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Cited by 298Sleep and related disordersCircadian rhythm and melatoninSleep and Work-Related Fatigue

Actigraphy-based sleep estimation in adolescents and adults: A comparison with polysomnography using two scoring algorithms

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Quante, Mirja, Kaplan, Emily R, Cailler, Michael, Rueschman, Michael, Wang, Rui, Weng, Jia, Taveras, Elsie M, Redline, Susan·2018·Nature and Science of Sleep
DOI 10.2147/nss.s151085PMC PMC5779275
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Abstract

Objectives: Actigraphy is widely used to estimate sleep–wake time, despite limited information regarding the comparability of different devices and algorithms. We compared estimates of sleep–wake times determined by two wrist actigraphs (GT3X+ versus Actiwatch Spectrum [AWS]) to in-home polysomnography (PSG), using two algorithms (Sadeh and Cole–Kripke) for the GT3X+ recordings. Subjects and methods: Participants included a sample of 35 healthy volunteers (13 school children and 22 adults, 46% male) from Boston, MA, USA. Twenty-two adults wore the GT3X+ and AWS simultaneously for at least five consecutive days and nights. In addition, actigraphy and PSG were concurrently measured in 12 of these adults and another 13 children over a single night. We used intraclass correlation coefficients (ICCs), epoch-by-epoch comparisons, paired t -tests, and Bland–Altman plots to determine the level of agreement between actigraphy and PSG, and differences between devices and algorithms. Results: Each actigraph showed comparable accuracy (0.81–0.86) for sleep–wake estimation compared to PSG. When analyzing data from the GT3X+, the Cole–Kripke algorithm was more sensitive (0.88–0.96) to detect sleep, but less specific (0.35–0.64) to detect wake than the Sadeh algorithm (sensitivity: 0.82–0.91, specificity: 0.47–0.68). Total sleep time measured using the GT3X+ with both algorithms was similar to that obtained by PSG (ICC=0.64–0.88). In contrast, agreement between the GT3X+ and PSG wake after sleep onset was poor (ICC=0.00–0.10). In adults, the GT3X+ using the Cole–Kripke algorithm provided data comparable to the AWS (mean bias=3.7±19.7 minutes for total sleep time and 8.0±14.2 minutes for wake after sleep onset). Conclusion: The two actigraphs provided comparable and accurate data compared to PSG, although both poorly identified wake episodes (i.e., had low specificity). Use of actigraphy scoring algorithm influenced the mean bias and level of agreement in sleep–wake times estimates. The GT3X+, when analyzed by the Cole–Kripke, but not the Sadeh algorithm, provided comparable data to the AWS. Keywords: validation, actigraphy, polysomnography, scoring algorithm

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  • Another research study for in-home polysomnography using the Cole-Kripke algorithm on a sample of 35 healthy volunteers found that it was more sensitive to identify sleep (88-96%), but less specific to detect awake time (35-64%).

    “Another research study for in-home polysomnography (PSG) using the Cole–Kripke algorithm on a sample of 35 healthy volunteers found that it was more sensitive to identify sleep (88–96%), but less specific to detect awake time (35–64%) [195].”

    From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [195]

  • The Cole-Kripke algorithm undervalued sleep and exaggerated wakefulness in children and vice versa in adults.

    “Previous research indicates that this algorithm undervalued sleep and exaggerated wakefulness in children and vice versa in adults.”

    From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [195]

  • Cole-Kripke sleep misclassification was high in research involving children as compared to adults.

    “However, research suggests that [195] Cole–Kripke sleep misclassification was high in research involving children as compared to adults.”

    From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [195]

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Authors
Quante, M., Kaplan, E. R., Cailler, M., Rueschman, M., Wang, R., Weng, J., Taveras, E. M., & Redline, S.
Affiliations
  • Brigham and Women's Hospital (US)
  • Harvard University (US)
Corresponding author
Quante, Mirja
ORCID
Venue
Nature and Science of Sleep
Publisher
Informa UK Limited
Published
2018-01
Volume
Volume 10
Pages
13-20
ISSN
1179-1608 (ISSN-L)
DOI
10.2147/nss.s151085
PMC
PMC5779275
OpenAlex
W2783706351
Cited by
298
References
22
Citations by year
2026: 35 · 2025: 27 · 2024: 53 · 2023: 41 · 2022: 42 · 2021: 41 · 2020: 31 · 2019: 19 · 2018: 8
FWCI
32.40
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature and Science of Sleep (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
  • Dove Medical Press (Taylor and Francis Group) (submittedVersion, cc-by-nc)
Funders
  • Max Kade Foundation
  • National Cancer Institute (U54CA155626)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
  • Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
Keywords
actigraphy, polysomnography, total sleep time, wake after sleep onset, adolescents, adults, device agreement, home sleep monitoring

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