Seizure detection based on EEG signal

Project to explore a deep learning solution to a computer vision problem. Human action recognition has become increasingly popular. This project implements a deep RNN to detect seizures.

Computational Artificial Intelligence Projects (Seizure Detection) - Fall-2022

A proof of concept for remote monitoring epilepsy patients using sezect Android app

Heart Rate / Epilepsy Alarm

Offline semi-automated seizure detection using deep learning

A proof of concept for remote monitoring epilepsy patients using sezect Android app

seizure detector with neural networks

Epilepsy Prediction with CNN-BiLSTM | BSc dissertation project

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

Movement-based detection of generalized tonic-clonic seizures using a Galaxy Watch Active 2.

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

A BangleJS watch app that acts as a Bluetooth data source for OpenSeizureDetector

The topic is "Electroencephalography based epileptic seizure detection". Based on the repo: https://github.com/unapale/SeizureBenchmarking_Example

Harmful Brain Activity Detection Classification - Classify seizures and other patterns of harmful brain activity in critically ill patients

Neureka 2020 competition for seizure detection - 4th Place Overall!

This project was done in partial fulfillment of the requirements for the module BME 1473: Acquisition and Processing of Bioelectrical Signals in Fall 2022. In this project, the broad objective is oriented toward detecting epileptic seizures by analyzing EEG signals recorded in-vivo from the patients diagnosed with the disease.

Public facing python code that attempts seizure detection and classification

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