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An actigraphy-based nap detection algorithm reliably identifies nap-based phenotypes that differentiate individuals with narcolepsy type 1 from healthy controls, and demonstrates that an orexin receptor 2-selective agonist reduces napping to normative levels.

The study developed and validated an actigraphy-based nap detection algorithm with high specificity (93.2%) and accuracy (F1 Area: 83.9%). Applying the algorithm, participants with narcolepsy type 1 had 12.8 fewer nap-free days over 28 days and slept 34 minutes more during the day than controls; treatment with oveporexton (TAK-861) increased nap-free days by 6.1-11.9 and reduced daytime sleep by 12-33 minutes versus baseline.

Last updated: Aug 21, 2026•0 RCTs•📖 Read as article →

Evidence Score

Evidence Score34/100
Human RCT☆☆☆☆☆
Meta-analysis☆☆☆☆☆
Mechanism★★★★★
Safety★★★★☆
Confidencelow

Study Evidence

Study 1. An actigraphy-based algorithm to assess daytime napping in people with narcolepsy type 1.

observational

Torres R, Ghosal R, Naylor M, Gill SK, Pyatkevich Y, Bermingham SL, Buhl DL, Tracey B, Karas M, Onorati F, Zipunnikov V, Volfson D · Sleep (2026)

Participants: N/A
Duration: 28 days (observational study)
Intervention: Actigraphy-based nap detection algorithm; oveporexton (TAK-861) in a randomized clinical trial
Outcome: Daytime napping (nap-free days, daytime sleep duration)
Effect Size: N/A (reported as differences: 12.8 fewer nap-free days, 34 min more sleep; 6.1-11.9 additional nap-free days, 12-33 min fewer)
Population: Participants with narcolepsy type 1 (NT1) and age/sex-matched healthy controls

Result:

PubMed: 42610966DOI: 10.1093/sleep/zsag219

Mechanism Graph

Developed nap detection algorithm using wrist-worn actigraphy data from 2237 participants with manually annotated naps
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Validated algorithm for high specificity and accuracy
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Applied algorithm to observational study comparing NT1 patients to controls
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Applied algorithm to randomized clinical trial of orexin receptor 2-selective agonist (oveporexton)
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Result: Algorithm differentiated NT1 from controls and showed treatment reduced napping to near-normal levels

Limitations

  • ⚠Algorithm developed on general population data (MESA) may not fully capture NT1-specific nap patterns
  • ⚠Abstract does not report effect sizes or confidence intervals for the differences
  • ⚠Observational study results may be confounded by lifestyle or medication differences

Frequently Asked Questions

What is the accuracy of the nap detection algorithm?▼

The algorithm has high specificity (Tau B: 93.2%) and accuracy (F1 Area: 83.9%).

How does oveporexton affect napping in narcolepsy type 1?▼

In a randomized clinical trial, oveporexton increased nap-free days by 6.1-11.9 and reduced daytime sleep by 12-33 minutes compared to baseline.

What is the difference in napping between NT1 patients and healthy controls?▼

NT1 patients had 12.8 fewer nap-free days over 28 days and slept 34 minutes more during the day than controls.

What data was used to develop the algorithm?▼

The algorithm was developed using data from the Multi-Ethnic Study of Atherosclerosis, including 2237 participants with 7 days of wrist-worn actigraphy and manually annotated naps.

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References

  1. 1.Torres R, Ghosal R, Naylor M, Gill SK, Pyatkevich Y, Bermingham SL, Buhl DL, Tracey B, Karas M, Onorati F, Zipunnikov V, Volfson D. "An actigraphy-based algorithm to assess daytime napping in people with narcolepsy type 1.." Sleep, 2026. PMID: 42610966 DOI: 10.1093/sleep/zsag219
Disclaimer: This content is for educational purposes only and is not medical advice. Evidence scores reflect the quality and quantity of available research, not clinical recommendations. Always consult a healthcare professional before starting any supplement or intervention.