Mobile & Tablet
Per-Device Custom rPPG Model Training
We train device-specific rPPG models for your exact smartphone or tablet camera hardware — front-facing selfie cameras, depth sensors, and multi-lens arrays. Every model is built from scratch for the sensor in your target device.
Custom preprocessing handles auto-exposure, rolling shutter, and OIS artifacts unique to each device. Generic rPPG SDKs treat all mobile cameras the same — we build models that account for the specific signal characteristics of yours.
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What We Build
Per-Device Model Training
Individual rPPG models trained on data from your target device hardware. An iPhone 15 Pro camera behaves differently from a Samsung Galaxy S24 — we train for yours specifically.
Auto-Exposure Compensation
Custom preprocessing that handles the aggressive auto-exposure algorithms on mobile cameras, which cause brightness fluctuations that corrupt rPPG signals in generic SDKs.
Rolling Shutter Correction
Preprocessing that compensates for rolling shutter artifacts in CMOS sensors — the temporal skew across frame rows introduces systematic error that we model and remove.
OIS Artifact Removal
Optical image stabilization creates micro-movements that generic rPPG algorithms interpret as physiological signal. Our preprocessing isolates and removes OIS-induced artifacts.
Native iOS & Android SDKs
Production-ready Swift (iOS) and Kotlin (Android) SDKs with full API documentation, sample apps, and integration guides. Not cross-platform wrappers — true native performance.
White-Label UI Components
Pre-built measurement screens, progress indicators, and results displays that match your app's design system. Fully customizable colors, fonts, animations, and layout.
Built for Mobile Hardware
Supported Platforms
iOS 15+, Android 10+, iPadOS 15+, Android tablets
Camera Requirements
Front-facing camera, minimum 720p, 24fps+
SDK Languages
Swift for iOS, Kotlin for Android, TypeScript for React Native bridge
Measurement Time
30 seconds default, configurable 15-60 seconds
SDK Size
Under 15MB for both iOS and Android
Output
Native objects, JSON, FHIR R4 Observation resources
Mobile & Tablet rPPG FAQ
Common questions about custom rPPG for mobile and tablet devices
Why does per-device training matter for mobile?
Every smartphone camera has different sensor characteristics, ISP processing, auto-exposure behavior, and OIS implementation. A model trained on iPhone data performs measurably worse on Samsung and vice versa.
Can you support our specific device fleet?
We train models for any device. Enterprise customers with specific device fleets (e.g., company-issued iPads, specific Android tablets) get models tuned exactly for those devices.
Is the SDK a React Native wrapper or truly native?
Truly native. Swift for iOS, Kotlin for Android. We offer a React Native bridge for cross-platform apps, but the core inference runs natively for maximum performance.
How does white-label work?
We deliver customizable UI components (SwiftUI/Kotlin Compose) that you style with your brand assets. Measurement screens, progress animations, and results displays — all configurable via a theming API.
What vitals can be measured on mobile?
Heart rate, respiratory rate, HRV (SDNN, RMSSD), blood pressure estimation, SpO2, and stress level. All from the front-facing camera in a 30-second measurement.
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