer systems.

Cite This Study

She et al. (2023) studied this question.

synapsesocial.com/papers/6a73244da3cf5acb16a0baaa https://doi.org/10.1109/tim.2023.3277985

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Implication

Algorithmic analysis demonstrates improved EEG emotion recognition across diverse subjects and sessions using multisource domain adaptation, indicating enhanced robustness for brain-computer systems.

Multisource Associate Domain Adaptation for Cross-Subject and Cross-Session EEG Emotion Recognition

Key Points

Discussion

Implication

Cite This Study

Multisource Associate Domain Adaptation for Cross-Subject and Cross-Session EEG Emotion Recognition

Key Points

Discussion

Implication

Cite This Study

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