Where Intelligence Meets Its Operator

EmoPulse

A five-layer ontological architecture that gives AI real-time perception of the human it serves. Not a feature — a new foundational layer. On-device. Zero cloud. Patent-protected.

2 Patents Pending + 1 Underway 5-Layer Architecture 100% Edge AI Dual-Use

THIS SOFTWARE IS PROPRIETARY AND CONFIDENTIAL
2 Patents Pending (2026-502, 2026-508) + 3rd Underway (2026-503)
© 2025–2026 Arvydas Pakalniskis / EmoPulse

Unauthorized copying, cloning, modification, or distribution is strictly prohibited
and may result in legal action. Protected under EU and US intellectual property law.

The perception layer that every AI system is missing

Every AI on Earth — ChatGPT, Claude, Gemini — responds to what you type. None of them know if you're stressed, exhausted, distracted, or about to make a critical error. They operate blind to the most important signal: the human state.

EmoPulse is not a scanner. It is not a sentiment classifier. It is an ontological architecture — a five-layer system that ingests multimodal signals from camera, voice, and text, maps them to a structured human state representation, assesses risk in real time, and constrains AI output accordingly.

"Payments got Stripe. Communications got Twilio. Search got Google. AI cognition got OpenAI. AI perception gets EmoPulse."
1
Signal Ingestion
Multimodal Feature Extraction
Three parallel channels — camera (rPPG, micro-expressions, gaze, FACS), text (tempo, pressure, escalation), voice (pitch, pauses, tension) — each producing an independent feature vector.
✓ Camera + Text engines built
2
Ontological Mapping
500+ Node Emotion Ontology
Raw signals mapped to a hierarchical RDF/OWL knowledge base integrating Plutchik, Parrott, and OCC models. Not "happy" or "sad" — structured semantic states with intensity, stability, trend, and context.
✓ Full ontology built
3
Decision Engine
Dynamic Fusion, Risk & Control Policy
Signals fuse into a 6-dimensional state vector via dynamic weighted fusion — weights computed at runtime. A risk scalar partitions the continuum into four operational modes, each generating a structured control policy.
✓ Full pipeline built · Patent pending (2026-503)
4
Controlled Output
AI Response Within Constraints
Three enforcement points: pre-generation constraints, live per-token mode checks, and post-generation compliance correction. The AI operates within the policy — not from scripts.
✓ Built
5
Feedback Loop
Continuous Cycle & Long-Term Memory
Every output becomes the next input. Coherence monitoring detects semantic degradation. Adaptive frame smooths state jumps. Long-term memory persists across sessions, AES-256 encrypted. <50ms cycle time.
✓ Built

On March 5, 2026 — an AI read a human before responding.
Not from a questionnaire. Not from cookies.
From a live biometric stream — through all 5 layers — in real time.

89%
BEHAVIORAL STABILITY
66%
DRIFT REDUCTION
<50ms
ON-DEVICE LATENCY
F1 .87
DEGRADATION DETECTION
>90%
CONTEXT RETENTION
~250mW
POWER CONSUMPTION
0
CLOUD DEPENDENCY
2+1
PATENTS

The AI adapted its tone, depth, urgency, and pace — all calibrated to the human's real-time state. No rules. No scripts. No guessing.

To prove the architecture works — we built a live scanner

The EmoPulse Dashboard is a real-time demonstration of Layer 1 — signal extraction from a standard camera. It extracts 47 biometric parameters on-device, with zero cloud dependency. This is not the product. This is the proof that the pipeline is real.

Emotion Detection

7 Core Emotions
Happy, Sad, Angry, Fearful, Surprised, Disgusted, Neutral
Confidence Scoring
Real-time certainty levels
Mood Shift Tracking
Emotional transitions over time
Emotion Spectrum
Visual frequency distribution

Biometrics — No Wearables

Heart Rate (BPM)
rPPG from skin color changes
HRV (RMSSD)
Heart rate variability analysis
Breathing Rate (RPM)
Respiratory pattern detection
Blink Detection
Eye Aspect Ratio method

Cognitive Metrics

Stress Level
Multi-signal stress index
Energy Flow
Arousal and activation state
Focus Score
Attention and concentration
Cognitive Load
Mental effort estimation

Authenticity & Gaze

TruthLens™
Genuine vs fake expression detection
Duchenne Smiles
Real smile counter (AU6+AU12)
Micro-Expressions
Rapid facial movements (<500ms)
Gaze Stability
Focus zone mapping
Pupil Dilation
Arousal and interest indicator
Multi-Face Detection
Track multiple subjects

Voice Analysis

Voice Emotion
Audio-based sentiment
Pitch Detection
Frequency analysis
Voice Level
Energy and intensity
Emotional Contagion
Group sync index

Advanced Features

NeuroMesh™
68-point facial landmark tracking
Action Units (FACS)
Scientific expression coding
Emotion Timeline
Historical visualization
Emotional Memory
Session recording
Neural Events Feed
Real-time activity log
SHA-256 Signature
Cryptographic session verification
Part III — Intellectual Property & Technology

NeuroMesh™

Patent Filed

68-point facial landmark system with 5+ action units

PulseSense™

Patent Filed

rPPG heart rate & HRV extraction from skin micro-color changes

TruthLens™

Patent Filed

Authenticity scoring via Duchenne marker analysis

MoodCast™

Patent Filed

Predictive emotion timeline with memory system

Patents
Patent 2026-502
Emotional Signal Engine — biometric extraction via rPPG and neural mesh. 35 claims. Filed.
Patent 2026-508
Ontological Context & Coherence Layer — state mapping, degradation detection, long-term memory. 30 claims. Filed.
Patent 2026-503
Multimodal Dynamic Weighted Fusion — runtime-adaptive α,β,γ signal fusion. On the way.

100% Edge AI

All processing on-device

No server uploads

No cloud storage

GDPR & defence-grade compliant

Works offline and air-gapped

Dual-use: on-device OR server (choice)

Technical Specifications
47
PARAMETERS
<50ms
LATENCY
30
FPS
68
LANDMARKS
5
ARCHITECTURE LAYERS
500+
ONTOLOGY NODES
6
STATE DIMENSIONS
4
CONTROL MODES
2+1
PATENTS
Tech Stack
Frontend

Vanilla JS, WebGL, CSS3

AI / ML

TensorFlow.js, Custom rPPG, face-api.js

Audio

Web Audio API

Crypto

Web Crypto API (SHA-256)

Deploy

PWA, on-device, server, air-gapped

Target Markets

◆ Defence & Security

Operator cognitive monitoring, threat assessment, PTSD screening
$49B

◆ Healthcare

Remote monitoring, mental health, clinical decision support
$15B

◆ AI Platforms

Perception layer for ChatGPT, Claude, Gemini, enterprise copilots
$30B

◆ Education

Student engagement, adaptive learning, real-time comprehension
$8B

◆ HR & Wellbeing

Team mood, burnout prevention, cognitive load monitoring
$120B

◆ Market Research

Audience reactions, ad testing, CX analytics
$80B
Competitive Positioning
CapabilityEmoPulseAffectivaHume AIiMotions
Ontological architecture 5 layers
AI behavioral controlPartial
Dynamic runtime fusion Patent pending
Parameters47~8~12HW dep.
Biometrics (BPM/HRV)HW only
100% on-device
Infrastructure (not app)
PriceAPI $0.01+$500+/moCustom$1000+/mo
License

This software is PROPRIETARY and protected by copyright and filed patents (EU/US).

VIEW FULL LICENSE →

Feel the Future

Home Live Dashboard Under the Hood For Investors

Arvydas Pakalniskis — Founder & CEO
info@emopulse.app · emopulse.app