Smart Wearable Ring
US-based consumer-health / wearable technology startupA compact smart ring continuously captures physiological and activity data while operating under extremely tight constraints around size, power consumption, wireless connectivity and sensor integration.
Where AI accelerated vs. where our engineers led.
Every project follows the same Rivix Split — AI drafts the mechanical work, a named engineer reviews and owns every decision that touches safety, cost, or a regulatory limit.
Where AI accelerated
- Embedded implementation & sensor interfaces
- BLE code
- Data-processing pipelines
- Mobile & backend code
- Test generation & documentation
Where our engineers led
- Sensor architecture & miniaturization
- Power budget
- Mechanical/electrical constraints
- Signal quality
- Hardware/firmware integration & validation
Technical deep-dive
Additional detail on architecture, stack and implementation specifics for this engagement.
Architecture & stack
The ring integrates multiple physiological and motion sensors around a compact, low-power MCU with an on-board edge-AI-capable core for basic signal processing, all within a form factor that leaves very little board area or battery volume to work with. Firmware handles sensor scheduling, on-device pre-processing and BLE sync to a companion mobile app.
- Multi-sensor front-end (PPG/temperature-class sensing) on a compact low-power MCU
- On-board signal-conditioning core to minimize what needs off-chip processing
- BLE sync to a companion mobile app for trend storage and account-level data
Connectivity & data pipeline
Given the extreme power constraints, most signal conditioning and feature extraction happens on-device before data is batched and synced over BLE, minimizing radio-on time. The mobile app and backend handle longer-term trend analysis and account-level storage.
- Most feature extraction and conditioning done on-device before any radio activity
- Data batched and synced on a fixed cadence rather than streamed continuously
- Backend handles longer-horizon trend analysis outside the power-constrained device
Key engineering challenges
Miniaturization was the dominant constraint — fitting sensors, antenna, battery and charging contacts into a ring form factor while maintaining signal quality against motion and varying finger contact. Power budgeting to hit a multi-day battery life target required careful tradeoffs between sensing frequency, radio duty-cycling and processing load.
- Fitting sensors, antenna, battery and charging contacts into a ring-scale PCB footprint
- Maintaining signal quality against motion artifact and variable finger contact/pressure
- Meeting a 7+ day battery target against continuous physiological sensing
Why this approach
Doing signal conditioning on-device rather than shipping raw streams to the cloud was necessary to hit the battery-life target — radio transmission is one of the most power-expensive operations available to a device this small, so minimizing what gets sent was a first-order design decision.
- On-device conditioning chosen because radio transmission is the single most power-expensive operation available at this form factor
- Batched rather than streamed sync directly protects the battery-life target
- Sensor selection and MCU pairing were driven primarily by the power budget, not raw sensing capability