Multi-Modal Closed-Loop BCI Platform
Real-time system integrating EEG, ECG, and EMG for sensorimotor decision-making research. Ultra-low latency architecture validated through rigorous SIL/HIL methodologies.
The closed-loop architecture: Subject → Biosignal Recording (Brain, Heart, Muscle) → Real-Time Processing → Feedback to Subject
Project Overview
This platform represents a comprehensive solution for real-time, closed-loop brain-computer interface research. Developed following control engineering principles, it combines multiple biosignal modalities with ultra-low-latency machine learning pipelines to enable precise investigation of sensorimotor decision-making processes.
Key Achievement
Successfully achieved end-to-end latency of <100ms for the complete processing pipeline: from biosignal acquisition through ML inference to real-time stimulus adaptation. This performance enables investigation of rapid neural processes and their interaction with sensorimotor behavior.
🧠 Multi-Modal Integration
Synchronized recording and processing of EEG, ECG, and EMG signals with precise timestamp alignment for investigating brain-heart-muscle interactions.
⚡ Real-Time ML
Optimized machine learning models with sub-50ms inference times enable online neural decoding and adaptive experimental protocols.
🔄 Closed-Loop Control
Dynamic stimulus modification based on real-time neural state, creating truly interactive brain-computer interface experiments.
System Validation Methodology
Following control engineering best practices, the platform underwent rigorous validation using both Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) testing before human experiments.
✅ SIL Validation
Verified algorithm correctness, timing accuracy, and edge case handling using simulated biosignals with known ground truth.
✅ HIL Validation
Tested real hardware components with synthetic signals to ensure the physical recording chain meets latency and quality requirements.
✅ Integration Testing
End-to-end system validation under maximum data throughput and stress conditions before human subject experiments.
Timing Analysis & Performance
For real-time closed-loop BCI systems, timing is critical. We conducted comprehensive latency profiling at every stage of the processing pipeline to ensure sub-100ms end-to-end performance.
Performance Metrics
| Component | Latency | Notes |
|---|---|---|
| Signal Acquisition | ~2.39 ms | Hardware + USB transmission |
| Real-Time Processing | ~30 ms | Feature extraction + ML inference |
| LSL Streaming | ~55 ms | Network transmission delay |
| Stimulus Generation | <10 ms | Audio/visual presentation |
| Total End-to-End | <100 ms | Complete closed-loop cycle |
Research Applications
This platform has enabled multiple research projects investigating the neural mechanisms of decision-making, agency, and learning.
🧭 Decoding Human Agency
Real-time EEG investigation of the "point of no return" in decision-making—the moment when actions can no longer be cancelled and agency is formed.
❤️ Heart-Brain Interaction
ECG-EEG real-time investigation of how cardiac phase affects learning and neural processing during decision-making tasks.
🎵 Prosody-on-Demand
Audio-neural interface using real-time EEG feedback to optimize speech prosody for memory enhancement in clinical populations.
Technical Capabilities
📡 Multi-Modal Sensors
- EEG: Up to 64 channels, 1000 Hz sampling
- ECG: Synchronized cardiac monitoring
- EMG: Multi-muscle array recording
- Lab Streaming Layer (LSL) integration
⚙️ Signal Processing
- Real-time filtering and artifact removal
- Multi-modal signal synchronization
- Cardiac phase detection (R-peak)
- Feature extraction pipelines
🧮 ML Pipeline
- Sub-50ms inference times
- Online learning capabilities
- Multiple ML framework support
- Performance monitoring
🎯 Closed-Loop Control
- Adaptive stimulus generation
- Timing-critical event handling
- Multi-threaded architecture
- <5ms timing jitter
Publications & Documentation
Research findings and technical documentation from projects using this platform.
📝 In Preparation
Detailed documentation of the system architecture, validation methodology, and experimental results from multiple research studies are currently in preparation.
🔗 Related Publications
This platform served as the technical foundation for multiple research projects. See the individual project pages for specific publications.
System architecture white paper and technical specifications coming soon
Interested in Collaboration?
This platform is available for collaborative research. If you're interested in multi-modal BCI research or need a real-time closed-loop system for your experiments, let's discuss how we can work together.