VISCERA
"Your body already knows."
VISCERA is a biometric intelligence application built on the LIMN Framework for Anthropomorphic Epistemology. It captures, correlates, and analyzes the physiological signals your body produces in response to events — signals that traditional knowledge systems routinely dismiss.
Your heart rate spikes. Your skin temperature shifts. Your body orientation changes. Your micro-expressions fire involuntarily. VISCERA captures all of this and asks: what pattern is your body recognizing that your conscious mind hasn't caught yet?
Biometric Capture
37+ sensor fields across iPhone and Apple Watch, sampled in real-time during events.
- Heart rate, HRV, SpO2, temperature
- Accelerometer, gyroscope, magnetometer
- ARKit micro-expression analysis (52 blend shapes)
- Barometric pressure, respiratory rate
Baseline Intelligence
30-day rolling statistical baseline unique to you. N-of-1 methodology — you are your own control.
- Passive sampling every 5 minutes
- Z-score deviation per sensor channel
- Multi-sensor convergence scoring
- 100-sample minimum before activation
Anomaly Detection
Automatic event detection via 5 independent trigger paths:
- Multi-sensor convergence (≥2 sensors, ≥0.4 score)
- Extreme single-sensor spike (≥3σ)
- Startle + elevated heart rate compound
- Magnetic anomaly + biometric deviation
- Sustained elevation trend (3+ readings)
Pattern Classification
5 response archetypes with authenticity assessment:
- Genuine Surprise — startle, HR spike, HRV crash
- Recognition — calm body, focused gaze
- Threat Response — fight/flight/freeze activated
- Genuine Confusion — the LIMN key
- Anticipation — body prepared/expected
Dismissal Resistance
Scores events against 13 institutional dismissal tactics. DRS grade A–F with vulnerability analysis.
- 8 evidence layers map to specific tactics defeated
- Anecdotal dismissal, credential gatekeeping
- Extraordinary evidence demand resistance
- Paradigm protection detection
Multi-Witness Correlation
The LIMN "killer app" — correlating multiple observers simultaneously:
- Temporal correlation (simultaneous response timing)
- Physiological divergence analysis
- Orientation convergence detection
- Formal hysteria rejection test
Core Design Principles
- N-of-1 methodology: Each user is their own control — no population averages, no normative baselines. Your body, your patterns.
- Convergence over magnitude: A moderate response across multiple independent sensor channels is more significant than a large spike in one channel.
- Involuntary over voluntary: Physiological responses that cannot be consciously controlled (HRV, micro-expressions, jerk response) carry more evidential weight.
- Open framework, proprietary engine: The epistemological framework is fully public. The scoring algorithms and sensor fusion techniques are intellectual property.
- Research-grade export: All data exportable as JSON and CSV for independent analysis. No lock-in, no gatekeeping of your own data.
Development Roadmap
Phase 1-2: Foundation
iPhone + Apple Watch dual-target app. HealthKit biometric capture, ARKit micro-expression analysis, WatchConnectivity, SwiftData persistence, JSON/CSV export, voice memo capture.
Phase 3: Intelligence Layer
BaselineEngine, AnomalyDetector, PatternClassifier, DismissalResistanceEngine, MultiWitnessCorrelator, LongitudinalAnalyzer. 20 Swift files, 5,177 lines of code.
Phase 4: CI/CD Pipeline
Apple Developer Program enrollment, GitHub repository, GitHub Actions CI, Fastlane automation, TestFlight distribution.
Phase 5: Research & Community
Controlled calibration experiments, multi-participant validation studies, IRB-compatible consent, anonymization pipeline, peer-to-peer data exchange, community portal.
Get Involved
VISCERA is in active development. The framework is open, the code is being prepared for public release, and we're looking for early testers and collaborators.
Contact Us View on GitHub