2026 Sleep Analytics

Cardiac Interpretation: Your average nocturnal dip of 19.1% classifies you as a standard dipper — normal cardioprotective nocturnal BP and HR reduction. Sleep HR of 66 bpm is within normal range.

Weekly Pattern Interpretation: The weekend vs weekday duration difference of 0h 27m of weekend recovery sleep is a compensatory mechanism for accumulated weekday sleep debt. While beneficial short-term, regular over-sleeping on weekends indicates chronic sleep restriction during the week. The day-of-week pattern reveals whether your sleep is schedule-driven (workplace constraint) or biologically regulated.

Records Context: Extreme values in biometric data provide the physiological ceiling and floor of your sleep system. The gap between your best and worst night reveals systemic variability — high variation suggests sensitivity to lifestyle inputs (alcohol, stress, travel), while narrow ranges indicate a well-regulated autonomic system. Tracking records over time allows detection of positive adaptation (best nights improving) or regression (worst nights worsening). From 127 nights, these 17 records span your complete 2026 physiological range to date.

Correlation Interpretation: Pearson r values range from −1 (perfect inverse) to +1 (perfect direct relationship). In biological systems, |r| > 0.5 is considered moderate-strong. The most clinically significant finding here is the duration–HRV relationship (r=0.19) — suggesting sleep quantity modulates autonomic recovery capacity. Correlation does not imply causation; confounding variables (exercise, stress, alcohol) influence all metrics simultaneously.

Calendar Reading Guide: Each square represents one night. Green = optimal, Red = suboptimal. Look for horizontal streaks (multi-night disruption arcs), weekend vs weekday colour differences (social jetlag), and month-to-month colour density shifts (seasonal trends). The calendar view often reveals patterns invisible in standard line charts — such as consistent Friday night sleep disruption, or month-long recovery plateaus.

Methodology: Hypnograms are modelled reconstructions, not sensor-verified PSG recordings. N3 (deep sleep) distribution uses empirical front-loading weights from Rechtschaffen & Kales sleep architecture norms: ~40% of total SWS in cycle 1, ~30% in cycle 2, ~20% in cycle 3, ~10% in cycle 4. REM is back-loaded inversely. Wake periods are distributed randomly proportional to reported awake minutes. True stage identification requires EEG — use this as a structural estimate, not a clinical measure.

Ultradian Biology: Sleep unfolds in ~90-minute cycles of NREM → REM. Deep sleep (N3/SWS) dominates early cycles — typically 30–40 min in cycles 1–2, declining to near-zero by cycle 4–5. REM sleep does the opposite, expanding from ~5 min early to 30+ min in the final cycle. Waking at the end of a REM cycle (cycle boundary) produces significantly less grogginess than waking mid-N2 or during N3. Optimizing wake time to fall at cycle boundaries is one of the most underutilised sleep hacks.

Two-Process Model (Borbély 1982, Achermann 2004): Sleep timing is governed by the interaction of two processes. Process S — homeostatic sleep pressure — builds exponentially during wakefulness (τ ≈ 18.2h) and dissipates during sleep (τ ≈ 4.2h). Process C — the circadian pacemaker in the SCN — oscillates with a ~24h period, promoting alertness during the day and permitting sleep at night. The "sleep gate" opens when Process S exceeds the upper threshold of Process C. This model accurately predicts why going to bed 2 hours early is ineffective (S hasn't built sufficiently), why total sleep deprivation accelerates sleep onset the following night (S is abnormally elevated), and why the post-lunch dip in alertness occurs (C dips transiently at ~14:00).

Spectral Interpretation: A dominant 7-day cycle in sleep duration is universal — it reflects social zeitgebers (work/rest schedule) overriding the body's intrinsic ~24h circadian rhythm. Strong 7-day power with a significant autocorrelation at lag-7 confirms weekly social entrainment. Biweekly (14-day) peaks may indicate bi-weekly travel, training blocks, or hormonal cycles. The absence of strong periodicity in HRV relative to sleep duration suggests autonomic recovery operates on faster timescales than social scheduling. Significant autocorrelation at short lags (1–3 days) indicates sleep rebound effects — poor nights predict better subsequent nights, and vice versa.