HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography

Understand

Electroencephalography (EEG) classification techniques have been widely studied for human behavior and emotion recognition tasks.

• But it is still a challenging issue since the data may vary from subject to subject, may change over time for the same subject, and maybe heterogeneous.
• Recent years, increasing privacy-preserving demands poses new challenges to this task.
• The data heterogeneity, as well as the privacy constraint of the EEG data, is not concerned in previous studies.