Concept · /readiness
Fire your readiness score.
Oura / WHOOP mash noisy wrist signals into a mystery grade. Here’s raw nocturnal RMSSD + resting HR vs your baseline — demo data only.
Example data · not your wearable
PPG pulse-rate variability, skin temp, sleep staging, and training load mashed into opaque weights. One night moves the number; you can’t audit why.
Nocturnal RMSSD and resting HR against your multi-week range. Hydration sessions as visible confounders. What changed — not a grade.
What the devices actually measure
A score is not a signal.
Most consumer wearables estimate pulse-rate variability (PRV) from photoplethysmography — light through the skin — not ECG-grade heart-rate variability. Raw nocturnal RMSSD and resting heart rate can be useful only as personal multi-week baselines, not as single-day diagnostic readings.
-
01
Proprietary readiness compounds noise Opaque weights on noisy inputs. No validated meaning for hard health outcomes. Easy to create orthosomnia — anxiety about imperfect sleep scores — and a digital nocebo when the number dips.
-
02
One night is mostly weather Alcohol, a late meal, heat, hard training, illness, and measurement error all move a single night. Treating it as a verdict is the product talking, not the physiology.
-
03
Useful = sustained co-shifts Multi-day movement across raw nocturnal RMSSD, resting HR, skin temperature, symptoms, training load, and hydration context. Patterns over days — not a morning color.
We will not claim
Interactive demo · labeled example only
What changed — not what you “are.”
Toggle confounders on a 28-day example baseline. The readout never grades you. It names the state, lists plausible confounders, and offers one practical next action. Hydration sessions from SweatSciences sit in the chart as context — not as the claimed cause.
Example athlete · 28-day window
Demo dataAnnotate confounders (example week)
Sessions are overlays, not verdicts. A big sodium day next to a noisy night is a reason to check replacement and fluid — not proof that hydration “caused” the RMSSD dip.
Product stance
Mystery grade vs. honest inputs.
| Wearable readiness | SweatSciences context | |
|---|---|---|
| Output | Single composite score | What changed + confounders + one action |
| Signal | PRV / PPG, often unlabeled as such | Raw nocturnal RMSSD & resting HR vs your baseline |
| Horizon | Often overnight → morning grade | Multi-week baseline; multi-day co-shifts |
| Hydration | Usually invisible or guessed | Your saved sweat sessions as explicit context |
| Model | Opaque weights, product lock-in | No proprietary score. Do the math locally. |
Privacy · architecture
Bring the data. Keep the score dead.
Three steps. Analyze as privately as the platform allows. Never invent a readiness brand on top of your export.
Bring the export
Apple Health export, or paste raw nocturnal RMSSD, resting HR, and optional skin temp. Your file, your paste — not a partner API that owns the relationship.
Analyze locally
Baselines and co-shift checks run in-browser or on-device where possible. Sessions already save locally today. Prefer private compute over “upload for insights.”
No proprietary score
Output is range / noisy night / multi-day co-shift — plain language. If we can’t show the inputs, we don’t ship the claim.
Next move
Know exactly what to drink.
Then read your week honestly.
Start with your sweat number. Save sessions on-device. When the readiness page ships, it’ll sit on top of that history — not replace it with a grade.
Educational tool concept — not medical advice. If you have cardiac or kidney conditions, high blood pressure, or are pregnant, talk to a clinician before changing training or sodium intake based on wearable trends.