Sleep Staging & Actigraphy - References

Sleep Staging & Actigraphy — Literature Dossier

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Landmark Peer-Reviewed Studies

1. Windred et al. (2024) — Sleep Regularity Is a Stronger Predictor of Mortality Risk Than Sleep Duration

• Citation: Windred, D. P., Burns, A. C., Lane, J. M., Saxena, R., Rutter, M. K., Cain, S. W., & Phillips, A. J. K. (2024). Sleep regularity is a stronger predictor of mortality risk than sleep duration: a prospective cohort study. Sleep, 47(1), zsad253.
• Identifiers: DOI: 10.1093/sleep/zsad253 (DOI · SciDB · Scholar) | PMID: 37738616 (PubMed · Europe PMC) | PMCID: PMC10782501 (PMC Full Text)
• Study Design & Cohort: Prospective cohort study in the UK Biobank ($N=60,977$ participants with $>10\text{ million}$ hours of objective wrist-accelerometer actigraphy recordings followed for $7.1\pm 1.3\text{ years}$; $1,859$ deaths).
• Quantitative Findings & Diagnostic Thresholds:
  • Higher Sleep Regularity Index (SRI) (Quintiles 2–5 vs. irregular Quintile 1, $\text{SRI}<71.6$) was associated with a 20% to 48% lower risk of all-cause mortality ($\text{HR }0.52–0.80,p<0.001$), 16% to 39% lower risk of cancer mortality ($\text{HR }0.61–0.84$), and 22% to 57% lower risk of cardiometabolic mortality ($\text{HR }0.43–0.78$).
  • In direct head-to-head multivariable Cox models, Sleep Regularity significantly outperformed Sleep Duration ($p<0.0001$) in predicting survival.

2. Xie et al. (2013) & Shokri-Kojori et al. (2018) — Slow-Wave Sleep Drives Glymphatic Clearance of Beta-Amyloid

• Citation: Xie, L., Kang, H., Xu, Q., Chen, M. J., Liao, Y., Thiyagarajan, M., … & Nedergaard, M. (2013). Sleep drives metabolite clearance from the adult brain. Science, 342(6156), 373–377. (Paired with human PET validation: Shokri-Kojori, E., et al. [2018]. $\beta$-Amyloid accumulation in the human brain after one night of sleep deprivation. PNAS, 115[17], 4483–4488).
• Identifiers: DOI: 10.1126/science.1241224 (DOI · SciDB · Scholar) | PMID: 24136970 (PubMed · Europe PMC) | PMCID: PMC3880190 (PMC Full Text) (and DOI: 10.1073/pnas.1721694115 (DOI · SciDB · Scholar) | PMID: 29632177 (PubMed · Europe PMC))
• Study Design & Cohort: Real-time two-photon in vivo imaging and radiotracer clearance assays paired with a human crossover ${}^{18}\text{F}$-florbetaben PET neuroimaging study ($N=20$ healthy adults after rested sleep vs. 1 night of sleep deprivation).
• Quantitative Findings & Diagnostic Thresholds:
  • Slow-wave sleep delta activity was associated with a 60% increase in cortical interstitial space volume, driving a 2-fold faster convective clearance of $\beta$-amyloid via astrocytic Aquaporin-4 channels.
  • In humans, a single night of sleep loss significantly increased ${}^{18}\text{F}$-florbetaben $\beta$-amyloid burden by $+5.0\%$ ($p<0.005$) specifically in the right hippocampus and thalamus.

3. Svensson et al. (2024) — Validity and Reliability of the Oura Ring Generation 3 (Gen3) Against Polysomnography

• Citation: Svensson, T., Madhawa, K., Nt, H., Chung, U. I., & Svensson, A. K. (2024). Validity and reliability of the Oura Ring Generation 3 (Gen3) with Oura sleep staging algorithm 2.0 (OSSA 2.0) when compared to multi-night ambulatory polysomnography: A validation study of 96 participants and 421,045 epochs. Sleep Medicine, 115, 251–263.
• Identifiers: DOI: 10.1016/j.sleep.2024.01.020 (DOI · SciDB · Scholar) | PMID: 38382312 (PubMed · Europe PMC)
• Study Design & Cohort: Multi-night epoch-by-epoch validation study ($N=96$ healthy adults across $421,045$ 30-second epochs) comparing Oura Ring Gen 3 (OSSA 2.0) against gold-standard reference polysomnography (PSG).
• Quantitative Findings & Diagnostic Thresholds:
  • For 2-stage (Sleep vs. Wake) classification, sensitivity was 94.4%, specificity was 73.0%, and overall accuracy was 91.8%.
  • For 4-stage classification (Wake, Light, Deep [SWS], REM), epoch-by-epoch accuracy across all stages was 79.5% ($\text{Cohen’s }\kappa =0.68$), with stage sensitivities of 75.5% for REM, 79.6% for Deep Sleep (N3), and 81.0% for Light Sleep, establishing research-grade validity for multi-sensor finger PPG/temperature/actigraphy.

4. Strøm-Tejsen et al. (2016) — The Effects of Bedroom Air Quality (CO2) on Sleep and Next-Day Performance

• Citation: Strøm-Tejsen, P., Zukowska, D., Wargocki, P., & Wyon, D. P. (2016). The effects of bedroom air quality on sleep and next-day performance. Indoor Air, 26(5), 679–686.
• Identifiers: DOI: 10.1111/ina.12254 (DOI · SciDB · Scholar) | PMID: 26452168 (PubMed · Europe PMC)
• Study Design & Cohort: Randomized, single-blind crossover field intervention ($N=30$ bedrooms monitored via actigraphy and cognitive battery across two conditions: unventilated [mean ${\text{CO}}_2=2,395–2,585\text{ ppm}$] vs. silent mechanical outdoor-air ventilation [mean ${\text{CO}}_2=660–715\text{ ppm}$]).
• Quantitative Findings & Diagnostic Thresholds:
  • Maintaining nocturnal bedroom ${\text{CO}}_2<750–800\text{ ppm}$ significantly increased objective actigraphic Sleep Efficiency ($p<0.004$), reduced number of nocturnal awakenings ($p<0.03$), improved subjective sleep depth and freshness ($p<0.002$), and significantly improved next-day Baddeley Grammatical Reasoning cognitive test performance ($p<0.02$).