EEG Online
AI Processing
GNN Processing
Advanced Quantum-Inspired BCI Classification System
Real-time Motor Imagery Decoding with Graph Neural Networks
Accuracy: 98.95%
Latency: <12ms
Channels: 22
Sampling: 250Hz
Feature Dims: 64
Live EEG Signal Stream
[12:34:56] Signal quality: EXCELLENT | Impedance: <5kΩ | SNR: 23.4dB
Signal Processing Pipeline
Spectral Power Analysis
Alpha: 12.3μV² | Beta: 8.7μV² | Gamma: 4.2μV² | Mu: 15.1μV²
System Controls
Classification confidence threshold: 85% | Auto-calibration: ON
Graph Neural Feature Extraction
Brain Activity Mapping
Motor cortex activation detected | Lateralization index: +0.73
Motor Imagery Classification
Left Hand
25.0%
Right Hand
25.0%
Foot
25.0%
Tongue
25.0%
85%
Classification Confidence
Advanced Performance Metrics
98.95%
Accuracy
11ms
Latency
2,847
Trials
2h 47m
Uptime
94.2%
Model Confidence
28.4dB
SNR
Graph neural network efficiency: 97.3% | Network depth: 4 layers