--- layout: null title: MW75 EEG Streamer - Real-time EEG Data Streaming description: Python package for streaming real-time EEG data from MW75 Neuro headphones. Supports WebSocket, CSV, and LSL outputs for neuroscience research and BCI applications. keywords: EEG, MW75, Neuro headphones, brain-computer interface, BCI, neuroscience, real-time streaming, Python, LSL, WebSocket, RFCOMM, Bluetooth, brainwave, electroencephalography image: /assets/mw75-preview.png --- {% seo %}

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"
Installation demo

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

Browser Visualization

Browser visualization demo