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

A P300 online spelling mechanism for Emotiv headsets. It's completely written in Node.js, and the GUI is based on Electron and Vue.

Python library for ESPEC North America chambers with P-300, SCP-220, Watlow F4, F4T controllers.

EEG BCI Real-Time Applications: Contains real-time demonstrations of BCI applications

Timeflux demos

Visually evoked potentials and P300 for the Attys (Windows/Linux)

A basic demonstration how to use Python, MNE, and PyTorch to analyze EEG signal.

감정저금통-뇌파를 이용한 기부유도시스템

A tool for teaching P300 by showing the ongoing averaging process and classification

P300 Classification for EEG-based BCI system with Bayes LDA, SVM, LassoGLM and a Deep CNN methods

Workshop on standardized Brain-Computer Interface Framework

뉴로 마케팅을 활용한 광고 분석 프로그램

Framework for P300 wave detection and noise-based cyberattacks in Brain-Computer Interfaces - Enrique Tomás Martínez Beltrán

El presente repositorio contiene todos los archivos del prototipo del proyecto BCI basado en potenciales P300, para interacción con dispositvos del entorno y creación de entornos inteligentes.

P300 Matrix for brain computer interfaces using html, CSS and JavaScript with mean error 1 millisecond

Implementation of P300 waveform detection algorithm proposed by the winners of BCI Competition III

Extract the independant sources with Composite Approximate Joint Diagonalization (CAJD) for linear/bilinear data models

Welcome to the EEG Signal Analysis repository, focusing on the extraction of P300 signals using synchronous averaging techniques. This project aims to provide insights into the optimal number of repetitions required to reliably capture the P300 response, a crucial component in various applications such as BCIs and cognitive neuroscience research.

For my MSc dissertation, and in my role as a research data analyst, I am undertaking an analysis of electroencephalography data to investigate whether detection of the P300 neural signal can be utilised within an EEG Brain-Computer Interface to discern information from the minds of individuals, without the need for explicit communication.

Graphical interface for loading p300 frames in an ATMega32 by serial port