Validation of actigraphy sleep metrics in children aged 8 to 16 years: considerations for device type, placement and algorithms.
Open accessAbstract
BACKGROUND: 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.
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We recently developed a reliable coding protocol that uses video cameras to measure screen time in youths, which offered the advantage of continuous recording to capture nuances, such as rapid changes in screen types or activities.
“We recently developed a reliable coding protocol that uses video cameras to measure screen time in youths, which offered the advantage of continuous recording to capture nuances, such as rapid changes in screen types or activities.27”
From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [27]
The Methods > Data collection overview describes accelerometers and polysomnography used to measure children's sleep, not video cameras used to measure screen time. Searches for a video-coding protocol and rapid changes in screen activities found no passage addressing the claim. No page numbers are available in our copy. (LLM, conf=0.78)
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- Authors
- Meredith-Jones, K. A., Haszard, J. J., Graham-DeMello, A., Campbell, A., Stewart, T., Galland, B. C., Cox, A., Kennedy, G., Duncan, S., & Taylor, R. W.
- Affiliations
- University of Otago (NZ)
- Auckland University of Technology (NZ)
- Corresponding author
- Meredith-Jones, K. A.
- ORCID
- Venue
- International Journal of Behavioral Nutrition and Physical Activity
- Published
- 2024-04-16
- Volume
- 21
- Issue
- 1
- Pages
- 40-40
- ISSN
- 1479-5868 (ISSN-L)
- PMC
- PMC11020269
- OpenAlex
- W4394849543
- Cited by
- 32
- References
- 24
- Citations by year
- 2026: 13 · 2025: 13 · 2024: 6
- FWCI
- 13.09
- Type
- journal article
- Language
- en
- Update notices
- correction (2024-06-08)
- Open access
- gold
- doi.org
- Locations
- International Journal of Behavioral Nutrition and Physical Activity (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Tuwhera (Auckland University of Technology) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- University of Otago
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- actigraphy, sleep monitoring, children and adolescents, polysomnography validation, accelerometer placement, wrist-worn devices, sleep onset, sleep efficiency, wake after sleep onset, nocturnal awakenings, total sleep time, sleep quality assessment
- MeSH terms
- Adolescent, Algorithms, Child, Humans, Sleep, Reproducibility of Results, Polysomnography, Actigraphy
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