Blood Glucose, Meals and Exercise in One Timeline

A glucose number without its moment is only half a record. Blood Glucose is now part of PlateLens, so a morning meter reading, a dense sensor stream, the meal you logged later and the exercise you actually did can share one truthful timeline without turning PlateLens into a clinical dashboard for everyone else.

The problem was not another input box

People who care about glucose often build the same day twice. Food and nutrition live in one app. A continuous glucose monitor or meter lives in another. Activity may live in the phone's health platform, while a timed exercise may be logged in PlateLens. Supplements may live in notes. Comparing them means switching screens and mentally reconstructing which event came first.

Adding a glucose field would not solve that. The important part is preserving the time of every observation and letting the existing meal and exercise records meet it there. That is why PlateLens first separated when a meal happened from when it was logged, and gave exercise a confirmed start and duration. Blood glucose now uses those same occurrence facts instead of inventing a second timeline.

One observation stays one observation

A finger-stick at 7:00 AM is a point. A reading two hours after dinner is another point. PlateLens does not stretch a line between them and call it a day-long glucose curve. When Apple Health or Health Connect supplies a dense sequence from the same contributing app/source stream and measurement method, PlateLens can connect the observed samples. A gap longer than 20 minutes starts a new segment.

One day when you need detail, a range when you need perspective

The Day chart has a real time axis and glucose scale. Tap, click or drag to select the nearest reading and see its exact value, time, source and measurement method. The legend explains the reading and event marks that are present, while keyboard and screen-reader actions can move through the same observations. The exact chronological ledger remains below the visualization.

The 7-, 30- and 90-day charts answer a different question. Each date shows its observed daily median and lowest-to-highest span; a single-reading day stays one point and a missing day stays a gap. Selecting a date opens the truthful 24-hour detail with its meal and exercise context. The All view remains a complete ledger rather than squeezing an unlimited history into a decorative curve.

Diary adds the same factual view to its exact Week and Month calendars. The current period stops at today, historical periods remain complete, and choosing an observed date opens that day's detail without losing the period you came from.

Context, not a causal verdict

Meals with a confirmed Meal time and exercise with a confirmed start logged in PlateLens appear as markers beside glucose. In the web Diary and Blood Glucose History, the event list beneath the curve also shows each meal's calories and main macros or each exercise's full timed interval, duration and calories. This answers “what else was recorded around then?” It does not answer “what caused this number?” Carbohydrates, activity, sleep, stress, medication, supplements and many other factors can overlap.

PlateLens deliberately does not paint a universal target band, diagnose a spike or award a meal-response score. A nutrition app should make the record easier to understand without pretending to replace a CGM app, a meter or a healthcare professional.

Designed to stay quiet for everyone else

Blood Glucose is not a new medical-looking tab forced onto every new account. The global + menu has one scalable Measurements doorway. Inside it are Blood glucose, Weight and Body measurements. Home hides the glucose card until the account has actually tracked a reading, and Diary only includes it when the exact selected Day, Week or Month contains readings.

After that first reading, Home keeps a compact latest-reading card with its real observation date and time. Diary stays calendar-specific and omits glucose from an empty selected period instead of carrying another day's history into it. Nothing carries yesterday's value forward as today's. This lets PlateLens serve someone monitoring pre-diabetes without making calorie tracking feel like disease management to someone who is not.

What is available across PlateLens

From a timeline to an analysis that admits what it knows

History answers “what was recorded?”. Analysis—inside Blood Glucose on mobile and under Progress on the web—answers a narrower question: “what repeated observations are actually supported by this 7-, 30- or 90-day window?”. It inventories the measurement method supplied with each reading and keeps Unknown explicit instead of guessing. When stored evidence identifies more than one method, it does not blend them into one pattern: the user chooses which group to compare.

Time and logged-context medians give each observed day equal weight and require at least three readings across three days. Meal and timed PlateLens-exercise associations require five unique before/after pairs across three days; they show the full observed change span alongside a day-weighted median. A sparse group stays Limited, an untagged reading stays untagged, and no glucose pair is reused to inflate the evidence count.

Source ownership prevents two truths

A reading entered in PlateLens can be edited or deleted in PlateLens. A reading imported from Apple Health or Health Connect is corrected in its source. On the next sync, PlateLens reconciles the same provider record when the health platform supplies its explicit update or deletion event, rather than knowingly making another copy. An empty or partial history read never proves deletion. Removing health permission stops future access; it does not silently erase history already copied into the PlateLens account.

Internally, every reading is stored in one canonical unit with full precision. PlateLens starts with the convention commonly used in the account country, then keeps the chosen mg/dL or mmol/L preference on the account so mobile, web, Watch and PDF agree. It can be changed in Unit Preferences or directly from the reading form, and changing it never rewrites the underlying observation.

The beginning of a more complete day

Blood glucose solves the first high-value version of the broader request: see observed health data in the same temporal context as food and movement. Supplements and medication deserve equally careful modeling—recurring stacks, dose identity, source data and safety boundaries—not a rushed reuse of the meal database. The Measurements doorway and occurrence architecture leave room for those additions without promising them before they are designed.