YASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.

Not supported. Measure 8 EEG channels with Shield PiEEG and RaspberryPi in C library

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

EEGraph: Convert EEGs to graphs with frequency and time-frequency domain connectivity measures.

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

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.

Code to accompany our International Joint Conference on Neural Networks (IJCNN) paper entitled - Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification

Signal Processing Toolkit, including ML models with visualization

Emotion Recognition, EEG Mapping, Azimuthal Projection Technique, CNN

In this project, we address the problem of eye-blink detection and analysis of left and right human eye blinks using EEG signals with help of Neurosky Mindwave Mobile. The purpose of this project is to monitor and understanding of eye blinks for proper communication with a person

Implementation of Domain Specific Denoising Diffusion Probabilistic Models for Brain Dynamics/EEG Signals

Code to accompany our International Conference on Pattern Recognition (ICPR) paper entitled - Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI.

Function to calculate consistency of phase at a given frequency across measurements

Machine learning for Anonymous detection of an alcoholic by EEG signals

JMIR AI'23: EEG dataset processing and EEG Self-supervised Learning

PhyAAt: Physiology of Auditory Attention - Processing Library

Real-time EEG BCI signal processing by Python

Brain Computer Interface (BCI) with Neurosky Mindwave Mobile 2 that enables anyone to use computer, mobilephone etc. with his/her thoughts.

A convolutional neural network developed in python using the Keras machine learning framework used to categorize brain signal based on what a user was looking at when the EEG data was collected.