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eess.SP2025
SpellerSSL: Self-Supervised Learning with P300 Aggregation for Speller BCIs
Jiazhen Hong, Geoff Mackellar, Soheila Ghane
Electroencephalogram (EEG)-based P300 speller brain-computer interfaces (BCIs) face three main challenges: low signal-to-noise ratio (SNR), poor generalization, and time-consuming…
eess.SP2024
EEG2Rep: Enhancing Self-supervised EEG Representation Through Informative Masked Inputs
Navid Mohammadi Foumani, Geoffrey Mackellar, Soheila Ghane +3
Self-supervised approaches for electroencephalography (EEG) representation learning face three specific challenges inherent to EEG data: (1) The low signal-to-noise ratio which cha…