A patented perception layer that turns a standard camera into a continuous, machine-readable state of the person at the controls. No wearable, no additional sensor, no network dependency. Defence, aviation, clinical research, automotive, authentication, autonomy.
One owner of the core, in one European jurisdiction
EmoPulse is built by UAB Omvion, registered in Kaunas, Lithuania, with a United States entity in Illinois. The architecture, the pending patents and the source belong to the company. When a programme office asks who controls the core and who signs for the delivery, both answers are the same legal entity.
We supply a layer, not an application. It is integrated into the partner's stack, their hardware, their security boundary and their evidence regime, and it is delivered the way defence and clinical programmes require: a written interface specification, a reproducible build with a published hash, and a signed artefact the receiving side can verify without trusting us.
European by design
Registered in Lithuania, EU. Processing runs on the device by default, so the data protection question is answered by the architecture rather than by a policy document.
Owned outright
3 patents pending, all held by the company. No third-party model licences in the interpretive layer.
Built to be integrated
Edge or server, air-gapped or connected. The same core engine, configured per deployment rather than rewritten.
02The architecture
Five layers between a camera frame and a decision
The architecture computes up to 47 parameters from a standard camera in real time, and a deployment uses the subset its job needs. Voice and text enter as separate streams and are fused at the interpretive layer. No additional hardware, no cloud requirement.
1
Signal Acquisition
Raw signals from a single camera - pulse and variability from skin micro-colour, micro-expressions, gaze, action units, pupil, blink. Voice and text enter as separate streams.
2
Feature Computation
Raw signals become 47 normalised parameters. Not "happy" or "sad" labels - a multidimensional description of this person right now, each parameter with intensity, stability and trend.
3
Cross-Stream Coherence
Face, voice and text are checked against each other. Contradictions are detected rather than averaged away. This is where the architecture is genuinely new, and it is what the pending patents cover.
4
State Vector Assembly
Coherent signals assemble into a compact state vector that a host system can act on - risk, clarity of intent, and a living signature of the person in front of the camera.
5
Temporal Context
A personal baseline and deviation from it. The system reacts to a change in this individual, not to a population average.
The deeper description, including what we measure and what we deliberately do not, is in Under the Hood.
What a programme receives
Interface specification
Frame rate, format, timing, quality indicators and failure behaviour, written down and agreed on both sides before integration begins.
Reproducible artefact
A deterministic build with a published hash. The receiving side rebuilds it and compares, rather than trusting a binary we sent.
Signed delivery
The artefact is signed with a key held by us and verified with our public key, so provenance is a technical fact rather than a claim in an e-mail.
Deployment modes
Edge by default. Optional server mode where a second party must see the state in real time. Air-gapped operation supported, because no link is required.
03Solutions
Eight domains, one core engine
Each domain is a separate integration with its own evidence and regulatory route. The engine underneath them is the same, configured per deployment rather than rebuilt.
01
Defence and allied security
Operator state during a task: fatigue, stress load, attention. Runs on the device, works air-gapped, and never needs to send an image anywhere. This is the domain where the on-device constraint stops being a privacy nicety and becomes an operational requirement.
02
Aviation and aerospace
Continuous fatigue and micro-sleep indicators for crews and ground operators, from a camera that is already in the cockpit or the console, without a wearable and without a trial-specific rig.
03
Medicine and clinical research
Physiological indicators visible to a clinician during a consultation, and a structured record afterwards. Research instrument first: the route here runs through clinical studies, not around them.
04
Automotive
Driver monitoring against the European requirement, using the standard camera rather than a dedicated sensor package, with the computation staying inside the vehicle.
05
Security and continuous authentication
A living signature rather than a stored template: involuntary signals re-verified through the session instead of matched once at the door. An attacker has to reproduce a person, not a picture of one.
06
AI platforms
The missing input for assistants and agents. A model that receives a state vector can tell the difference between a user who is thinking and a user who is lost, and change what it does about it.
07
Robotics and humanoids
A machine that shares physical space with a person needs to read that person continuously, on board, with no network in the loop. The state vector is exactly the input such a system lacks today.
08
Industrial and training environments
Readiness before a shift, cognitive load during it, and evidence afterwards that a procedure was performed by someone in a fit state to perform it.
04Demonstrators
Four public builds, open one and check it yourself
The same architecture in four configurations, each reachable without an account. Proof-of-concept demonstrators, not certified products.
Our technology sits inside a European defence research programme built across five member states, with our company as technology owner and technical coordinator of the sensing work, backed by a letter of support from the Lithuanian Ministry of National Defence. We are a registered participant in the European Union research and funding system under participant identification code 864933093. In the United States the work runs through our Illinois entity.
Where systems cannot send an image off the device, cannot rely on a link, and cannot expose a person's biometrics to a third party, the computation has to happen where the camera is. That constraint is the reason this architecture exists in the form it does.
Institutions we work with
Defence, security, space and health institutions on both sides of the Atlantic, and the industry partners who put the layer into hardware.
Europe
European Defence FundOur technology sits inside a defence research programme built across five member states. We own the layer and coordinate the sensing work.
Lithuanian Ministry of National DefenceBacks that work with a letter of support, issued to our company in September 2026.
NATO innovation channelsOur architecture is known to the alliance innovation programmes and has been assessed by them.
European Space Agency, Lithuanian incubation networkWorking through where the layer belongs in space operations, where bandwidth and a second operator do not exist.
Lithuanian Innovation Agency and communications regulatorEngaged on the artificial intelligence regulatory sandbox track.
Lithuanian health authorityGave us a written regulatory position on where our described use sits. We asked before we built, not after.
Lithuanian data protection authorityConsulted in writing on the biometric data question.
United States
Federal Bureau of InvestigationOur technical paper is in their research channel.
United States Air ForceOur paper is held by the contracting office for review under an innovation solicitation.
United States ArmyWe work the innovation competition line as its windows open.
Naval and special operations researchTechnical papers in preparation for their research routes.
DARPAOur technical summary is with the relevant office.
Industry
SamsungOur submission to their advanced technology programme is under review.
Sensor and device manufacturersDirect technical work on what the layer needs from their hardware, in Europe and the United States.
Robotics and humanoid groupsConversations about the operator-facing layer on board the machine.
DistributionLive on Google Play, RapidAPI and ClawHub.
Naming an institution here describes our work with it. It implies no endorsement or approval by it, and we do not present it as one.
06Who we build with
The companies we build with
Research institutes, defence electronics houses and innovation organisations across Europe, working with us on where this layer belongs and how it plugs into their systems.
AT
ACORDE Technologies
Spain
IB
IngB RT&S
Germany
ITA
Instituto Tecnológico de Aragón
Spain
F6S
F6S
Ireland
OM
UAB Omvion
Lithuania
GV
GV66 CO
United States
Alongside them we work directly with sensor and device manufacturers, robotics groups and identity companies in Europe and the United States, which is how the layer is built against real hardware rather than against a specification sheet.
Advisory
Dr. Anastasia Vasina, MD, PhD (Pathology)
Fractional Chief Medical Officer; formerly CPO and CMO at Soter Analytics. Medical and ethical advisory: where a physiological signal may be spoken about, and where it may not.
Angelo Arcadu
Public affairs and strategic communications; project delivery in defence, healthcare and critical infrastructure, including work with the Italian Ministry of Defence. Based in Washington, D.C.
Advisers act in an advisory capacity. Their affiliations are their own and do not constitute an endorsement by any institution.
07Maturity and assurance
Stated plainly, because a programme office will ask
Evaluation status, intellectual property position and the open technical questions, as they stand today.
Intellectual property. 3 patents pending, held by the company. None granted. No third-party model licence sits in the interpretive layer.
Published performance. The 93 to 96 per cent figures in the literature belong to peer-reviewed studies of the underlying methods, not to this system. We do not present them as our benchmark.
Independent evaluation. Not yet performed. Measurements to date are our own, and third-party evaluation is on the roadmap as a deliverable, not as a claim.
Regulatory position. Not a medical device. Outputs are informational indicators derived from camera signal estimation, and the clinical route runs through ethics review and a study protocol.
Anti-spoofing. Liveness detection is at proof-of-concept maturity. Passive methods are not deepfake-proof and we do not describe ours as such.
Generalisation. Behaviour across skin tones, lighting and motion is an open question and is precisely what the planned evaluation campaigns address.
Contact
If any of this belongs in your programme
Write to us. One address, read by the people who build the thing.