Apple Health

Apple Health insights need baselines, context and confidence.

daygauge reads selected Apple Health sleep, movement and recovery summaries after permission, then shows what helped, what held the day back and what to try next.

See the product loop See Pro pricing See score anatomy

Why people search this

Apple Health becomes useful when the app explains the day around it.

Apple Health contains useful summaries, but a dashboard still leaves the pattern work to the user.

daygauge turns authorised Apple Health signals into score evidence, pattern notes and weekly attribution while keeping sensitive sources opt-in.

Quick answer

daygauge reads authorised Apple Health summaries such as sleep, steps, active energy, resting heart rate and HRV where available.

Search questions answered

What this page covers.

What Apple Health data can an app use?
How can Apple Health data affect a lifestyle score?
Does daygauge write to Apple Health?
How are Apple Health permissions explained?
What happens if a user declines a permission?

How daygauge would use this

From research context to product evidence.

Signal

daygauge reads authorised Apple Health summaries such as sleep, steps, active energy, resting heart rate and HRV where available.Environmental sound and headphone exposure are optional context sources. They stay separate from diagnosis, treatment and health-risk prediction.

Confidence

Missing or sensitive data lowers confidence instead of creating false certainty.If the signal is not measured, explicitly imported or user-approved, daygauge should say so in the evidence.

Weekly review

Pro keeps the weekly baseline review: what changed, what moved with it, and whether the pattern repeated.This is where daygauge has to beat a generic wearable dashboard: clearer explanation, baselines and boundaries.

Example evidence

What a user should expect to see in the app.

Sleep evidence: 6h 52m from Apple Health, 38 minutes below personal baseline, medium confidence.

Weekly review preview

Data used

Authorised Apple Health sleep, steps, active energy, resting heart rate and HRV where available.

Confidence

Confidence rises when the same pattern repeats against your own baseline and drops when key signals are missing.

Next move

daygauge would suggest one small experiment, then watch whether the evidence repeats over the next week.

Boundary

Research context only. daygauge does not diagnose, treat, prevent or predict disease risk. Personal medical concerns belong with a qualified clinician.

Evidence 1

Sleep evidence: 6h 52m from Apple Health, 38 minutes below personal baseline, medium confidence.

Evidence 2

Movement evidence: steps 22% above 14-day average, high confidence.

Evidence 3

Noise evidence: optional headphone exposure imported, compared with sleep and focus patterns only.

Safety line

Research context only. daygauge does not diagnose, treat, prevent or predict disease risk. Personal medical concerns belong with a qualified clinician.

Research context

Sources daygauge can cite without overclaiming.

These sources are used as context for product wording and evidence labels. They should not be turned into personal disease-risk estimates.

Research context only. daygauge does not diagnose, treat, prevent or predict disease risk. Personal medical concerns belong with a qualified clinician.

Product boundaries

What daygauge should not claim.

No diagnosis, treatment, prevention or personal disease-risk prediction.
No hidden inference from sensitive data such as fertility, hormones, glucose, labs, cycle context or exposure tests.
No guilt language, food moralising, overtraining incentives or leaderboard use for sensitive topics.
No claim that a single habit caused a result. daygauge can show patterns, confidence and possible confounders.

Related daygauge guides.

Early access

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Paid app, one plan · evidence context, not medical advice