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Clinical Kiosks

Clinical Kiosk & Point-of-Care

Custom rPPG for Clinical Kiosks & Point-of-Care Devices

We build and train rPPG models specifically for fixed-mount clinical kiosk cameras with controlled lighting, known distance-to-subject, and medical-grade imaging sensors. Every variable your kiosk controls is an advantage we exploit for higher accuracy.

Your kiosk enclosure, your camera module, your lighting rig, your processing hardware — we build a model tuned to all of it and deliver production-ready output in FHIR R4, HL7, or any format your EHR requires.

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What We Build

Fixed-mount camera tuning
Controlled lighting optimization
Known-distance calibration
FHIR R4 output
Medical-grade sensor tuning

What We Build

1

Fixed-Mount Camera Optimization

Models tuned for your exact camera module, mounting position, and enclosure geometry — eliminating variables that degrade accuracy in uncontrolled environments.

2

Controlled Lighting Preprocessing

Custom preprocessing that exploits the controlled, known lighting of your kiosk enclosure for maximum signal-to-noise ratio in rPPG extraction.

3

Known-Distance Calibration

Models calibrated for the fixed subject-to-camera distance in your kiosk design, optimizing facial ROI detection and signal extraction for that specific geometry.

4

Medical-Grade Sensor Tuning

Preprocessing and model training specifically for medical-grade CMOS and CCD sensors — leveraging their superior dynamic range, lower noise floor, and linear response characteristics.

5

Direct FHIR R4 Output

Vital sign data output as FHIR R4 Observation resources with proper LOINC coding, ready for direct EHR integration without middleware.

6

Sub-Second Extraction

Optimized inference for embedded kiosk processors — Qualcomm, Intel NUC, NVIDIA Jetson — delivering vital signs in under one second per measurement cycle.

Technical Specifications

Camera Types

Medical-grade CMOS, industrial USB3 cameras, GigE Vision cameras, custom optical modules

Processing Targets

Intel NUC, NVIDIA Jetson Orin Nano, Qualcomm QCS610, Raspberry Pi CM4

Distance Range

30cm-120cm calibrated

Measurement Time

15-30 seconds for full vital panel

Output Formats

FHIR R4, HL7 v2, custom JSON, direct EHR connectors

Compliance

HIPAA, SOC 2 Type II, ISO 13485-aligned

Clinical Kiosk rPPG FAQ

Common questions about custom rPPG builds for clinical kiosks and point-of-care devices

Why does a kiosk need custom rPPG versus a standard SDK?

A controlled kiosk environment allows significantly higher accuracy than a generic mobile SDK. Custom tuning exploits the known lighting, fixed distance, and specific camera hardware of your kiosk to achieve medical-grade signal quality — advantages that a one-size-fits-all SDK simply cannot leverage.

Can you output vitals directly to our EHR?

Yes. We deliver vital sign data as FHIR R4 Observation resources with proper LOINC codes, HL7 v2 ORU messages, and direct connectors for Epic, Cerner, and Athenahealth. Your kiosk can write vitals straight into the patient chart without middleware.

What camera modules do you recommend for kiosks?

We can work with any camera, but we recommend specific medical-grade CMOS modules for maximum signal quality based on your enclosure design and lighting. Regardless of what you choose, we tune the preprocessing and model to your exact hardware.

How does the controlled environment improve accuracy?

Fixed lighting eliminates illumination variation. Known distance eliminates focal length ambiguity. A fixed mount eliminates camera motion. Each removed variable increases signal fidelity — a kiosk with all three controlled can achieve accuracy levels that mobile and uncontrolled deployments cannot match.

What's the deployment timeline for a kiosk build?

Typically 1-2 weeks for the initial model delivery. Kiosk builds are faster than other deployment types because the controlled environment simplifies preprocessing — fewer variables to account for means faster tuning and validation cycles.

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