mw75-streamer 1.0.0

Stream EEG data from MW75 Neuro headphones using BLE and RFCOMM

MW75 Neuro Streamer

Stream 12-channel EEG data from MW75 Neuro headphones with WebSocket, CSV, and LSL output support.

Features

• Real-time streaming: 500Hz, 12-channel EEG with µV precision
• Multiple outputs: WebSocket JSON, CSV files, Lab Streaming Layer (LSL)
• Built-in testing: WebSocket servers with browser visualization
• Robust protocol: Checksum validation and error detection

Installation

# Clone this repository
git clone https://github.com/arctop/mw75-streamer.git
cd mw75_streamer

Option 1: Using uv (recommended)

1. Install uv if you need (see installtion guide)

brew install uv

2. install python, the dependencies and this package

uv venv && uv pip install -e ".[all]"

Option 2: Using pip

python -m venv .venv
source .venv/bin/activate
pip install -e ".[all]"

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

Testing

# 1. Start test server
uv run -m mw75_streamer.testing --advanced
# Optional: Press 'b' + Enter in server terminal to open browser visualization

# 2. Start EEG streaming
uv run -m mw75_streamer --ws ws://localhost:8080

How It Works

1. BLE Activation: Discovers MW75 via Bluetooth LE and sends activation commands
2. RFCOMM Streaming: Connects to channel 25 and receives 63-byte packets
3. Data Processing: Converts raw ADC to µV, validates checksums, outputs to CSV/WebSocket/LSL

Data Formats

CSV: Timestamp,EventId,Counter,Ref,DRL,Ch1RawEEG,...,Ch12RawEEG,FeatureStatus

WebSocket JSON: Real-time streaming with timestamp, counter, ref/drl, and 12 channel values in µV

Requirements

• Hardware: MW75 Neuro headphones (paired via Bluetooth)
• OS: macOS (fully supported), Linux (planned - contributions welcome)
• Python: 3.9+

macOS Setup for LSL

# Install LSL library (for LSL support)
brew install labstreaminglayer/tap/lsl
export DYLD_LIBRARY_PATH="/opt/homebrew/lib:$DYLD_LIBRARY_PATH"

# Pair MW75 headphones in System Preferences > Bluetooth

Performance Optimization

For improved real-time performance and reduced packet drops, run with elevated priority:

# Run with high priority (requires sudo for optimal performance)
sudo uv run -m mw75_streamer --csv eeg.csv

# The streamer automatically sets:
# - Process priority (niceness -10)
# - Thread real-time scheduling policy
# - Optimized RFCOMM event loop timing (1ms intervals)

Note: Running without sudo will still work but may have higher packet drop rates under system load.

Troubleshooting

• MW75 not found: Ensure headphones are powered on and paired
• Connection failed: Re-pair device in Bluetooth settings
• Dropped packets: Reduce Bluetooth interference, move away from WiFi routers and other 2.4GHz devices

Alternative: Using Python Directly

If you prefer to use regular Python instead of uv, activate your virtual environment first:

# After installation with pip
source .venv/bin/activate
python -m mw75_streamer --csv eeg.csv --ws ws://localhost:8080

Development

See CONTRIBUTING.md for development setup and contribution guidelines.

License

MIT License - see LICENSE for details.

About

MW75 EEG Streamer was developed by Arctop, a neurotechnology company focused on making brain-computer interfaces accessible and practical.

Acknowledgments

AI Assistance

• Claude Code (by Anthropic) - AI coding assistant used for development support and code optimization.

Open Source Dependencies

This project builds upon excellent open source libraries:

• bleak - Cross-platform Bluetooth Low Energy library for Python
• PyObjC - Python bridge to Objective-C for macOS integration
• websocket-client - WebSocket client library for real-time streaming
• websockets - WebSocket server implementation for testing tools
• pylsl - Python bindings for Lab Streaming Layer
• black - Python code formatter for consistent style
• mypy - Static type checker for Python
• flake8 - Python linting tool for code quality

Hardware & Community

• Master & Dynamic for creating the MW75 Neuro headphones and making EEG accessible
• The Python community for excellent Bluetooth libraries and frameworks

---

For detailed technical information about the MW75 protocol, see the inline documentation in the source code.