Tejas Kumar presented a React Native app he built to help people regulate workload and stress using a single metric: HRV (Heart Rate Variability). He walked through what HRV represents, why low HRV correlates with stress, and how wearables like Apple Watch (and an Oura Ring) capture the data passively over time, where trends matter more than any single reading.

From there, the talk shifted into what it takes to ship this kind of product. Tejas showed the app’s traffic-light readiness UI, explained why it requires 28 days of HRV data to calculate readiness, and toured the core implementation: requesting HealthKit permission, querying HRV samples via a React Native HealthKit library, and calculating stats (mean, standard deviation, coefficient of variation) in TypeScript. He also covered key production decisions around toolchain (Expo), deployment (EAS), library selection signals, and keeping computation on-device to avoid data residency complexity.

What you’ll walk away with:

• A clear mental model of HRV and why trends can guide day-to-day workload decisions
• A practical pattern for turning HealthKit data into a simple, readable UI
• How readiness can be derived from a 60‑day baseline vs a 7‑day trend (plus stability via coefficient of variation)
• A production-oriented HealthKit integration flow: permissions → queries → stats
• The concrete tradeoffs Tejas made: Expo toolchain, EAS deployment, and on-device computation

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