Write data

This guide is compatible with Health Connect version 1.1.0-alpha12.

This guide covers the process of writing or updating data in Health Connect.

Handle zero values

Some data types like steps, distance, or calories might have a value of 0. Only write zero values when it reflects true inactivity while the user was wearing the device. Don't write zero values if the device wasn't worn, data is missing, or the battery died. In such cases, omit the record to avoid misleading data.

Set up data structure

Before writing data, we need to set up the records first. For more than 50 data types, each have their respective structures. See the Jetpack reference for more details about the data types available.

Basic records

The Steps data type in Health Connect captures the number of steps a user has taken between readings. Step counts represent a common measurement across health, fitness, and wellness platforms.

The following example shows how to set steps count data:

val endTime = Instant.now()
val startTime = endTime.minus(Duration.ofMinutes(15))

val stepsRecord = StepsRecord(
    count = 120,
    startTime = startTime,
    endTime = endTime,
    startZoneOffset = ZoneOffset.UTC,
    endZoneOffset = ZoneOffset.UTC,
    metadata = Metadata.autoRecorded(
        device = Device(type = Device.TYPE_WATCH)
    )
)

Records with units of measurement

Health Connect can store values along with their units of measurement to provide accuracy. One example is the Nutrition data type that is vast and comprehensive. It includes a wide variety of optional nutrient fields ranging from total carbohydrates to vitamins. Each data point represents the nutrients that were potentially consumed as part of a meal or food item.

In this data type, all of the nutrients are represented in units of Mass, while energy is represented in a unit of Energy.

The following example shows how to set nutrition data for a user who has eaten a banana:

val endTime = Instant.now()
val startTime = endTime.minus(Duration.ofMinutes(1))

val banana = NutritionRecord(
    name = "banana",
    energy = 105.0.kilocalories,
    dietaryFiber = 3.1.grams,
    potassium = 0.422.grams,
    totalCarbohydrate = 27.0.grams,
    totalFat = 0.4.grams,
    saturatedFat = 0.1.grams,
    sodium = 0.001.grams,
    sugar = 14.0.grams,
    vitaminB6 = 0.0005.grams,
    vitaminC = 0.0103.grams,
    startTime = startTime,
    endTime = endTime,
    startZoneOffset = ZoneOffset.UTC,
    endZoneOffset = ZoneOffset.UTC,
    metadata = Metadata.manualEntry(
        device = Device(type = Device.TYPE_PHONE)
    )
)

Records with series data

Health Connect can store a list of series data. One example is the Heart Rate data type that captures a series of heartbeat samples detected between readings.

In this data type, the parameter samples is represented by a list of Heart Rate samples. Each sample contains a beatsPerMinute value and a time value.

The following example shows how to set heart rate series data:

val endTime = Instant.now()
val startTime = endTime.minus(Duration.ofMinutes(5))

val heartRateRecord = HeartRateRecord(
    startTime = startTime,
    startZoneOffset = ZoneOffset.UTC,
    endTime = endTime,
    endZoneOffset = ZoneOffset.UTC,
    // records 10 arbitrary data, to replace with actual data
    samples = List(10) { index ->
        HeartRateRecord.Sample(
            time = startTime + Duration.ofSeconds(index.toLong()),
            beatsPerMinute = 100 + index.toLong(),
        )
    },
    metadata = Metadata.autoRecorded(
        device = Device(type = Device.TYPE_WATCH)
    ))

Request permissions from the user

After creating a client instance, your app needs to request permissions from the user. Users must be allowed to grant or deny permissions at any time.

To do so, create a set of permissions for the required data types. Make sure that the permissions in the set are declared in your Android manifest first.

// Create a set of permissions for required data types
val PERMISSIONS =
    setOf(
  HealthPermission.getReadPermission(HeartRateRecord::class),
  HealthPermission.getWritePermission(HeartRateRecord::class),
  HealthPermission.getReadPermission(StepsRecord::class),
  HealthPermission.getWritePermission(StepsRecord::class)
)

Use getGrantedPermissions to see if your app already has the required permissions granted. If not, use createRequestPermissionResultContract to request those permissions. This displays the Health Connect permissions screen.

// Create the permissions launcher
val requestPermissionActivityContract = PermissionController.createRequestPermissionResultContract()

val requestPermissions = registerForActivityResult(requestPermissionActivityContract) { granted ->
  if (granted.containsAll(PERMISSIONS)) {
    // Permissions successfully granted
  } else {
    // Lack of required permissions
  }
}

suspend fun checkPermissionsAndRun(healthConnectClient: HealthConnectClient) {
  val granted = healthConnectClient.permissionController.getGrantedPermissions()
  if (granted.containsAll(PERMISSIONS)) {
    // Permissions already granted; proceed with inserting or reading data
  } else {
    requestPermissions.launch(PERMISSIONS)
  }
}

Because users can grant or revoke permissions at any time, your app needs to periodically check for granted permissions and handle scenarios where permission is lost.

Write data

One of the common workflows in Health Connect is writing data. To add records, use insertRecords.

The following example shows how to write data inserting step counts:

suspend fun insertSteps(healthConnectClient: HealthConnectClient) {
    val endTime = Instant.now()
    val startTime = endTime.minus(Duration.ofMinutes(5))
    try {
        val stepsRecord = StepsRecord(
            count = 120,
            startTime = startTime,
            endTime = endTime,
            startZoneOffset = ZoneOffset.UTC,
            endZoneOffset = ZoneOffset.UTC,
            metadata = Metadata.autoRecorded(
                device = Device(type = Device.TYPE_WATCH)
            )
        )
        healthConnectClient.insertRecords(listOf(stepsRecord))
    } catch (e: Exception) {
        // Run error handling here
    }
}

Update data

If you need to change one or more records, especially when you need to sync your app datastore with data from Health Connect, you can update your data. There are two ways to update existing data which depends on the identifier used to find records.

Metadata

It is worth examining the Metadata class first as this is necessary when updating data. On creation, each Record in Health Connect has a metadata field. The following properties are relevant to synchronization:

Update after reading by time range

To update data, prepare the needed records first. Perform any changes to the records if necessary. Then, call updateRecords to make the changes.

The following example shows how to update data. For this purpose, each record has its zone offset values adjusted into PST.

suspend fun updateSteps(
    healthConnectClient: HealthConnectClient,
    prevRecordStartTime: Instant,
    prevRecordEndTime: Instant
) {
    try {
        val request = healthConnectClient.readRecords(
            ReadRecordsRequest(
                recordType = StepsRecord::class, timeRangeFilter = TimeRangeFilter.between(
                    prevRecordStartTime, prevRecordEndTime
                )
            )
        )

        val newStepsRecords = arrayListOf<StepsRecord>()
        for (record in request.records) {
            // Adjusted both offset values to reflect changes
            val sr = StepsRecord(
                count = record.count,
                startTime = record.startTime,
                startZoneOffset = record.startTime.atZone(ZoneId.of("PST")).offset,
                endTime = record.endTime,
                endZoneOffset = record.endTime.atZone(ZoneId.of("PST")).offset,
                metadata = record.metadata
            )
            newStepsRecords.add(sr)
        }

        healthConnectClient.updateRecords(newStepsRecords)
    } catch (e: Exception) {
        // Run error handling here
    }
}

Upsert through Client Record ID

If you are using the optional Client Record ID and Client Record Version values, we recommend using insertRecords instead of updateRecords.

The insertRecords function has the ability to upsert data. If the data exists in Health Connect based on the given set of Client Record IDs, it gets overwritten. Otherwise, it is written as new data. This scenario is useful whenever you need to sync data from your app datastore to Health Connect.

The following example shows how to perform an upsert on data pulled from the app datastore:

suspend fun pullStepsFromDatastore() : ArrayList<StepsRecord> {
    val appStepsRecords = arrayListOf<StepsRecord>()
    // Pull data from app datastore
    // ...
    // Make changes to data if necessary
    // ...
    // Store data in appStepsRecords
    // ...
    var sr = StepsRecord(
        metadata = Metadata.autoRecorded(
            clientRecordId = "Your client record ID",
            device = Device(type = Device.TYPE_WATCH)
        ),
        // Assign more parameters for this record
    )
    appStepsRecords.add(sr)
    // ...
    return appStepsRecords
}

suspend fun upsertSteps(
    healthConnectClient: HealthConnectClient,
    newStepsRecords: ArrayList<StepsRecord>
) {
    try {
        healthConnectClient.insertRecords(newStepsRecords)
    } catch (e: Exception) {
        // Run error handling here
    }
}

After that, you can call these functions in your main thread.

upsertSteps(healthConnectClient, pullStepsFromDatastore())

Value check in Client Record Version

If your process of upserting data includes the Client Record Version, Health Connect performs comparison checks in the clientRecordVersion values. If the version from the inserted data is higher than the version from the existing data, the upsert happens. Otherwise, the process ignores the change and the value remains the same.

To include versioning in your data, you need to supply Metadata.clientRecordVersion with a Long value based on your versioning logic.

val endTime = Instant.now()
val startTime = endTime.minus(Duration.ofMinutes(15))

val stepsRecord = StepsRecord(
    count = 100L,
    startTime = startTime,
    startZoneOffset = ZoneOffset.UTC,
    endTime = endTime,
    endZoneOffset = ZoneOffset.UTC,
    metadata = Metadata.manualEntry(
        clientRecordId = "Your supplied record ID",
        clientRecordVersion = 0L, // Your supplied record version
        device = Device(type = Device.TYPE_WATCH)
    )
)

Upserts don't automatically increment version whenever there are changes, preventing any unexpected instances of overwriting data. With that, you have to manually supply it with a higher value.

General guidance

Apps must only write own-sourced data to Health Connect.

If data in your app has been imported from another app, then the responsibility falls onto the other app to write its own data to Health Connect.

It's also a good idea to implement logic that handles write exceptions such as data being outside of bounds, or an internal system error. You can apply your backoff and retry strategies on a job scheduling mechanism. If writing to Health Connect is ultimately unsuccessful, make sure that your app can move past that point of export. Don't forget to log and report errors to aid diagnosis.

When tracking data, there are a couple of suggestions you can follow depending on the way your app writes data.

Time zone handling

When writing time-based records, avoid setting offsets to zoneOffset.UTC by default because this can lead to inaccurate timestamps when users are in other zones. Instead, calculate the offset based on the device's actual location. You can retrieve the device's time zone using ZoneId.systemDefault().

val endTime = Instant.now()
val startTime = endTime.minus(java.time.Duration.ofDays(1))
val stepsRecords = mutableListOf<StepsRecord>()
var sampleTime = startTime
val minutesBetweenSamples = 15L
while (sampleTime < endTime) {
    // Get the default ZoneId then convert it to an offset
    val zoneOffset = ZoneOffset.systemDefault().rules.getOffset(sampleTime)
    stepsRecords += StepsRecord(
        startTime = sampleTime.minus(java.time.Duration.ofMinutes(minutesBetweenSamples)),
        startZoneOffset = zoneOffset,
        endTime = sampleTime,
        endZoneOffset = zoneOffset,
        count = Random.nextLong(1, 100),
        metadata = Metadata.unknownRecordingMethod(),
    )
    sampleTime = sampleTime.plus(java.time.Duration.ofMinutes(minutesBetweenSamples))
}
healthConnectClient.insertRecords(
    stepsRecords
)

See the documentation for ZoneId for more details.

Write frequency and granularity

When writing data to Health Connect, use appropriate resolution. Using the appropriate resolution helps reduce storage load, while still maintaining consistent and accurate data. Data resolution encompasses two things:

• Frequency of writes: How often your application write any new data into Health Connect.
  • Write data as frequently as possible when new data is available, while being mindful of device performance.
  • To avoid negatively impacting battery life and other performance aspects, the maximum interval between writes should be 15 minutes.
• Granularity of written data: How often the data was sampled.
  • For example, write heart rate samples every 5 seconds.
  • Not every data type requires the same sample rate. There is little benefit to updating step count data every second, as opposed to a less frequent cadence such as every 60 seconds.
  • Higher sample rates may give users a more detailed and granular look at their health and fitness data. Sample rate frequencies should strike a balance between detail and performance.

Additional guidelines

Follow these guidelines when writing data:

• On every sync, only write new data and updated data that was modified since the last sync.
• Chunk requests to at most 1000 records per write request.
• Restrict tasks to run only when the device is idle and is not low on battery.
• For background tasks, use WorkManager to schedule periodic tasks, with a maximum time period of 15 minutes.

The following code uses WorkManager to schedule periodic background tasks, with a maximum time period of 15 minutes, and a flex interval of 5 minutes. This configuration is set using the PeriodicWorkRequest.Builder class.

val constraints = Constraints.Builder()
    .requiresBatteryNotLow()
    .requiresDeviceIdle(true)
    .build()

val writeDataWork = PeriodicWorkRequestBuilder<WriteDataToHealthConnectWorker>(
        15,
        TimeUnit.MINUTES,
        5,
        TimeUnit.MINUTES
    )
    .setConstraints(constraints)
    .build()

Active tracking

This includes apps that perform event-based tracking such as exercise and sleep, or manual user input such as nutrition. These records are created when the app is in the foreground, or in rare events where it is used a few times in a day.

Verify that your app doesn't keep Health Connect running for the entire duration of the event.

Data must be written to Health Connect in one of two ways:

• Sync data to Health Connect after the event is complete. For example, sync data when the user ends a tracked exercise session.
• Schedule a one-off task using WorkManager to sync data later.

Best practices for granularity and frequency of writes

When writing data to Health Connect, use appropriate resolution. Using the appropriate resolution helps reduce storage load, while still maintaining consistent and accurate data. Data resolution encompasses 2 things:

1. Frequency of writes: how often your application pushes any new data into Health Connect. Write data as frequently as possible when new data is available, while being mindful of device performance. To avoid negatively impacting battery life and other performance aspects, the maximum interval between writes should be 15 minutes.

2. Granularity of written data: how often the data that is pushed in was sampled. For example, write heart rate samples every 5s. Not every data type requires the same sample rate. There is little benefit to updating step count data every second, as opposed to a less frequent cadence such as every 60 seconds. However, higher sample rates may give users a more detailed and granular look at their health and fitness data. Sample rate frequencies should strike a balance between detail and performance.

Structure records for series data

For data types that use a series of samples, such as HeartRateRecord, it's important to structure your records correctly. Instead of creating a single, day-long record that is constantly updated, you should create multiple smaller records, each representing a specific time interval.

For example, for heart rate data, you should create a new HeartRateRecord for each minute. Each record would have a start time and end time spanning that minute, and would contain all the heart rate samples captured during that minute.

During regular syncs with Health Connect (for example, every 15 minutes), your app should write all the one-minute records that have been created since the previous sync. This keeps records at a manageable size and improves the performance of querying and processing data.

The following example shows how to create a HeartRateRecord for a single minute, containing multiple samples:

val startTime = Instant.now().truncatedTo(ChronoUnit.MINUTES)
val endTime = startTime.plus(Duration.ofMinutes(1))

val heartRateRecord = HeartRateRecord(
    startTime = startTime,
    startZoneOffset = ZoneOffset.UTC,
    endTime = endTime,
    endZoneOffset = ZoneOffset.UTC,
    // Create a new record every minute, containing a list of samples.
    samples = listOf(
        HeartRateRecord.Sample(
            time = startTime + Duration.ofSeconds(15),
            beatsPerMinute = 80,
        ),
        HeartRateRecord.Sample(
            time = startTime + Duration.ofSeconds(30),
            beatsPerMinute = 82,
        ),
        HeartRateRecord.Sample(
            time = startTime + Duration.ofSeconds(45),
            beatsPerMinute = 85,
        )
    ),
    metadata = Metadata.autoRecorded(
        device = Device(type = Device.TYPE_WATCH)
    ))

Write data monitored throughout the day

For data collected on an ongoing basis, like steps, your application should write to Health Connect as frequently as possible when new data is available. To avoid negatively impacting battery life and other performance aspects, the maximum interval between writes should be 15 minutes.

Data should be written to Health Connect at the end of the workout or sleep session. For active tracking, such as exercise and sleep, or manual user input like nutrition, these records are created when the app is in the foreground, or in rare events where it is used a few times in a day.

Verify that your app doesn't keep Health Connect running for the entire duration of the event.

Data must be written to Health Connect in one of two ways:

• Sync data to Health Connect after the event is complete. For example, sync data when the user ends a tracked exercise session.
• Schedule a one-off task using WorkManager to sync data later.

Exercise and sleep sessions

At minimum, your application should follow the guidance in the Expected column in Table 2. Where possible, follow the guidance in the Best column.

The following table shows how to write data during an exercise:

Table 3 shows how to write data during or after a sleep session:

Multi-sport events

This approach uses existing data types and structures, and it verifies compatibility with current Health Connect implementations and data readers. This is a common approach taken by fitness platforms.

Additionally, individual sessions such as swimming, biking, and running aren't inherently linked within Health Connect, and data readers must infer the relationship between these sessions based on their time proximity. Transitions between segments, such as from swimming to biking, aren't explicitly represented.

The following example shows how to write data for a triathlon:

val swimStartTime = Instant.parse("2024-08-22T08:00:00Z")
val swimEndTime = Instant.parse("2024-08-22T08:30:00Z")
val bikeStartTime = Instant.parse("2024-08-22T08:40:00Z")
val bikeEndTime = Instant.parse("2024-08-22T09:40:00Z")
val runStartTime = Instant.parse("2024-08-22T09:50:00Z")
val runEndTime = Instant.parse("2024-08-22T10:20:00Z")

val swimSession = ExerciseSessionRecord(
    startTime = swimStartTime,
    endTime = swimEndTime,
    exerciseType = ExerciseSessionRecord.EXERCISE_TYPE_SWIMMING_OPEN_WATER,
    metadata = Metadata.autoRecorded(
      device = Device(type = Device.TYPE_WATCH)
    )
)

val bikeSession = ExerciseSessionRecord(
    startTime = bikeStartTime,
    endTime = bikeEndTime,
    exerciseType = ExerciseSessionRecord.EXERCISE_TYPE_BIKING,
    metadata = Metadata.autoRecorded(
      device = Device(type = Device.TYPE_WATCH)
    )
)

val runSession = ExerciseSessionRecord(
    startTime = runStartTime,
    endTime = runEndTime,
    exerciseType = ExerciseSessionRecord.EXERCISE_TYPE_RUNNING,
    metadata = Metadata.autoRecorded(
      device = Device(type = Device.TYPE_WATCH)
    )
)

healthConnectClient.insertRecords(listOf(swimSession, bikeSession, runSession))

Handle exceptions

Health Connect throws standard exceptions for CRUD operations when an issue is encountered. Your app should catch and handle each of these exceptions as appropriate.

Each method on HealthConnectClient lists the exceptions that can be thrown. In general, your app should handle the following exceptions: