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TrailGenic / Sleep & recovery research

Your sleep has a story.
Read the pattern.

Sleepgenic translates wearable sleep data into longitudinal human meaning. Explore the scores, physiology, and real-world context behind recovery.

Explore the reports Read our methodology
14 published reports13 interpretations19 defined termsOpen methods. Disclosed limits.

The longitudinal record

Follow the recovery story.

All reports ↗
Field report 01

Food-to-Sleep Pilot — September 2026 Interim Report

Ten observed sleep outcomes paired with real-world dinner, meal-timing, alcohol, and activity context. The strongest early signal is an alcohol-associated perturbation, while food-specific and timing-specific conclusions remain premature.

Read report Field report 02

Week 12 — July 11–17, 2026

Week 12 recorded a full seven-night recovery rebound after the Triple Summit trip. Overall Score rose to 74.4, Recovery Score to 80.3, REM to 1.21 hours, total sleep to 7.55 hours, resting heart rate improved to 63.1 bpm, Sleep Stress fell to 15.8, and SpO2 returned to 95.4%. HRV remained slightly below baseline at 33.6 ms and restlessness stayed elevated. Sleepgenic classifies Week 12 as systemic rebound with residual autonomic and fragmentation lag.

Read report Field report 03

Week 11 — July 4–10, 2026

Week 11 captured the Wheeler Peak and return-travel phase with only four of seven nights observed. Total sleep averaged 8.67 hours and Duration Score 84.0, yet Overall Score averaged 50.3, Recovery Score 52.8, resting heart rate 70.0 bpm, and Sleep Stress 27.7. The post-Wheeler night showed 8.85 hours of sleep but a Recovery Score of 12. Sleepgenic classifies Week 11 as the accumulated-load trough under incomplete coverage, with early recovery appearing late in the week.

Read report

Beyond the morning number

Make sense of your signals.

The interpretation library ↗
Interpretation 01

Can a Sleep Tracker Detect Sleep Apnea?

Consumer wearables can raise a useful question about sleep-disordered breathing, but they cannot answer it. Sleepgenic separates a wearable flag from a clinical finding and explains when repeated SpO₂, respiration, fragmentation, or daytime-symptom patterns should move from interpretation to professional evaluation.

Read interpretation Interpretation 02

Does Hiking Affect Sleep Differently From Walking, Rucking, and Running?

Sleepgenic canonical v1 compares 54 active-stimulus-linked scored nights—14 Walk, 11 Running, 10 Rucking, and 19 Hiking—plus 43 Rest/Recovery reference nights from April 18 through August 14, 2026. Hiking remained associated with longer sleep and the clearest recovery-strain signature, but the pending training-dose join prevents causal or modality-only conclusions.

Read interpretation Interpretation 03

How Accurate Are Deep and REM Sleep on Wearables?

Deep and REM values from wearables are estimates inferred from movement and cardiovascular signals rather than direct brain-wave measurement. Sleepgenic explains why stage error is device-specific, why one night should not be overread, and how a stable-device longitudinal baseline makes imperfect stage data useful.

Read interpretation

About the research

Sleep Research · The Sister-Property Mirror

Sleepgenic translates
wearable sleep data
into longitudinal
human meaning.

The dedicated sleep research arm of TrailGenic — translating consumer wearable scores, sleep architecture, and recovery physiology through a longitudinal n=1 method. Tracking gaps are disclosed. No paywalls, no gates, no commerce.

Read the Methodology Latest Dataset Report →
77
Observed nights · Apr 18–Jul 17
84.6%
Calendar coverage · gaps disclosed
Open
Machine-readable · no imputation
Active Dataset · Updated July 21, 2026
77 observed nights across a 91-night calendar window.
84.6% calendar coverage from April 18 through July 17, 2026. Fourteen nights are unobserved, including seven explicitly labeled forgotten-watch nights and the unrepresented May 23–29 interval. Missing observations are not treated as zero and are not imputed. Weekly means use available recorded nights.
The Other Half of the Story

Where TrailGenic Physiology
documents cardiovascular and metabolic
adaptation, Sleepgenic documents
sleep architecture and recovery.

01

TrailGenic Physiology tracks heart rate, drift, ketones, training effect, and metabolic adaptation across 20+ structured field sessions. The cardiovascular side of the same body's response to load.

02

TrailGenic Biomarkers formalizes the field signal taxonomy — direct signals, derived signals, environmental load factors, population benchmarks. The methodological architecture Sleepgenic mirrors exactly.

03

Sleepgenic is the same architecture applied to sleep — sleep score, HRV trajectory, stage architecture, breathing disruption, training-stimulus response. Same researcher. Same discipline. Different primary outcome.

04

Together, these are two halves of the same physiological story. Cardiovascular adaptation and sleep recovery are not separate phenomena — they are the same n=1 dataset read through two complementary lenses.

The Gap

Hundreds of millions of people
wear sleep trackers. Almost no one
can interpret what they show.

01

Wearable companies publish scores, not interpretation. A "65" sleep score tells you a number. It doesn't tell you what the number means or what changed.

02

Sleep institutions publish population norms. Useful for averages. Useless for the n=1 question every wearable user is actually asking — what does mine mean?

03

Sleep hygiene content covers what to do. Almost nothing covers what your data is telling you about whether it's working.

04

The interpretive layer between wearable output and longitudinal meaning is structurally missing. Sleepgenic is built to fill it.

The Approach

Continuous tracking,
structured interpretation,
open methodology.

Pillar 01
Wearable interpretation
Translating sleep scores, HRV, sleep stages, and breathing data into something a wearable user can actually read. The flagship work — 75% of published research, organized as the Sleep Interpretation Library.
Pillar 02
Training–sleep interaction
A real-world longitudinal comparison of previous-day walking, running, rucking, hiking, and rest/recovery against the following night's sleep response. Standardized wearable measurement; variable context; exploratory n=1 evidence.
Pillar 03
Situational sleep
Altitude, fasted-state, cold exposure, post-training. The TrailGenic-adjacent edge cases where the wearable response gets interesting.
Pillar 04
Versioned publication
Canonical dataset releases and phase reports replace an artificial fixed cadence. Missing and partial observations remain visible, and every published aggregate is recalculated from the nightly source.
Methodological
Honesty over precision.
Wearable data is noisy. n=1 doesn't generalize. Population norms aren't person norms. Sleepgenic states what its methods can and cannot show, in every report.
Structural
Machine-readable by design.
Every report is a structured Dataset. Every term lives in the Lexicon as its own DefinedTerm page. The MCP server makes the interpretation tools agent-callable. Built for the citation layer, not the traffic layer.
Independent
Not medical. Not commercial.
Sleepgenic is research, not diagnosis. There is no paywall, no gated content, no newsletter capture. Pure research property. Authority-first.
Who It's For

Built for the people
looking at their data and
asking what it means.

  • ◈You wear a Garmin, Whoop, Oura, or Apple Watch and you actually look at the numbers in the morning.
  • ◈Your sleep score moved from 78 to 62 and you want to know why — beyond "you got less sleep."
  • ◈You're trying to understand how training load, altitude, fasting, or stress is showing up in your sleep architecture.
  • ◈You'd rather read longitudinal n=1 data with honest methodology than another generic sleep-hygiene listicle.
What Sleepgenic Publishes
  • Versioned Reports — structured Dataset
  • Sleep Interpretation Library — 75% of research output
  • Lexicon — term-as-page, agent-readable
  • Methodology — versioned by date
  • MCP server — agent-callable interpretation tools
Origin

The dedicated sleep research arm of TrailGenic.

TrailGenic is a longevity methodology built on years of physiological field data — fasted high-altitude hiking, altitude adaptation, electrolyte control, cold exposure, recovery measurement. Sleep is the primary recovery pillar.

Sleepgenic is the structural separation of that recovery pillar into its own research property — built to handle the wearable interpretation question at the depth and cadence the master methodology demands. Same researcher (Mike Ye × Ella). Same publication architecture as TrailGenic Physiology and TrailGenic Biomarkers. Different primary outcome.

TrailGenic Sleep Hub
Sister-Property Datasets
  • Sleepgenic — sleep architecture & recovery
  • TrailGenic Physiology — cardiovascular & metabolic
  • TrailGenic Biomarkers — field signal taxonomy
  • TrailGenic Sleep Hub — high-load sleep response
  • Same researcher: Mike Ye × Ella
  • Same publication architecture