🧠 Enhance neurorehabilitation with recoveriX, a BCI technology that helps patients regain motor functions through innovative therapy and real-time feedback.

🌐 Normalize and parse domain names from messy input, cleaning errors and preserving structure for easier use and analysis.

AI wearables. Put it on, speak, transcribe, automatically

Converting real-time EEG into sounds, music and visual effects

Mother of All BCI Benchmarks

Project for 2025 NeuroSparkEU Hackathon in Elche

A framework for simplying BCI workflow in clinical applications

BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors

This interface module is designed for customers who have purchased our equipment. It enables seamless data acquisition from the devices and provides control over operational parameters and device status monitoring.

classifying movements using EEG signals. This is my final project for my BSS course.

Python library for real-time gait modulation prediction using multimodal neural and movement data (LFP, EEG, IMU, EMG) — designed for closed-loop DBS systems in Parkinson’s disease.

NYCU CSIC30014 Lab2: EEG Classification with EEGNet (87%+ accuracy, optimized hyperparameters, BCI Competition III dataset)

Python API for Mentalab biosignal aquisition devices

🧠 What is Neurological Spark? Neurological Spark is the innate rapid thought processing capability common in neurodivergent individuals - the ability to solve complex problems instantly through accelerated neural pathways that operate 200-300ms before conscious awareness.

mne-denoise provides narrow-band artefact removal tailored to MNE-Python workflows. It wraps harmonic regression techniques to suppress power-line noise and other oscillatory contaminants while preserving signal rank and interpretability.

Brain-Computer Interface Controlled Electronic Role-playing Game development efforts by the 100% volunteer RPG Research community at https://www.rpgresearch.com.

Python Brain-Computer Interface Software

This Cookiecutter template sets up a basic Python project structure, aiming to save you time and to promote best practices. It's ideal for starting new Book projects quickly with a standard setup including a project structure, basic documentation, and necessary configuration files.

This repository hosts a Jupyter notebook for loading, preprocessing, and analyzing the BigP3BCI dataset, focusing on P300 oddball event‑related potentials (ERPs) in an EEG brain–computer interface (BCI) paradigm.