BCI-CPP-FRAMEWORK - Brain-Computer Interface Research Platform

🧠 Advanced Brain-Computer Interface Research Platform

BCI-CPP-Framework is a comprehensive, enterprise-grade research platform for Brain-Computer Interface (BCI) development. It combines real-time 3D neural visualization, advanced signal processing algorithms (Kalman Filter, CSP, t-test), and publication-ready graph generation in a single integrated environment.

"Real-time neural decoding with 3D visualization - From raw EEG to research publication"

⚠️ DISCLAIMER

This software is intended for research, educational, and development purposes only. It simulates neural signals and is not a medical device. The developers are not responsible for any misuse or damage caused by this program. Always ensure proper ethical guidelines and institutional approvals when conducting research involving human subjects.

🚀 Key Features

🧠 Real-time 3D Neural Visualization

3D Brain Mesh: 128-node Fibonacci lattice topology with synaptic connections
Dynamic Neural Activity: Real-time pulsing nodes with color-coded activity
Interactive Camera: 360-degree orbit control with mouse drag
Synaptic Electricity Lines: Visual connections between neural nodes
Mode-based Coloring: Speech (Blue), Motor (Gold), Visual (Green)

🔬 Advanced Signal Processing

Kalman Filter: Real-time motor decoding with 9D state space (position, velocity, acceleration)
Common Spatial Pattern (CSP): Feature extraction for EEG signal classification
Realistic EEG Generation: Multi-band simulation (Alpha, Beta, Gamma, Theta, Delta)
fMRI BOLD Simulation: Hemodynamic response function modeling
Power Spectrum Analysis: Real-time frequency domain visualization

📊 Research-Grade Analytics

10-Fold Cross-Validation: Robust model validation with mean accuracy & standard deviation
Statistical t-test: Significance testing with p-values and Cohen's d effect size
Ablation Studies: Component importance analysis
Confusion Matrix: 3-class classification performance
ROC Curve: Model performance with AUC score
Feature Importance Heatmap: CSP feature ranking
Spectrogram: Time-frequency analysis
EEG Topomap: 2D scalp potential distribution

🔒 Clinical Safety & Monitoring

IEC 60601-1 Compliance: Tissue temperature monitoring
Electrode Impedance Tracking: Real-time impedance monitoring
Seizure Detection: Emergency alert system with NDN routing
Hardware Health Monitoring: NPU load, battery, RSSI tracking

🌐 Quantum-Secured Networking

NDN (Named Data Networking): Quantum-secured packet routing (Kyber-1024)
PIT Table Management: Pending Interest Table monitoring
Content Store Cache: Cache hit ratio and bandwidth tracking

📈 Data Logging & Visualization

CSV Data Export: Real-time data logging with timestamps
10 Publication-Ready Figures: Automated graph generation
Performance Trends: Temporal analysis of all metrics
Correlation Heatmap: Feature correlation analysis

🎯 Research Applications

Motor Decoding: Real-time limb movement prediction
Speech Restoration: Thought-to-text decoding
Visual Cortex Mapping: Phosphene grid reconstruction
Seizure Prediction: Anomaly detection in neural signals
Neuroplasticity Tracking: Adaptive learning rate monitoring

📦 Installation Guide

System Requirements

Windows 10/11, Linux, or macOS
C++17 Compiler (GCC/MinGW)
Python 3.8 or higher
Raylib Library

Quick Installation

# Clone the repository
git clone https://github.com/alihusnain404/bci-cpp-framework
cd bci-cpp-framework

# Ensure Raylib is in the correct directory
# The repository includes raylib/ folder with include/ and lib/

# Compile the C++ program (Windows)
g++ -std=c++17 main.cpp -Iraylib/include -Lraylib/lib -lraylib -lopengl32 -lgdi32 -lwinmm -o App.exe

# Compile the C++ program (Linux/macOS)
g++ -std=c++17 main.cpp -Iraylib/include -Lraylib/lib -lraylib -lGL -lm -lpthread -ldl -lrt -o App

# Install Python dependencies
pip install pandas numpy matplotlib seaborn scipy

🛠 Usage

Running the C++ Application

# Windows
App.exe

# Linux/macOS
./App

Controls

Key	Function
`1`	Speech Decoding Mode
`2`	Motor Control Mode
`3`	Visual Cortex Mode
`4`	Reset Mode
`S`	Seizure Alert Simulation
`C`	Calibrate CSP
`L`	Log Data to CSV
`A`	Toggle Ablation Study View
`V`	Toggle Advanced Visualizations
`K`	System Reset
`R`	Reset Camera
Mouse Drag	360° Orbit Camera

Generating Research Graphs

# After running the C++ program and generating CSV data
python graphs.py

📋 Output Sections

Left Panel: Neural Signal Acquisition

EEG Raw Signal: Real-time voltage waveform with seizure detection
fMRI BOLD Response: Hemodynamic response function
Power Spectral Density: 1-100Hz frequency spectrum
Kalman Filter Position: 3D decoded position [x, y, z]
Performance Metrics: Accuracy, NPU load, SNR, temperature

Right Panel: Controls & Visualizations

NDN Packets: Quantum-secured routing table
CSP Calibration: Feature extraction training
Safety Monitor: IEC 60601-1 compliance
Controls: All keyboard shortcuts
Research Parameters: Neuroplasticity, learning rate

Advanced Visualizations (Press V)

Confusion Matrix: 3-class classification results
ROC Curve: Model performance with AUC
Feature Importance: CSP feature ranking
Spectrogram: Time-frequency representation
EEG Topomap: 2D scalp potential distribution

📊 Generated Figures

Figure	Description
Figure 1	EEG Waveform with Seizure Detection
Figure 2	Confusion Matrix - 3-Class Classification
Figure 3	ROC Curve with AUC
Figure 4	CSP Feature Importance Heatmap
Figure 5	Spectrogram - Time-Frequency Analysis
Figure 6	EEG Topomap - Scalp Potential Distribution
Figure 7	Performance Trends Over Time
Figure 8	Correlation Matrix of Neural Metrics
Figure 9	Ablation Study - Component Importance
Table 1	Performance Summary Statistics

🎯 Example Output

🧠 NEURAL SIGNAL ACQUISITION
Device: Neuralink N1 vFW-2.5.3-2026.03.15 | Implant: ACTIVE

EEG RAW SIGNAL (uV):    [━━━━━━━━━━━━━━━━] 42.3 µV
fMRI BOLD (HRF):        [━━━━━━━━━━━━━━━━] 0.23
Kalman Pos: [0.42, 0.18, 0.05] | Accuracy: 96.7%
NPU Load: 58.3% | SNR: 44.1 dB
Tissue Temp: 37.2°C ✅ | Plasticity: 1.0004 | Battery: 84.2%

MODE: SPEECH DECODING
Output: "I WOULD LIKE SOME WATER PLEASE"
Confidence: 94.2% | Latency: 0.42 ms

10-FOLD CROSS-VALIDATION:
Mean Acc: 88.5% | Std: 2.1%

t-test: t=4.82 | p=0.0003 ✅ | d=1.24

🔧 Advanced Configuration

Customizing Parameters

// Kalman Filter Parameters (main.cpp)
float dt = 0.016f;  // Time step (16ms for 60Hz)
// State transition matrix automatically configured

// CSP Parameters
CommonSpatialPattern csp(4);  // 4 spatial filters

// EEG Generation Parameters
alphaAmp = 15.0f;  // 8-13 Hz
betaAmp = 8.0f;    // 13-30 Hz
gammaAmp = 5.0f;   // 30-80 Hz
thetaAmp = 12.0f;  // 4-8 Hz
deltaAmp = 20.0f;  // 0.5-4 Hz

CSV Data Format

Timestamp,Mode,EEG_uV,fMRI_BOLD,NPU_Load,Tissue_Temp,Plasticity,Seizure,Battery,RSSI,Kalman_Acc,CSP_Acc
2024-01-15 10:30:45.123,2,12.34,0.023,42.5,37.1,1.000,0,87.0,-42.0,94.2,88.5

📁 Repository Structure

bci-cpp-framework/
├── main.cpp                    # Core C++ application
├── graphs.py                   # Python graph generator
├── App.exe                     # Pre-compiled executable (Windows)
├── raylib/                     # Raylib library
│   ├── include/               # Header files
│   └── lib/                   # Library files
├── graph_figures/             # Generated figures
│   ├── Figure1_EEG_Waveform_Enhanced.png
│   ├── Figure2_Confusion_Matrix.png
│   ├── Figure3_ROC_Curve.png
│   ├── Figure4_Feature_Importance.png
│   ├── Figure5_Spectrogram.png
│   ├── Figure6_EEG_Topomap.png
│   ├── Figure7_Performance_Trends.png
│   ├── Figure8_Correlation_Heatmap.png
│   ├── Figure9_Ablation_Study.png
│   └── Table1_Performance_Summary.png
├── research_data_*.csv        # Generated data logs
├── video/                     # Project demonstration video
│   └── demo.mp4
├── Icon/                      # Banner and icons
│   └── Banner.png
└── README.md                  # This file

📊 Detection Capabilities

Algorithms Implemented

Kalman Filter: 9D state estimation (position, velocity, acceleration)
Common Spatial Pattern (CSP): Multi-class feature extraction
Statistical Analysis: t-test, p-values, effect size
Cross-Validation: 10-fold robust validation
Ablation Studies: Component importance analysis

Visualization Capabilities

3D Neural Mesh: 128-node Fibonacci lattice
Synaptic Connections: Distance-based interconnection
Real-time Waveforms: EEG, fMRI, power spectrum
Publication Figures: 10 high-quality research plots
Interactive Camera: 360-degree orbit control

🤝 Contributing

We welcome contributions! Please feel free to submit pull requests, report bugs, or suggest new features.

Areas for Contribution

New Algorithms: Add more neural decoding algorithms
Visualization Enhancements: Improve 3D rendering
Performance Optimization: Optimize signal processing
Documentation: Improve user guides and API docs
Testing: Add unit tests and validation

🐛 Troubleshooting

Common Issues

Compilation Error:

# Ensure Raylib is properly installed
# Check include and lib paths in the compile command
# Use the exact command from the Installation section

Raylib Not Found:

# Download Raylib from https://www.raylib.com/
# Extract to the raylib/ folder in the project root
# Structure should be: raylib/include/ and raylib/lib/

Python Dependencies:

# Install required packages
pip install pandas numpy matplotlib seaborn scipy

CSV Not Generating:

# Press 'L' key in the application to start logging
# CSV will be saved as research_data_[timestamp].csv

📄 License

This project is licensed under the PROPRIETARY LICENSE - STRICT PROTECTION - see the LICENSE file for details.

🙏 Acknowledgements

Raylib - For 3D visualization and graphics
Raylib Team - For the excellent game development library
Matplotlib - For publication-quality plotting
SciPy - For scientific computing
IEEE EMBS - For the research platform inspiration

📞 Support

If you encounter any issues or have questions:

Check the Issues page
Create a new issue with detailed description
Provide error messages and system information
Watch the demonstration video in the video/ folder

MADE WITH ❤️ BY AUTHOR ALI HUSNAIN

Advancing Brain-Computer Interface Research - From Signal to Insight

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
Icon		Icon
graph figures		graph figures
raylib		raylib
video		video
App.exe		App.exe
LICENSE		LICENSE
README.md		README.md
graph.py		graph.py
main.cpp		main.cpp

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