# PhysioWave-T

PhysioWave-T compresses multiscale wavelet analysis into a fixed-length token sequence: dynamic scale folding recombines the subbands into one signal before tokenization, so decomposition depth changes what each token carries rather than how long the sequence is. Across four EEG routes, folding cuts Transformer latency by 4.0–7.2 times and peak memory by 6.8–12.7 times over scale expansion without accuracy loss, and the 30M-parameter EEG encoder leads eight of nine metrics against BENDR, BIOT, LaBraM and EEGPT.

PhysioWave-T compresses multiscale wavelet analysis into a fixed-length token sequence: dynamic scale folding recombines the subbands into one signal before tokenization, so decomposition depth changes what each token carries rather than how long the sequence is. Across four EEG routes, folding cuts Transformer latency by 4.0–7.2 times and peak memory by 6.8–12.7 times over scale expansion without accuracy loss, and the 30M-parameter EEG encoder leads eight of nine metrics against BENDR, BIOT, LaBraM and EEGPT.