Future Export Metrics

Purpose

This document captures candidate Apple Health export metrics for future enhancement work.

The current app exports:

  • Weight (HKQuantityTypeIdentifierBodyMass)
  • Steps (HKQuantityTypeIdentifierStepCount)
  • Blood Glucose (HKQuantityTypeIdentifierBloodGlucose)
  • Hemoglobin A1C (HKClinicalTypeIdentifierLabResultRecord, filtered to LOINC 4548-4)

The list below is based on a review of a full Apple Health export dump from a real iPhone backup (~/Dropbox/apple_health_export). The goal is to prioritize exports that are both useful to users and compatible with the app’s CSV-first workflow.

Data snapshot from the sampled export

Notable counts from the reviewed dump:

  • Active Energy Burned: 1,797,912 records
  • Heart Rate: 1,041,445 records
  • Distance Walking/Running: 538,972 records
  • Step Count: 496,510 records
  • Blood Glucose: 262,751 records
  • Apple Exercise Time: 155,343 records
  • Apple Stand Time: 124,718 records
  • Sleep Analysis: 4,327 records
  • Heart Rate Variability (SDNN): 14,509 records
  • Oxygen Saturation: 9,981 records
  • Respiratory Rate: 3,942 records
  • Resting Heart Rate: 2,517 records
  • Walking Heart Rate Average: 2,461 records
  • Body Mass: 2,164 records
  • Body Fat Percentage: 993 records
  • Lean Body Mass: 722 records
  • VO2 Max: 548 records
  • Workouts: 3,638 records

The dump also contains:

  • Clinical records, including document references, conditions, allergies, and diagnostic reports
  • Electrocardiogram CSV files
  • Workout route GPX files

Candidate metrics by theme

Cardio and recovery

Strong near-term candidates with broad user appeal:

  • Heart Rate (HKQuantityTypeIdentifierHeartRate)
  • Resting Heart Rate (HKQuantityTypeIdentifierRestingHeartRate)
  • Walking Heart Rate Average (HKQuantityTypeIdentifierWalkingHeartRateAverage)
  • Heart Rate Variability (SDNN) (HKQuantityTypeIdentifierHeartRateVariabilitySDNN)
  • Respiratory Rate (HKQuantityTypeIdentifierRespiratoryRate)
  • Oxygen Saturation (HKQuantityTypeIdentifierOxygenSaturation)
  • VO2 Max (HKQuantityTypeIdentifierVO2Max)
  • Heart Rate Recovery (HKQuantityTypeIdentifierHeartRateRecoveryOneMinute)

Why this theme matters:

  • High user value for fitness, recovery, illness tracking, and trend analysis
  • Clean fit with the current timestamped-sample CSV model
  • Present in meaningful volume in the sampled export

Sleep and overnight health

  • Sleep Analysis (HKCategoryTypeIdentifierSleepAnalysis)
  • Respiratory Rate during sleep (HKQuantityTypeIdentifierRespiratoryRate)
  • Oxygen Saturation during sleep (HKQuantityTypeIdentifierOxygenSaturation)

Why:

  • Sleep is a widely understandable export category
  • Basic sleep-session export is valuable even without complex sleep-stage analysis
  • Pairs naturally with cardio and recovery metrics

Activity rings and movement

  • Active Energy Burned (HKQuantityTypeIdentifierActiveEnergyBurned)
  • Basal Energy Burned (HKQuantityTypeIdentifierBasalEnergyBurned)
  • Apple Exercise Time (HKQuantityTypeIdentifierAppleExerciseTime)
  • Apple Stand Time (HKQuantityTypeIdentifierAppleStandTime)
  • Apple Stand Hour (HKCategoryTypeIdentifierAppleStandHour)
  • Distance Walking/Running (HKQuantityTypeIdentifierDistanceWalkingRunning)
  • Flights Climbed (HKQuantityTypeIdentifierFlightsClimbed)
  • Time in Daylight (HKQuantityTypeIdentifierTimeInDaylight)

Why:

  • These are core Apple Watch metrics users already recognize
  • They provide useful longitudinal analysis outside the Apple Health UI
  • They complement steps rather than duplicating it

Body composition

  • Body Mass Index (HKQuantityTypeIdentifierBodyMassIndex)
  • Body Fat Percentage (HKQuantityTypeIdentifierBodyFatPercentage)
  • Lean Body Mass (HKQuantityTypeIdentifierLeanBodyMass)

Why:

  • Good fit with the current weight and glucose audience
  • Lower implementation risk than more specialized performance metrics
  • Useful in spreadsheets and BI tools

Mobility and gait

  • Walking Speed (HKQuantityTypeIdentifierWalkingSpeed)
  • Walking Step Length (HKQuantityTypeIdentifierWalkingStepLength)
  • Walking Asymmetry Percentage (HKQuantityTypeIdentifierWalkingAsymmetryPercentage)
  • Walking Double Support Percentage (HKQuantityTypeIdentifierWalkingDoubleSupportPercentage)
  • Apple Walking Steadiness (HKQuantityTypeIdentifierAppleWalkingSteadiness)
  • Six-Minute Walk Test Distance (HKQuantityTypeIdentifierSixMinuteWalkTestDistance)
  • Stair Ascent Speed (HKQuantityTypeIdentifierStairAscentSpeed)
  • Stair Descent Speed (HKQuantityTypeIdentifierStairDescentSpeed)

Why:

  • Valuable for aging, rehab, fall-risk, and general mobility tracking
  • Distinctive HealthKit metrics that are not easy to extract elsewhere
  • Best treated as a dedicated theme in the product

Workout summaries

Rather than only exporting raw samples, support workout-level exports such as:

  • Workout records (<Workout ...>)
  • Start time
  • End time
  • Duration
  • Total energy burned
  • Total distance
  • Source

Possible follow-ons:

  • Workout route linkage
  • Swimming workout summaries
  • Per-workout average heart rate or pace if derivable cleanly

Why:

  • The sampled export contains 3,638 workouts
  • Workout summaries are easier to use than very high-frequency workout-adjacent sample streams
  • This is a natural extension of the CSV export model

Cycling and training performance

  • Cycling Speed (HKQuantityTypeIdentifierCyclingSpeed)
  • Cycling Cadence (HKQuantityTypeIdentifierCyclingCadence)
  • Cycling Power (HKQuantityTypeIdentifierCyclingPower)
  • Cycling Functional Threshold Power (HKQuantityTypeIdentifierCyclingFunctionalThresholdPower)
  • Distance Cycling (HKQuantityTypeIdentifierDistanceCycling)
  • Physical Effort (HKQuantityTypeIdentifierPhysicalEffort)

Why:

  • Clearly present in the sampled export
  • Relevant for advanced Apple Watch and bike computer users
  • Better framed as an advanced/performance theme because record volume is high and aggregation may need more design

Hearing and environmental exposure

  • Headphone Audio Exposure (HKQuantityTypeIdentifierHeadphoneAudioExposure)
  • Environmental Audio Exposure (HKQuantityTypeIdentifierEnvironmentalAudioExposure)
  • Audio Exposure Events (HKCategoryTypeIdentifierAudioExposureEvent)
  • Environmental Sound Reduction (HKQuantityTypeIdentifierEnvironmentalSoundReduction)

Why:

  • Distinctive Apple ecosystem data
  • Useful for hearing-health and lifestyle analysis
  • Differentiates the app from more basic Health exporters

Nutrition

Potentially useful, but likely not first-wave:

  • Dietary Energy Consumed (HKQuantityTypeIdentifierDietaryEnergyConsumed)
  • Carbohydrates (HKQuantityTypeIdentifierDietaryCarbohydrates)
  • Protein (HKQuantityTypeIdentifierDietaryProtein)
  • Total Fat (HKQuantityTypeIdentifierDietaryFatTotal)
  • Fiber (HKQuantityTypeIdentifierDietaryFiber)
  • Sugar (HKQuantityTypeIdentifierDietarySugar)
  • Sodium (HKQuantityTypeIdentifierDietarySodium)
  • Potassium (HKQuantityTypeIdentifierDietaryPotassium)
  • Cholesterol (HKQuantityTypeIdentifierDietaryCholesterol)

Why later:

  • Present in the sampled dump, but at much lower frequency
  • Nutrition tends to expand into a much broader feature surface once started
  • Better handled as an intentional theme than an isolated metric addition

Clinical records and file-backed exports

Beyond A1C, the sampled export includes:

  • Diagnostic reports (<ClinicalRecord type="DiagnosticReport" ...>)
  • Conditions (<ClinicalRecord type="Condition" ...>)
  • Allergies (<ClinicalRecord type="AllergyIntolerance" ...>)
  • Document references (<ClinicalRecord type="DocumentReference" ...>)
  • ECG files (electrocardiograms/ecg_*.csv)
  • Workout route files (workout-routes/route_*.gpx)

Potential future directions:

  • Generic lab-result export from clinical records
  • Diagnostic report metadata export
  • Condition and allergy metadata export
  • ECG discovery/export
  • Workout route export

Why this is later-stage:

  • These are not simple quantity samples
  • They likely need a separate export model and file-handling workflow
  • Still worth tracking because they would materially broaden the product

Suggested prioritization

Near-term

  • Heart Rate
  • Resting Heart Rate
  • Heart Rate Variability (SDNN)
  • Sleep Analysis
  • Active Energy Burned
  • Apple Exercise Time
  • Distance Walking/Running
  • Oxygen Saturation
  • Respiratory Rate
  • Workout summaries
  • Body Fat Percentage

Mid-term

  • Walking Heart Rate Average
  • VO2 Max
  • Flights Climbed
  • Apple Stand Time and Apple Stand Hour
  • Body Mass Index
  • Lean Body Mass
  • Mobility and gait metrics
  • Hearing and environmental exposure metrics

Later

  • Cycling and training performance metrics
  • Nutrition
  • Generic clinical-record export
  • ECG and workout-route export workflows

Implementation notes

  • Keep new metric routing centralized in HealthMetricConfig.swift.
  • Add dedicated unit handling where needed:
    • heart rate: count/min
    • oxygen saturation: percent
    • energy: kcal
    • distance: metric or imperial
  • Workouts, ECGs, routes, and clinical records should not be forced into the same path as simple HKQuantitySample exports without design review.
  • High-frequency metrics like heart rate, cycling speed, and cadence need extra memory scrutiny and may need stricter date-range controls.

Open product question

Should the app stay focused on flat CSV export of point-in-time health metrics, or should it also expand into richer exports for workouts, ECGs, routes, and clinical documents?