Variational mode decomposition (VMD) in Python

Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic Setting (CHIL 2022)

Empirical wavelet transform (EWT) in Python

Residual and bidirectional LSTM for epileptic seizure detection

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.

ICLR 2023 paper - ManyDG - Dataset processing and mode codes

This repository contains the trained deep learning models for the detection and prediction of Epileptic seizures.

Epilepsy Prediction with CNN-BiLSTM | BSc dissertation project

Code for BHI 2023 Paper on EEG Seizure Detection

Implementation of Neonatal Seizure Detection using EEG signals for deploying on edge devices including Raspberry Pi.

A Python package for behavioral state analysis using EEG. BEST includes tools automated sleep classification of long-term iEEG data recorded using implantable neural stimulation and recording devices, removal of DBS artifacts and feature extraction.

Self-supervised learning with graph neural network backbones for seizure detection in iEEG data.

Electrographic Seizure Detection Program

Epileptic Seizure Prediction with EEG Data and Logistic Regression in Python 🧠 🐍

Seizure Detection in EEG Signals using Short Time Fourier Transform and Discrete Wavelet Transform

This repository holds our academic research to develop the most efficient deep learning algorithm to accurately detect an ongoing seizure from EEG Waves.

Heart Rate / Epilepsy Alarm

My research on the diagnosis of epilepsy based on brain signals as a master's thesis. (Deep Learning - ECoG - EEG)

EEG Epileptic Seizure Detection project that focuses on the detection of epileptic seizures in EEG recordings using machine learning models applied across multiple data domains: temporal, frequency, and time-frequency. It provides tools for data preprocessing, model training, evaluation, and an interactive graphical interface to explore and analyze