Master MVA - Time Series Project
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Updated
May 16, 2021 - Jupyter Notebook
Master MVA - Time Series Project
This application is primarily used to identify cognitive disabilities in people of any age. It does this by taking a screening test and estimating a user's likelihood of having a disability such as dyslexia or dyscalculia. It also offers various ways to monitor a patient's progress and create a graph as a result.
Deep Learning & Labs Course, NYCU, 2023
CNN for ERP classification of the AMUSE dataset.
Biomedical Robotics 2022 Practical Activity based on EEG Data
Integrated EEG Analysis Pipeline
EEG Introduction and mind letter recognition system made by 3 students.
Machine Learning based Brain Computer Interface (BCI) by analyzing EEG Data using PyTorch
Improvement upon the IEEE Sensors Journal research of decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for standing and sitting.
Project for Machine Learning and Artificial Intelligence Exam
Detect stress use EEG signal and Deep learning
Statistical comparison study of valence-arousal classifiers from EEG signals on DEAP and MANHOB datasets
This repo contains the code for my Bachelor-Thesis: Feature engineering for motor imagery classification.
In this repository we used a variant of the EEGNet in order to classify patients with epilepsia
NYU CS-GY 9223 E Neuroinformatics (Spring 2024) - Final Project
Robust electrophysiology tools with GPU acceleration
🌀 A simple program to connect to the MUSE headband and save the EEG data. This can be used to configure experiments or to develop BCI applications.
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