CAAST-Net: Causality-Aware Spiking Transformer with Flask API for EEG-Based Seizure Detection

Epileptic seizure detection from electroencephalogram (EEG) signals is an essential task for real-time neurological monitoring. Traditional models face challenges with interpretability, energy efficacy, and capturing temporal causality in neural data. To address these drawbacks, this manuscript proposes a Causality-Aware Attention with Spiking Transformer Network (CAAST-Net). The frequency-domain features are extracted by fast Fourier transform (FFT) to acquire band power across five canonical E