eeg-classification

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

Wearable (BLE) Brain-Computer Interface, ADS1299 and STM32 with SDK for mobile application

[Old version] PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces - https://arxiv.org/pdf/1611.08024.pdf

i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension (channel attention) and *temporal dimension*. iii. Common spatial pattern (CSP), an efficient feature enhancement method, realized with Python.

CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification

[TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"

EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow

code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"

A ViT based transformer applied on multi-channel time-series EEG data for motor imagery classification

This project is for classification of emotions using EEG signals recorded in the DEAP dataset to achieve high accuracy score using machine learning algorithms such as Support vector machine and K - Nearest Neighbor.

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

EntroPy: complexity of time-series in Python (DEPRECATED)

[TAFFC-2022] PyTorch implementation of TSception v2

[TNNLS-2023] This is the PyTorch implementation of LGGNet.

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

Multi-Scale Convolutional Transformer Network for Motor Imagery Brain-Computer Interface

End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)

Empirical wavelet transform (EWT) in Python