Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2025 Apr 11;48(4):zsae267.
doi: 10.1093/sleep/zsae267.

Evaluating the performance of open-source and proprietary processing of actigraphy sleep estimation in children with suspected sleep disorders: a comparison with polysomnography

Aliye B Cepni  1 , Sarah Burkart  2 , Xuanxuan Zhu  2 , James White  2 , Olivia Finnegan  2 , Srihari Nelakuditi  2 , Michael Beets  2 , David Brown Iii  2 , Russell Pate  2 , Gregory Welk  3 , Massimiliano de Zambotti  4 , Rahul Ghosal  2 , Yuan Wang  2 , Bridget Armstrong  2 , Elizabeth Adams  2 , Vincent van Hees  5 , R Glenn Weaver  2
Affiliations
Comparative Study

Evaluating the performance of open-source and proprietary processing of actigraphy sleep estimation in children with suspected sleep disorders: a comparison with polysomnography

Aliye B Cepni et al. Sleep. .

Abstract

Study objectives: Evaluate the performance of actigraphy-based open-source and proprietary sleep algorithms compared to polysomnography in children with suspected sleep disorders.

Methods: In a sleep clinic, 110 children (5-12 years, 54% female, 50% black, 82% with sleep disorders) wore wrist-placed ActiGraph GT9X during overnight polysomnography. Actigraphy data were scored as sleep or wake using open-source GGIR and proprietary ActiLife software. Discrepancy and epoch-by-epoch analyses were conducted to assess agreement between algorithms and polysomnography, along with equivalence testing.

Results: The open-source vanHees2015 algorithm showed good accuracy (79.5% ± 12.0%), sensitivity (81.1% ± 13.5%), and specificity (66.0% ± 23.8%) for sleep detection but was outperformed by the proprietary ActiLife algorithms. The magnitude and trend of bias for total sleep time (TST), sleep efficiency (SE), sleep onset latency, and wake after sleep onset were similar between algorithms. TST and SE were statistically equivalent for the Cole-Kripke (Actilife) and vanHees2015 algorithms compared to the Sadeh (Actilife) algorithm. The Cole-Kripke (ActiLife) demonstrated higher sensitivity (90.5%) to detect sleep but lower specificity (61.2%) than Cole-Kripke (GGIR) (sensitivity: 62.7%, specificity: 79.9%). Sadeh and Cole-Kripke estimated sleep outcomes were not statistically equivalent between implementations in ActiLife and GGIR.

Conclusions: The open-source vanHees2015 algorithm performed well but slightly worse than the proprietary ActiLife algorithms in children. The open-source nature vanHees2015 makes it ideal for clinical pediatric use. Implementation of the Sadeh and Cole-Kripke algorithms in the proprietary ActiLife and open-source GGIR software yield different sleep estimates, so comparisons between studies using these different implementations should be avoided.

Keywords: GGIR; actigraphy; pediatrics; pediatrics—sleep apnea; scoring.

PubMed Disclaimer

Comment in

References

    1. Meltzer LJ, Montgomery-Downs HE, Insana SP, Walsh CM.. Use of actigraphy for assessment in pediatric sleep research. Sleep Med Rev. 2012;16(5):463–475. doi: https://doi.org/10.1016/j.smrv.2011.10.002 - DOI - PMC - PubMed
    1. Fekedulegn D, Andrew ME, Shi M, Violanti JM, Knox S, Innes KE.. Actigraphy-based assessment of sleep parameters. Ann. Work Expo. Health. 2020;64(4):350–367. doi: https://doi.org/10.1093/annweh/wxaa007 - DOI - PMC - PubMed
    1. Sadeh A, Sharkey KM, Carskadon MA.. Activity-based sleep-wake identification: an empirical test of methodological issues. Sleep. 1994;17(3):201–207. doi: https://doi.org/10.1093/sleep/17.3.201 - DOI - PubMed
    1. Cole RJ, Kripke DF, Gruen W, Mullaney DJ, Gillin JC.. Automatic sleep/wake identification from wrist activity. Sleep. 1992;15(5):461–469. doi: https://doi.org/10.1093/sleep/15.5.461 - DOI - PubMed
    1. Neishabouri A, Nguyen J, Samuelsson J, et al.Quantification of acceleration as activity counts in ActiGraph wearable. Sci Rep. 2022;12(1):11958. doi: https://doi.org/10.1038/s41598-022-16003-x - DOI - PMC - PubMed

Publication types