How Sleepgenic reads
wearable sleep data.
Sleepgenic translates wearable sleep data into longitudinal human meaning through a structured methodology: continuous Garmin tracking, a named three-layer interpretation model (Score × Physiology × Context), an immutable nightly source layer, explicit previous-day stimulus semantics, formula-driven derived signals, rolling personal baselines, and auditable quality control. Eight components, every transformation disclosed.
components
interpretation model
per TrailGenic Biomarkers
From wearable output to longitudinal human meaning.
Sleepgenic interprets each night through three linked views. No single score is treated as the answer, and no missing night is treated as a zero. The method is personal, longitudinal, and explicit about what the device did not observe.
Instrumentation.
Garmin Enduro 3 — continuous nightly tracking. Detailed Sleep Tracking enabled, Pulse-Ox toggle on, high-frequency HRV and respiration sampling. Charging happens during work blocks (Mon–Fri daytime), never overnight.
Automatic, physiology-driven sleep onset and wake detection — movement, heart rate, respiratory pattern. Sleep Schedule target window set to 10:00pm–6:30am Pacific. The schedule setting affects only contextual feedback tags such as LATE_BED_TIME; it does not gate or window underlying tracking.
Garmin Connect nightly records are assembled into the canonical Raw Nights layer. Source values remain unchanged; normalization, reconciliation, and corrections occur only in separate auditable layers, with every conflict retained in the QC Log.
All source timestamps remain preserved in GMT. Canonical v1 does not silently convert them to Pacific time. Local bedtime analysis requires an explicit time-zone and location join, especially during travel and altitude periods.
Nightly record fields.
Each calendar date receives a canonical row, including scored nights, explicit missing nights, absent dates, time-only records, and nap-only records. Raw Nights governs all sleep measurements. Reports are versioned analytical outputs recalculated from the nightly source rather than manually stored weekly aggregates.
| Variable | Type | Purpose |
|---|---|---|
| Sleep Date | Temporal | Canonical response key; links the night to Previous Day Date and versioned reports |
| Sleep Start / End (GMT) | Temporal | Onset and wake timestamps; sleep window duration and timing analysis |
| Overall Score | Composite | Garmin's global sleep quality rating (0–100) |
| Quality / Recovery / Duration Sub-scores | Composite | Garmin's three-component decomposition of overall score |
| Deep / REM / Light / Awake (min) | Architecture | Sleep stage durations; consumer-grade approximation of stage proportions |
| Total Sleep (hrs) | Architecture | Total tracked sleep duration; debt and surplus context |
| Avg / Lowest SpO2 (%) | Respiratory | Nocturnal oxygen saturation; altitude and breathing-disruption signal |
| Avg HR (bpm) | Cardiovascular | Sleeping heart rate; recovery and autonomic state signal |
| Avg / Low / High Resp (rpm) | Respiratory | Respiratory rate and variability; recovery and stress signal |
| Sleep Stress | Composite | Garmin-derived autonomic load during sleep window |
| Restless Moments / Awake Count | Architecture | Fragmentation signal; continuity vs disruption analysis |
| Breathing Disruption | Respiratory | Garmin's NONE/LOW respiratory irregularity flag |
| Feedback / Insight Tags | Categorical | Garmin's POSITIVE_/NEGATIVE_ tags; tag-frequency longitudinal analysis |
| Previous-Day Stimulus | Context | Activity on Sleep Date minus one day — Walk, Running, Rucking, Hiking, Rest, or Recovery; original and normalized labels are both preserved |
Score Layer × Physiology Layer × Context Layer.
Read separately. Read against each other.
Most wearable interpretation collapses three layers into a single verdict — one score, one judgment. Sleepgenic separates them. Each measurement is read at three levels: what the wearable reported, what the body appears to be doing underneath, and what happened in real life around the sleep window. When the three layers agree, interpretation is straightforward. When they disagree, the meaning lives in the gap. This named interpretive framework operates across every versioned Report and every Sleep Interpretation Library article.
Score Layer. What the wearable reports. Sleep score, recovery score, sleep stress, body battery — the headline number on the screen, before any interpretation. The starting point, not the verdict.
Physiology Layer. What the body appears to be doing underneath. HRV, resting heart rate, deep sleep, REM, breathing patterns. The signals the score is built from — and the layer that often disagrees with the score itself.
Context Layer. What happened in real life around the sleep window. Training stimulus, illness, alcohol, jet lag, ambient temperature, emotional load. The variables that determine whether a number is good news, bad news, or noise.
The three layers are read first separately, then against each other. Disagreement is the most informative state — a low Score Layer with a strong Physiology Layer reconciled by a hard-training Context Layer is a different reading than a low score across all three. Recovery-and-readiness apps cannot operate this model; they treat sleep as one variable inside a five-variable training-recovery system. Sleepgenic is sleep-only, at depth they cannot match.
Source-reported sleep signals
— preserved fields.
Fields supplied directly by the Garmin source, including physiological estimates and Garmin-proprietary composite scores. “Source-reported” identifies lineage; it does not imply clinical measurement or algorithmic transparency.
Derived sleep signals
— formula-driven and auditable.
Canonical v1 derives only fields whose formulas and thresholds are visible in the workbook. It does not publish uncalculated composites as established measurements.
Previous-day stimulus,
dose, and context.
Sleepgenic treats the night as a response and the preceding calendar day as the exposure window. Context is observed rather than experimentally controlled, so modality-level findings remain descriptive until dose and environmental joins are complete.
Previous-Day Stimulus. Original source label plus a normalized category: Walk, Running, Rucking, Hiking, or Rest/Recovery. Sleep Date minus one day is the exposure key.
Training Dose. Duration, exercise load, distance, ascent, intensity, and peak elevation are prepared as structured fields. Canonical v1 marks this TrailGenic join as pending rather than treating every activity in a modality as equivalent.
Altitude and Travel. Peak elevation, sleeping elevation, travel status, and location are required to distinguish ordinary training from hypoxic or travel-related strain.
Time Zone and Location. GMT timestamps remain source-preserved. Local timing is not inferred during road trips; it will be calculated only after an explicit location and time-zone join.
Acute and Accumulated Load. A single prior-day stimulus may interact with consecutive efforts and recent recovery history. Dose-response interpretation waits for the detailed training join.
Known Confounders. Caffeine, hydration, alcohol, illness, meals, heat, bedroom environment, and emotional load are documented when available. They are not presumed controlled.
Population benchmarks
vs Sleepgenic.
Population sleep norms vs Sleepgenic measurements, anchored to the adults aged 50+ reference cohort to match the subject's demographic. Sleepgenic values shown are historical baseline medians (Nov 23, 2025 – Apr 17, 2026; 80 scored nightly records plus one time-only partial record), the stable reference layer. Versioned longitudinal results are published in Reports and interpreted in the Sleep Interpretation Library.
| Sleep Metric | Population (50+) | Sleepgenic (Mike) | Interpretation |
|---|---|---|---|
| Total Sleep | 6.0–7.5 hrs1,2 | 5.99 hrs | ~30 min below cohort median; chronic mild restriction |
| Sleep Score | 66 avg, age 50–593 | 67.5 | At cohort mean; mid-Fair band |
| Deep Sleep % | 10–18% TST1,4 | 20.9% | Above cohort range; wearables overestimate deep sleep vs PSG |
| REM Sleep % | 18–22% TST1,2 | 13.6% | Below cohort range; consistent with REM compression under short sleep |
| Sleeping HR | 57–90 bpm; mean 735 | 65.0 bpm | Below cohort mean; lower-middle of healthy range |
| Nocturnal HRV (RMSSD) | 19–24 ms median, 50+ men (short-term ECG)6 | 35.0 ms (overnight wearable) | Above cohort baseline even after wearable-vs-ECG calibration; see note below |
| Restless Moments | Garmin proxy; no clinical equivalent | 44.0 | Garmin-internal fragmentation signal; trended longitudinally |
| Respiratory Rate | 12–20 rpm; mean ~15.47 | 16.52 rpm median | 80 scored baseline nights with respiration available |
| Avg SpO2 | 95–100% | 96.0% median | 55 scored baseline nights with SpO2 available |
A note on wearable vs clinical measurement. Population HRV values above are drawn from short-term resting electrocardiogram (Tegegne et al., n=84,772). Garmin overnight RMSSD averages many hours of measurement during parasympathetic-dominant sleep states, which structurally produces higher values than waking ECG — typically by 30–50% in healthy individuals. This is calibration, not error. Sleepgenic reads each measurement against its own methodology, and reports population values in their original measurement frame so the gap is visible rather than hidden. The same caution applies to wearable sleep stage classification, which agrees with polysomnography roughly 65–75% of the time and tends to overestimate deep sleep relative to gold-standard scoring.
The Sleepgenic baseline values now reconcile directly to the nightly canonical source. Canonical v1 spans 269 calendar rows through August 18, 2026, including 182 scored sleep episodes and 97 stimulus-linked scored nights. Longitudinal deviations use prior-night rolling 28-day personal baselines rather than copied weekly aggregates.
- Mitterling T, Högl B, Schönwald SV, et al. Sleep and respiration in 100 healthy Caucasian sleepers — a polysomnographic study according to AASM standards. Sleep. 2015;38(6):867–875.
- Ohayon MM, Carskadon MA, Guilleminault C, Vitiello MV. Meta-analysis of quantitative sleep parameters from childhood to old age in healthy individuals. Sleep. 2004;27(7):1255–1273.
- Garmin Connect aggregate user data, 2023–2024 reports. Age 50–59 cohort average sleep score: 66.
- Li J, Vitiello MV, Gooneratne N. Sleep in Normal Aging. Sleep Med Clin. 2018;13(1):1–11.
- Engdahl J, et al. Reference ranges for ambulatory heart rate measurements in a middle-aged population (SCAPIS, n=3,942 healthy adults aged 50–65). 2024.
- Tegegne BS, Man T, van Roon AM, Snieder H, Riese H. Reference values of heart rate variability from 10-second resting electrocardiograms: the Lifelines Cohort Study (n=84,772). Eur J Prev Cardiol. 2020;27(19):2191–2194.
- American Academy of Sleep Medicine clinical reference ranges; pooled wearable validation studies (WHOOP, Oura, Garmin) within ±1 brpm of polysomnography.
Analytical framework.
Each versioned report is interpreted by Ella — Sleepgenic's reflective AI analytical layer — operating the Three-Layer Interpretation Model against the canonical nightly dataset, prior 28-day personal baselines, stimulus-linked descriptive results, and the population benchmarks above. The same method extends to every Sleep Interpretation Library article: same three layers, same separation, same disagreement-as-signal logic.
The framework documents what the wearable data shows, against what the design supports, with the limitations stated openly. It does not predict, diagnose, or prescribe. Sleep meaning, not training prescription.
What this methodology
cannot show.
Methodological honesty is the differentiator. Every limit below is real. Every report is read against this list.
Wearable measurement noise. Consumer-grade sleep stage classification is approximate. Deep, REM, and light boundaries are inferred from movement, heart rate, and respiration — not direct EEG. Stage durations should be read as estimates, not measurements.
n=1 does not generalize. This is one person's longitudinal response. Patterns may resemble what's reported in population studies, or may not. Findings cannot be applied to other people without their own data.
Confounding is unavoidable. This is an observational real-world record, not a randomized or controlled experiment. Training dose, terrain, altitude, travel, timing, caffeine, stress, hydration, ambient temperature, alcohol, illness, and other variables may overlap.
Garmin's algorithms are proprietary. The sleep score, sub-scores, and feedback tags are produced by closed algorithms that may change over time. Sleepgenic interprets the outputs as Garmin reports them and notes meaningful algorithm changes when known.
Not medical advice. Sleepgenic publishes research and interpretation. It does not diagnose, prescribe, or treat. Anyone with a clinical sleep concern should see a licensed clinician.
The methodology evolves. Interpretation Articles and versioned Reports will surface limits this document doesn't yet name. When that happens, the methodology is updated and the date is revised. The current version is always live.
The Sleepgenic Dataset.
Open methodology.
The Sleepgenic Dataset is a longitudinal field research record of consumer wearable sleep data, tracked using standardized instrumentation and consistent analytical protocol across all entries. Mirrors the TrailGenic Physiology Dataset structure with sleep architecture and recovery response as primary outcome.
For research partnerships, data licensing, or academic access inquiries:
- 01 — Instrumentation
- 02 — Nightly record fields
- 03 — Three-Layer Interpretation Model
- 04 — Direct signals
- 05 — Derived signals
- 06 — Environmental & stimulus load
- 07 — Population benchmarks
- 08 — Analytical framework
- Last updated: August 18, 2026