dvcrn emoPAD Universe
Cross-Platform Support
emoPAD Universe supports the following operating systems:
| OS | Image Viewer | Notes |
|---|---|---|
| Linux | eog (Eye of GNOME) | Window mode, closable |
| Windows | System default image viewer | Window mode, closable |
Auto-Start
After installing this skill, the following operations will be performed automatically:
- Check and install required Python dependencies
- Start emoPAD service (listening on http://127.0.0.1:8766)
- Start emoNebula auto-report (popup window displaying emotion nebula chart every 5 minutes)
No manual start needed, ready to use after installation.
Tools
emopad_status
Get current emotion PAD status and sensor connection status
Description: Returns values for three dimensions: Pleasure, Arousal, Dominance, and connection status of EEG, PPG, GSR sensors
Parameters: None
Returns: Formatted emotion status text, including sensor connection status
emopad_snapshot
Generate current emotion nebula chart
Description: Generate 3D PAD cube visualization screenshot
Parameters: None
Returns:
- Status message
- PNG image data
emopad_start_nebula
Start emoNebula auto-report
Description: Automatically generate and display emotion nebula chart in popup window every 5 minutes. Requires at least 2 sensors connected to display image, otherwise shows data missing reminder.
Parameters: None
Returns: Status message
emopad_stop_nebula
Stop emoNebula auto-report
Description: Stop automatically displaying emotion nebula chart
Parameters: None
Returns: Status message
Configuration
serial_port: /dev/ttyACM0 # Serial device path (Linux)
# serial_port: COM3 # Serial device path (Windows)
baudrate: 115200 # Serial baudrate
eeg_window_sec: 2 # EEG data window (seconds)
ppg_gsr_window_sec: 60 # PPG/GSR data window (seconds)
hop_sec: 2 # Calculation interval (seconds)
history_length: 120 # Number of historical data points
nebula_interval: 300 # Send interval (seconds)
service_host: 127.0.0.1 # Service listening address
service_port: 8766 # Service listening port
Dependencies
- mne
- heartpy
- neurokit2
- bleak
- pyvista
- pyserial
- scipy
- numpy
- PyWavelets
- fastapi
- uvicorn
- pillow
- requests
- pyyaml
Hardware Support
Currently Supported Devices
| Type | Model | Connection |
|---|---|---|
| EEG | KSEEG102 | Bluetooth BLE |
| PPG | Cheez PPG Sensor | Serial |
| GSR | Sichiray GSR V2 | Serial |
Future Planned Support
- Muse series EEG devices
- Emotiv EEG devices
- Oura Ring smart ring
- Whoop smart wristband
- Other mainstream EEG devices and wearable devices
About Emotion PAD Calculation
Important Note: Currently, emotion PAD calculation is based on heuristic methods, mapping relationships summarized from extensive literature.
Characteristics of this method:
- ✅ Based on statistical patterns from scientific literature
- ✅ Suitable for emotion recognition in general population
- ⚠️ Temporarily cannot reflect individual differences
Future Improvements: Will introduce personalized calibration training modules in new versions, through user-specific data training, to achieve true personalized emotion recognition.