Dongming Zhao

Drift-gated and output-consistent continual learning for eeg seizure prediction

Long-term electroencephalography (EEG) seizure prediction on wearable hardware requires models that are small enough for local inference, responsive to patient-specific distribution shifts, and robust to catastrophic forgetting. We present a code-faithful continual-learning extension of SlimSeiz that targets the latter...