TFM-Tokenizer learns a vocabulary of time-frequency motifs from single-channel EEG via a dual-path masked architecture and encodes signals into discrete tokens, reporting up to 11% Cohen's Kappa gains on benchmarks and 14% on ear-EEG sleep staging.
Eegpt: Pretrained transformer for universal and reliable representation of eeg signals
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Tokenizing Single-Channel EEG with Time-Frequency Motif Learning
TFM-Tokenizer learns a vocabulary of time-frequency motifs from single-channel EEG via a dual-path masked architecture and encodes signals into discrete tokens, reporting up to 11% Cohen's Kappa gains on benchmarks and 14% on ear-EEG sleep staging.