USC-InfoLab / NeuroGNNLinks
NeuroGNN is a state-of-the-art framework for precise seizure detection and classification from EEG data. It employs dynamic Graph Neural Networks (GNNs) to capture intricate spatial, temporal, semantic, and taxonomic correlations between EEG electrode locations and brain regions, resulting in improved accuracy. Presented at PAKDD '24.
☆45Updated last year
Alternatives and similar repositories for NeuroGNN
Users that are interested in NeuroGNN are comparing it to the libraries listed below
Sorting:
- ☆172Updated 2 years ago
- [Arxiv] NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG☆63Updated 6 months ago
- GGN model for seizure classification (datasets: TUH EEG seizure TUSZ 1.5.2)☆60Updated last year
- [AAAI 2023] Python implementation of Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analy…☆39Updated last year
- Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic Setting (CHIL 2022)☆112Updated 2 years ago
- An all-in-one EEG feature extraction toobox, including statistical features, Hjorth parameters, entropy, nonlinear features, power spectr…☆43Updated last year
- source codes for EEGWaveNet: Multi-Scale CNN-Based Spatiotemporal Feature Extraction for EEG Seizure Detection (IEEE Transactions on Indu…☆60Updated 2 years ago
- A Pytorch implementation of our paper "Adaptive Spatial-Temporal Aware Graph Learning for EEG-based Emotion Recognition".☆16Updated last year
- ☆93Updated 9 months ago
- Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Grap…☆177Updated 2 years ago
- [TNSRE 2023] Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation☆45Updated last year
- SleepPrintNet: A Multivariate Multimodal Neural Network based on Physiological Time-series for Automatic Sleep Staging☆38Updated last year
- Code for processing EEG data with Riemannian and deep learning-based classifiers. Additionally provides methods for data augmentation inc…☆30Updated 5 years ago
- seizure type classification using TUH dataset☆75Updated last year
- [IEEE JBHI] "MultiChannelSleepNet: A Transformer-Based Model for Automatic Sleep Stage Classification With PSG"☆54Updated 2 years ago
- ☆66Updated 2 years ago
- This is the python implementation of Tensor-CSPNet and Graph-CSPNet.☆72Updated 4 months ago
- JMIR AI'23: EEG dataset processing and EEG Self-supervised Learning☆47Updated 2 years ago
- ☆20Updated 2 years ago
- High-East / Attention-based-spatio-temporal-spectral-feature-learning-for-subject-specific-EEG-classificationOfficial code for "Attention-Based Spatio-Temporal-Spectral Feature Learning for Subject-Specific EEG Classification" paper☆37Updated 3 years ago
- ☆37Updated 9 months ago
- IEEE Transactions on Emerging Topics in Computational Intelligence☆67Updated 4 months ago
- Deep Learning, Wavelet Analysis and Fourier Transforms for identification of abnormal EEG in Epilepsy patients☆61Updated 4 years ago
- Implementation of graph convolutional networks based on PyTorch Geometric to classify EEG signals.☆54Updated 4 years ago
- This repository contains the python scripts developed as a part of the work presented in the paper "STAnet: A Spatiotemporal Attention Ne…☆12Updated 2 years ago
- ☆17Updated 2 years ago
- PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognition☆63Updated last year
- Code for the paper published in Deep Generative Models for Health Workshop at the Neurips 2023.☆54Updated last year
- Emotion classification from Brain EEG signals using a hybrid CNN-Transformer model and various ML algorithms.☆27Updated 2 years ago
- Analysis of Transformer attention in EEG signal classification☆45Updated 11 months ago