Every wearable metric, one normalised schema
WearLink maps 15 data families across 109 webhook event types — 22 summary objects and 87 high-resolution series streams. Each page below covers what the metric is, which providers supply it, the exact events to subscribe to, and the places providers disagree badly enough to break a naive integration.
Sleep
7/12 liveSleep stages, duration, efficiency and timing, normalised across every ring, watch and mattress sensor.
4 events · sleep.created
Heart Rate Variability
6/9 liveRMSSD and SDNN heart-rate variability from rings, straps and watches — as separate, clearly-labelled streams.
3 events · heart_rate_variability.created
Heart Rate
8/12 liveContinuous, resting and workout heart rate from every major wearable, in one schema and one unit.
6 events · heart_rate.created
Workouts
7/10 live614 provider sport names collapsed into 90 unified workout types, with per-workout metrics and streams.
12 events · workout.created
Steps & Daily Activity
6/8 liveStep counts, distance, floors and active minutes — deduplicated across phone and watch.
8 events · steps.created
Calories & Energy
7/8 liveActive and basal energy expenditure, normalised to kilocalories and fusible with nutrition intake.
5 events · calories.created
Recovery & Readiness
2/4 liveProvider readiness and recovery scores, delivered with their inputs so you can build your own.
3 events · recovery_score.created
Blood Glucose & CGM
2/4 liveContinuous glucose monitoring streams normalised to a single unit, with insulin delivery alongside.
3 events · blood_glucose.created
Blood Pressure
4/4 liveSystolic and diastolic readings from connected cuffs, with the measurement context that makes them interpretable.
3 events · blood_pressure.created
Body Composition
5/6 liveWeight, BMI, body fat, lean mass and skeletal muscle mass from connected scales and platforms.
9 events · body_composition.created
Body & Skin Temperature
4/6 liveAbsolute and deviation-based temperature streams — kept separate, because they are not the same signal.
6 events · body_temperature.created
Respiratory Rate & SpO2
6/8 liveBreathing rate, oxygen saturation and breathing-disturbance streams from rings and watches.
6 events · respiratory_rate.created
Nutrition & Energy Balance
3/3 livePhoto-based meal recognition with per-dish macros, fused with wearable burn into daily energy balance.
1 event · nutrition.log.created
Stress
2/3 liveVendor stress scores and the electrodermal and HRV-derived signals underneath them.
3 events · stress.created
VO2 Max & Fitness Metrics
3/6 liveCardiorespiratory fitness estimates, fitness age and walk-test distance across platforms.
5 events · fitness_metrics.created
Frequently asked questions
- What data types does WearLink normalise?
- 15 families — sleep, HRV, heart rate, workouts, steps, calories, recovery, glucose, body composition, temperature, respiratory rate, nutrition, stress and fitness metrics — delivered across 109 webhook event types (22 summary objects and 87 high-resolution series streams).
- What does "normalised" actually mean here?
- Same field names, same units and same object shape regardless of which provider produced the record. A sleep session from an Oura ring and one from a WHOOP band arrive identically structured. Where providers genuinely disagree — HRV method, sleep stage taxonomy, active versus total calories — WearLink keeps the distinction visible rather than averaging it away.
- What is the difference between a summary event and a series event?
- A summary event carries a settled record for a period — a night of sleep, a workout, a daily total. A series event carries the underlying high-resolution samples, such as second-by-second heart rate or five-minute glucose readings. Subscribe to summaries for most product features and to series when you need the raw signal.
- Can I compare a metric between two different devices?
- It depends on the metric, and each data-type page says so explicitly. Durations and counts are broadly comparable; proprietary scores such as recovery and readiness are not; HRV is only comparable when both devices report the same statistic. Assume within-user, within-device trends are reliable and cross-device absolutes are not.
Looking for a specific device instead? Browse integrations by provider or check live connection status.