How HABS Neuro AI Works
A complete infrastructure for acquiring, processing, and structuring cognitive signals into AI-ready data formats.
Brain Data Acquisition
Multi-modal physiological signal capture from standardized research-grade sensors.
- EEG (electroencephalography)
- Eye Tracking
- ECG (cardiac signals)
- GSR (galvanic skin response)
Cognitive Clustering
Proprietary models that structure neural signatures into meaningful cognitive states.
- Emotion detection (valence, arousal)
- Cognitive load measurement
- Attention & vigilance tracking
- Memory encoding signals
Neuro AI Modeling
Deep learning models trained on controlled experimental data for multiclass cognitive state classification.
- Scientifically validated pipelines
- Cross-validated performance
- No heuristics or rules
- Pure data-driven approach
Standardized Cognitive Metrics
Benchmark-ready outputs formatted for seamless integration into AI systems and LLMs.
- JSON/API-ready format
- Real-time streaming
- Batch processing support
- Cloud & edge deployment
Core Capabilities
Detect Emotional States
Identify valence (positive/negative) and arousal (calm/excited) in real-time.
Measure Cognitive Load
Quantify mental effort and working memory utilization during tasks.
Assess Attention & Vigilance
Track focus levels, engagement, and sustained attention over time.
Identify Stable Neural Signatures
Extract reproducible patterns for classification and prediction.
