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A reliable local-first heart-rate database stores each measurement with its timestamp, value, unit, source, and sync identity—not just a daily average. Keep the original platform record and its provenance alongside fields you normalize for queries. That lets you compare readings from multiple sources without losing where they came from or when they were recorded.
This is data-model guidance, not medical interpretation. Apple HealthKit and Android Health Connect expose different data models, and neither guarantees that every app or device supplies identical fields.
What to store for each heart-rate reading
Represent a heart-rate series as individual samples. Health Connect’s HeartRateRecord, for example, contains samples with their own time and beats-per-minute value. Preserve those sample times if later queries may need the original cadence; a minute-level average cannot recover the readings it replaced. See Android’s Health Connect write-data guidance.
A practical logical model separates the reading from the record and the source that supplied it. The following table is a design recommendation based on platform fields, not a schema required by Apple or Android.
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| Entity | Useful fields | Purpose |
|---|---|---|
heart_rate_sample |
Local primary key; parent record key; sample timestamp as an absolute instant; original offset or civil-time context when available; numeric value; unit; sample/type identifier | Stores an individually queryable reading without discarding its native time or measurement meaning. |
source_record |
Platform; native record ID when available; start and end; source key; import or update metadata; version or last-modified marker when supplied | Preserves the provider’s record boundary and identity, and gives samples a place to reference their originating record. |
data_source |
Platform or app origin; source name and version where available | Identifies which app or platform supplied a record. |
device |
Available device details, such as type, manufacturer, or model | Records hardware provenance separately instead of repeating device descriptions on every sample. |
Keep source metadata attached to a source record or in related source and device entities. This separation makes it possible to explain a reading’s origin while avoiding redundant device details on every row. Platform fields differ: HealthKit records source and version and identifies the hardware device, while Health Connect metadata includes data origin, device details, a generated record ID, and optional client sync identity and version. See Apple’s HealthKit framework overview and Android’s Health Connect data type format.
How to preserve meaning across Apple and Android imports
Use two layers: retain the source-native record and fields you receive, then map the useful values into a consistent local query model. Do not let normalization erase record boundaries, sample timestamps, or source identity.
- Keep the native type and unit. HealthKit uses constrained data types and units; its heart-rate type is
heartRate. Health Connect represents heart-rate samples as timestamped bpm values. Store the native representation or an auditable mapping alongside normalized values. - Make mappings explicit. Record how each source type and unit maps to your normalized field. This makes conversions inspectable and avoids assuming two platform records are interchangeable just because both concern heart rate.
- Preserve provenance in the mapping. Keep platform, source app, device, and native record identity connected to the normalized sample. A normalized query should not make it impossible to trace a value back to its original record.
How to handle time zones and local-day reports
Order and compare readings by their absolute instants, but preserve the source’s zone offset or equivalent civil-time context when it is available. The instant answers when a sample occurred globally; the offset can help determine which local calendar day a user or source intended.
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Health Connect requires a zone offset when writing data so an app can represent civil time, which may not be UTC. If the intended local offset is known, do not silently replace it with UTC. The platform’s guidance is in the Health Connect data type format documentation.
Test date-boundary and daylight-saving transitions in the application’s reporting logic. The platform documentation does not prescribe one universal local database representation, so choose a representation that retains the instant and the available source context without confusing the two.
How to make imports idempotent without merging distinct readings
Timestamp alone is not a safe universal key. Health Connect states that its generated record IDs are not tied to timestamps, and distinguishes those IDs from app-supplied client IDs. Apple HealthKit exposes different source and sync metadata concepts; do not treat Android client identifiers as Apple identifiers.
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- Capture native identity. Store the platform record ID when the provider supplies one, along with the platform and source. Keep sample identity separate where the source model requires it.
- Keep a stable import or client key when supported. Health Connect client IDs can help with syncing and conflict resolution. They are distinct from the generated Health Connect ID.
- Track updates. Preserve a client record version or other update marker when supplied. Health Connect client record versions support version checks during upsert; keep these distinct from your local primary key.
- Define behavior for sources without stable IDs. Choose and document an application-level matching policy rather than assuming that equal timestamps mean equal records. The provider documentation cited here does not define a universal cross-platform conflict policy.
Health Connect’s identity and version fields are described in its data type format documentation and write-data guidance. HealthKit’s separate metadata concepts are documented under Metadata Keys.
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How to choose record granularity
Store the producer’s real sample timestamps when downstream use may require individual readings. Aggregating early saves storage or query work only by giving up detail; keep both raw samples and derived summaries if your product needs both.
Android’s current Health Connect write guidance advises using multiple smaller interval records rather than one day-long record that is continually updated. It gives a new heart-rate record for each minute as an example, with that minute’s samples grouped inside it. The same guidance uses a five-second heart-rate sampling interval as an example and describes four samples per minute in its general guidance. These are platform examples, not a clinical standard, a universal sampling policy, or a required local database layout. See Write data | Health Connect.
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What to index and test in a local database
Choose indexes from the queries your application actually runs, then measure representative workloads. Possible starting points include an index on (sample_time, source_id) for time-range queries by source, and an index on the sample’s source-record foreign key for retrieving all samples in a record. These are design suggestions, not vendor requirements.
- Can a time-range query return readings in instant order while filtering by source?
- Can a local-day report use retained offset or civil-time context rather than assuming UTC boundaries?
- Can a sample be traced to its native record, source app, and device when those details are available?
- Can an update be recognized without using timestamp as the sole identity key?
- Does a derived aggregate remain distinguishable from an original sample?
Database choice, index plan, backup and encryption design, retention, cross-device conflict behavior, and legal compliance depend on the application and its geography. The platform data models do not settle those decisions or establish that a particular local schema meets regulatory obligations.
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