A Python-based Brain-Computer Interface (BCI) project that uses the MindWave EEG headset to create interactive applications controlled by brainwave signals. This project demonstrates real-time processing of attention, meditation, and various EEG frequency bands to control games and visualize brain activity.
- Attention-Based Movement: Control horizontal movement using attention levels
- Meditation-Based Jumping: Jump by achieving high meditation states
- Real-time EEG Processing: Live brainwave signal processing for responsive gameplay
- Visual Feedback: Character expressions change based on brain state
- Live EEG Monitoring: Real-time display of brainwave data
- Multiple Frequency Bands: Delta, Theta, Alpha, Beta, and Gamma wave visualization
- Attention & Meditation Tracking: Dedicated meters for mental states
- Blink Detection: Left/right eye blink detection and classification
Control the character using your attention and meditation levels
Real-time visualization of EEG signals and brain states
See the brain-computer interface in action
- Hardware: MindWave EEG headset (NeuroSky)
- Python: 3.7+
- Operating System: Windows, macOS, or Linux
- EEG mindwave headset: NeuroSky MindWave Mobile EEG Headset
Product Link: [MindWave Mobile](https://nl.aliexpress.com/item/1005006620561995.html)
- Bluetooth to Visual COM: Bluetooth USB Dongle Adapter Serial Port Transparent Transmission HM-15 Beacon Base Station EDR 4.0+ BLE4.0 Dual Mode Master-Slave in One
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
pip install pygame pyserial-
Connect MindWave Headset:
- Pair your MindWave device via Bluetooth
- Note the COM port (Windows) or device path (Linux/macOS)
-
Configure Serial Port:
- Update the
SERIAL_PORTvariable in both files to match your device - Default is set to
"COM9"- change as needed
- Update the
python game_mindwave.pyControls:
- Attention: Controls forward and backward movement (0-100 scale)
- Meditation: Enables jumping when levels are high enough
- Goal: Collect coins while navigating platforms using only your mind!
python mindwave_ui.pyFeatures:
- Real-time EEG frequency band display
- Attention and meditation level meters
- Raw signal visualization
- Blink detection indicators
- Signal quality monitoring
Both applications require setting the correct serial port:
# In game_mindwave.py and mindwave_ui.py
SERIAL_PORT = "COM9" # Windows
# SERIAL_PORT = "/dev/ttyUSB0" # Linux
# SERIAL_PORT = "/dev/cu.MindWaveMobile-SerialPo" # macOSAdjust brain signal sensitivity in game_mindwave.py:
# Attention sensitivity for movement
ATTENTION_THRESHOLD = 50
# Meditation threshold for jumping
MEDITATION_THRESHOLD = 60- Sampling Rate: 512 Hz (MindWave native)
- Frequency Bands Monitored:
- Delta (0.5-4 Hz): Deep sleep, unconscious processes
- Theta (4-8 Hz): Drowsiness, meditation
- Alpha (8-13 Hz): Relaxed awareness
- Beta (13-30 Hz): Active concentration
- Gamma (30-100 Hz): High-level cognitive processing
- Protocol: Serial communication via Bluetooth/USB
- Baud Rate: 9600
- Packet Format: MindWave ThinkGear protocol
- Real-time Processing: Sub-100ms latency for responsive control
- Physics Engine: Custom pygame-based physics
- Collision Detection: Rectangle-based collision system
- Scoring System: Coin collection with brain-state feedback
- Visual Feedback: Character expressions reflect mental state
- Neuroscience Learning: Understand brainwave patterns
- BCI Research: Experiment with brain-computer interfaces
- Biofeedback Training: Learn to control attention and meditation
- ADHD Training: Attention regulation exercises
- Meditation Practice: Meditation state visualization
- Stress Management: Real-time stress level monitoring
- Novel Gaming Experiences: Mind-controlled gameplay
- Accessibility: Alternative input method for disabled users
- Competitive Training: Mental state optimization for esports
This project can serve as a foundation for:
- Cognitive Load Assessment: Measuring mental workload in real-time
- Attention Training Systems: ADHD and focus improvement applications
- Brain-Computer Interface Research: Academic BCI studies
- Neurofeedback Systems: Clinical biofeedback applications
Device Not Connecting:
- Verify Bluetooth pairing
- Check COM port assignment
- Ensure MindWave is charged and powered on
Poor Signal Quality:
- Clean electrode contacts
- Ensure proper headset positioning
- Check for electromagnetic interference
Game Not Responding:
- Verify attention/meditation thresholds
- Check serial port configuration
- Ensure headset is properly calibrated
- Machine Learning Integration: Personalized brain pattern recognition
- Multi-user Support: Collaborative brain-controlled experiences
- Advanced Games: More complex BCI-controlled game mechanics
- Data Analytics: Historical brain state analysis and reporting
- Mobile App: Smartphone companion for remote monitoring
- Cloud Integration: Data synchronization and sharing
This project is open source and available under the MIT License.
- NeuroSky: For the MindWave EEG technology
- Pygame Community: For the game development framework
- PySerial Contributors: For serial communication capabilities
We welcome contributions to enhance this project! Please fork the repository, make your changes, and submit a pull request.
Experience the future of human-computer interaction through the power of your mind!