Real-time EEG Streaming

Stream EEG data from MW75 Neuro headphones with Python

View on GitHub Get Started API Documentation

Key Features

⚡

High-Speed Streaming

Real-time EEG data streaming with minimal latency for responsive brain-computer interface applications.

🔄

Multiple Output Formats

Stream to WebSocket, CSV files, Lab Streaming Layer (LSL), or stdout with simultaneous multi-format support.

🧠

MW75 Neuro Integration

Seamless integration with MW75 Neuro headphones using BLE activation and RFCOMM data streaming on macOS.

📊

Data Validation

Built-in packet validation, checksum verification, and automatic conversion to microvolts for accurate data.

🔧

Modular Architecture

Clean, modular codebase with type safety, comprehensive logging, and easy extensibility.

🔬

Research Ready

Perfect for neuroscience research, BCI development, and real-time brain signal analysis applications.

Quick Installation

macOS Only: Currently supported on macOS only. Linux and Windows support coming soon.

# Option 1: Install from PyPI (recommended)
uv pip install mw75-streamer

# For additional features (WebSocket, LSL support):
uv pip install "mw75-streamer[all]"

# Or directly (slower):
pip install "mw75-streamer[all]"

# Option 2: Install from source
# Clone this repository
git clone https://github.com/arctop/mw75-streamer.git
cd mw75_streamer

# Option 2a: Using uv (recommended)
# 1. Install uv if you need (see installation guide:
#    https://docs.astral.sh/uv/getting-started/installation)
brew install uv

# 2. install python, the dependencies and this package
uv venv && uv pip install -e ".[all]"

# Option 2b: Using pip
python -m venv .venv
source .venv/bin/activate
pip install -e ".[all]"

# For LSL support on macOS
brew install labstreaminglayer/tap/lsl
export DYLD_LIBRARY_PATH="/opt/homebrew/lib:$DYLD_LIBRARY_PATH"

Basic Usage

# Basic streaming
uv run -m mw75_streamer --browser

uv run -m mw75_streamer --csv eeg.csv

uv run -m mw75_streamer --ws ws://localhost:8080

uv run -m mw75_streamer --lsl MW75_EEG

# Combined outputs
uv run -m mw75_streamer --csv eeg.csv --ws ws://localhost:8080