Synthetic EEG Dataset for CNN-LSTM Training: Clean and Artifact-Contaminated Signals
This dataset consists of synthetically generated EEG and EMG signals designed for training Convolutional Neural Networks (CNNs) in artifact detection and removal. The dataset includes both clean EEG signals and EEG signals contaminated with simulated EMG artifacts from various sources.
Synthetic Epileptic Spike EEG Database (SESED-WUT)
The database contains EEG, EMG, and EOG signals with artificially generated epileptic spikes. The recordings were performed using the g.USBamp 2.0 amplifier. Data were collected from 5 EEG channels (C3, Cz, C4, Fz, Fp1), 1 EOG channel (VEOG), and 3 EMG channels (Nape, Cheek, Jaw). The signals were sampled at 256 Hz and processed with a bandpass filter (0.1–100 Hz) and a notch filter (48–52 Hz).
