Validation of Actigraphy Sleep Metrics in Children Aged 8 to 16 Years: Considerations for Device Type, Placement and Algorithms

Simple item page
aut.relation.articlenumber40
aut.relation.issue1
aut.relation.journalInternational Journal of Behavioral Nutrition and Physical Activity
aut.relation.startpage40
aut.relation.volume21
dc.contributor.authorMeredith-Jones, KA
dc.contributor.authorHaszard, JJ
dc.contributor.authorGraham-DeMello, A
dc.contributor.authorCampbell, A
dc.contributor.authorStewart, T
dc.contributor.authorGalland, BC
dc.contributor.authorCox, A
dc.contributor.authorKennedy, G
dc.contributor.authorDuncan, S
dc.contributor.authorTaylor, RW
dc.date.accessioned2024-04-30T00:06:25Z
dc.date.available2024-04-30T00:06:25Z
dc.date.issued2024-04-16
dc.description.abstractBackground: Actigraphy is often used to measure sleep in pediatric populations, despite little confirmatory evidence of the accuracy of existing sleep/wake algorithms. The aim of this study was to determine the performance of 11 sleep algorithms in relation to overnight polysomnography in children and adolescents. Methods: One hundred thirty-seven participants aged 8–16 years wore two Actigraph wGT3X-BT (wrist, waist) and three Axivity AX3 (wrist, back, thigh) accelerometers over 24-h. Gold standard measures of sleep were obtained using polysomnography (PSG; Embletta MPRPG, ST + Proxy and TX Proxy) in the home environment, overnight. Epoch by epoch comparisons of the Sadeh (two algorithms), Cole-Kripke (three algorithms), Tudor-Locke (four algorithms), Count-Scaled (CS), and HDCZA algorithms were undertaken. Mean differences from PSG values were calculated for various sleep outcomes. Results: Overall, sensitivities were high (mean ± SD: 91.8%, ± 5.6%) and specificities moderate (63.8% ± 13.8%), with the HDCZA algorithm performing the best overall in terms of specificity (87.5% ± 1.3%) and accuracy (86.4% ± 0.9%). Sleep outcome measures were more accurately measured by devices worn at the wrist than the hip, thigh or lower back, with the exception of sleep efficiency where the reverse was true. The CS algorithm provided consistently accurate measures of sleep onset: the mean (95%CI) difference at the wrist with Axivity was 2 min (-6; -14,) and the offset was 10 min (5, -19). Several algorithms provided accurate measures of sleep quantity at the wrist, showing differences with PSG of just 1–18 min a night for sleep period time and 5–22 min for total sleep time. Accuracy was generally higher for sleep efficiency than for frequency of night wakings or wake after sleep onset. The CS algorithm was more accurate at assessing sleep period time, with narrower 95% limits of agreement compared to the HDCZA (CS:-165 to 172 min; HDCZA: -212 to 250 min). Conclusion: Although the performance of existing count-based sleep algorithms varies markedly, wrist-worn devices provide more accurate measures of most sleep measures compared to other sites. Overall, the HDZCA algorithm showed the greatest accuracy, although the most appropriate algorithm depends on the sleep measure of focus.
dc.identifier.citationInternational Journal of Behavioral Nutrition and Physical Activity, ISSN: 1479-5868 (Print); 1479-5868 (Online), Springer Science and Business Media LLC, 21(1), 40-. doi: 10.1186/s12966-024-01590-x
dc.identifier.doi10.1186/s12966-024-01590-x
dc.identifier.issn1479-5868
dc.identifier.issn1479-5868
dc.identifier.urihttp://hdl.handle.net/10292/17482
dc.languageeng
dc.publisherSpringer Science and Business Media LLC
dc.relation.urihttps://ijbnpa.biomedcentral.com/articles/10.1186/s12966-024-01590-x
dc.rightsOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
dc.rights.accessrightsOpenAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAccelerometery
dc.subjectAlgorithm
dc.subjectPolysomnography
dc.subjectSleep
dc.subjectSleep/wake
dc.subjectValidation
dc.subject32 Biomedical and Clinical Sciences
dc.subject3202 Clinical Sciences
dc.subjectClinical Research
dc.subjectPrevention
dc.subjectSleep Research
dc.subjectBioengineering
dc.subjectNeurosciences
dc.subject11 Medical and Health Sciences
dc.subject13 Education
dc.subjectPublic Health
dc.subject3210 Nutrition and dietetics
dc.subject4202 Epidemiology
dc.subject4207 Sports science and exercise
dc.subject.meshChild
dc.subject.meshAdolescent
dc.subject.meshHumans
dc.subject.meshActigraphy
dc.subject.meshReproducibility of Results
dc.subject.meshSleep
dc.subject.meshPolysomnography
dc.subject.meshAlgorithms
dc.subject.meshHumans
dc.subject.meshPolysomnography
dc.subject.meshReproducibility of Results
dc.subject.meshSleep
dc.subject.meshAlgorithms
dc.subject.meshAdolescent
dc.subject.meshChild
dc.subject.meshActigraphy
dc.subject.meshChild
dc.subject.meshAdolescent
dc.subject.meshHumans
dc.subject.meshActigraphy
dc.subject.meshReproducibility of Results
dc.subject.meshSleep
dc.subject.meshPolysomnography
dc.subject.meshAlgorithms
dc.titleValidation of Actigraphy Sleep Metrics in Children Aged 8 to 16 Years: Considerations for Device Type, Placement and Algorithms
dc.typeJournal Article
pubs.elements-id545167
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Validation of actigraphy sleep metrics in children aged 8 to 16 years.pdf
Size:
966.36 KB
Format:
Adobe Portable Document Format
Description:
Journal article
Download
Collections
School of Sport and Recreation