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Use case

Wearable API for Research Studies

High-resolution series from consumer wearables, with units and provenance you can cite.

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Research & digital biomarkers

Studies that use consumer wearables spend more time on data engineering than on analysis: each vendor has its own export format, its own sampling cadence and its own idea of what a "day" is. WearLink normalises the summaries and exposes the high-resolution series streams with canonical units.

Provenance is preserved on every record — which provider, which device type where exposed, when it was ingested and whether it was revised — so a methods section can state exactly what was measured.

Per-participant export produces the full normalised history for a user in one request, which is the shape most analysis pipelines want.

What usually goes wrong

Series data is where the value is, and where vendors differ most

Heart-rate series arrive at different cadences; HRV is rMSSD on one device and a proprietary index on another. The summary is comparable, the series often is not.

Participants own many different devices

A pragmatic study accepts whatever the participant wears. That means one pipeline per vendor unless something normalises upstream.

Reproducibility needs provenance

A result that cannot say which device, which firmware-era algorithm and which revision produced a value cannot be reproduced.

How WearLink handles it

  • High-resolution series streams — Heart rate, HRV, respiratory rate, temperature and more as series events alongside the daily summaries.
  • Canonical units, originals preserved — SI and clinical units on the normalised object with the provider’s original values retained for audit.
  • Per-participant export — One request returns the full normalised history for a user, including revisions.
  • Sandbox with seed data — Build the analysis pipeline against realistic seeded data before the first participant is enrolled.

FAQ

Research & digital biomarkers — frequently asked

Can I get raw heart-rate series rather than daily averages?
Yes. Series events carry the higher-resolution streams where the device exposes them; the data-type pages list the series events per family.
How is HRV normalised?
To milliseconds, with the provider’s method recorded. rMSSD-based values and proprietary indices are labelled rather than silently mixed; the HRV page explains the differences.
Can participants withdraw and have data deleted?
Yes. The per-user deletion endpoint removes stored data and revokes connections.
Is there academic pricing?
The free tier covers small pilots and the Developer tier covers 50 participants. For larger cohorts, contact us with the study size.

Other use cases

Same API, different products

Fitness & coaching apps

Pull workouts, heart rate, recovery and sleep from the devices your members already wear.

Clinical & remote monitoring

Heart rate, blood pressure, glucose and sleep from consumer devices, in one auditable pipeline.

Corporate wellness

Steps, sleep and activity challenges across every device an employee brings, with per-user consent.

Insurance & incentive programmes

Verified activity and sleep data for behaviour-based incentives, with an audit trail behind every reward.

Connect your first wearable today

Free for up to 3 connected users. No credit card. Your first API key is issued the moment you sign up.

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