EEG Datasets

EEG datasets are collections of brainwave recordings used to study brain activity and develop brain-computer interfaces (BCIs). Current research focuses on improving the accuracy and interpretability of EEG classification using deep learning models like Transformers, convolutional neural networks (CNNs), and graph neural networks (GNNs), often coupled with techniques like data augmentation and federated learning to address data scarcity and heterogeneity. These advancements are crucial for improving the reliability and clinical applicability of EEG-based diagnostics and BCIs, impacting fields such as neurological disorder diagnosis, mental health assessment, and assistive technologies.

Papers

October 28, 2022

Automatic Seizure Prediction using CNN and LSTM
Abhijeet Bhattacharya
LSTM Network CNN Network Deep Learning Algorithm Seizure Detection EEG Data EEG Datasets Seizure Prediction

October 12, 2022

Toward the application of XAI methods in EEG-based systems
Andrea Apicella, Francesco Isgrò, Andrea Pollastro, Roberto Prevete
Application Proficiency Emotion Recognition XAI Method Brain Computer Interface EEG Datasets

October 5, 2022

MAtt: A Manifold Attention Network for EEG Decoding
Yue-Ting Pan, Jing-Lun Chou, Chun-Shu Wei
EEG Datasets Manifold Attention

October 3, 2022

On The Effects Of Data Normalisation For Domain Adaptation On EEG Data
Andrea Apicella, Francesco Isgrò, Andrea Pollastro, Roberto Prevete
Domain Adaptation Mixed Effect Brain Computer Interface EEG Data EEG Datasets Normalization Technique Data Normalisation

September 11, 2022

Examining Uniqueness and Permanence of the WAY EEG GAL dataset toward User Authentication
Aratrika Ray-Dowling
Support Vector Machine EEG Data Identity Verification EEG Datasets Object Permanence

July 4, 2022

Task-oriented Self-supervised Learning for Anomaly Detection in Electroencephalography
Yaojia Zheng, Zhouwu Liu, Rong Mo, Ziyi Chen, Wei-shi Zheng, Ruixuan Wang
Anomaly Detection Self Supervised Brain Electroencephalography EEG Data EEG Signal EEG Datasets

June 29, 2022

Data augmentation for learning predictive models on EEG: a systematic comparison
Cédric Rommel, Joseph Paillard, Thomas Moreau, Alexandre Gramfort
Data Augmentation Predictive Model Brain Electroencephalography EEG Data Systematic Comparison EEG Classification EEG Datasets

February 12, 2022

Towards Best Practice of Interpreting Deep Learning Models for EEG-based Brain Computer Interfaces
Jian Cui, Liqiang Yuan, Zhaoxiang Wang, Ruilin Li, Tianzi Jiang
End to End Brain Computer Interface Best Practice EEG Datasets Interpretation Method Interpretation Quality