Trial reportJournal of physiological anthropology2022
Validity of an algorithm for determining sleep/wake states using FS-760 in school-aged children.
Trial report in Journal of physiological anthropology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The role of 24-hour wearable sensors in early evaluation of adolescent orthostatic dysregulation.PCN reports : psychiatry and clinical neurosciences · 2025Article
- Light at night and circadian rhythms: from the perspective of physiological anthropology research.Journal of physiological anthropology · 2024Article
- Timing of Deep and REM Sleep Based on Fitbit Sleep Staging in Young Healthy Adults under Real-Life Conditions.Brain sciences · 2024Article
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Abstract
backgroundActigraphy is a method used for determining sleep (S)/wakefulness (W) by actigraph, a device equipped with a built-in accelerometer and an algorithm validated for each device. The S/W determination algorithm for the waist-worn actigraph FS-760 has been formulated for adults. However, the algorithm for children has not been established. The purpose of this study was to formulate an algorithm for discriminating S/W in school-aged children using FS-760 and to evaluate its validity. We further tested the generalizability of existing algorithm for adults by applying it to the children's activity data and then examined factors associated with adult algorithm agreement rates by multiple regression analysis using combined adult and children data.
methodsSixty-five, healthy, school-aged children (aged 6 to 15 years) were recruited and randomly assigned to two groups: A (n = 33) and B (n = 32). They underwent 8-h polysomnography (PSG) and wore FS-760 simultaneously to obtain activity data. To determine the central epoch of the sleep/wake states (𝑥), a five-order linear discriminant analysis was conducted using the activity intensity of group A for five epochs (𝑥
resultsThe mean agreement rate of the developed algorithm was 91.0%, with a mean sensitivity (true sleep detection rate) of 93.0% and a mean specificity (true wakefulness detection rate) of 63.9%. The agreement rate of the adult algorithm applied to children's activity was significantly lower (81.8%) than that of the children algorithm. Multiple regression analysis showed that the agreement rates calculated by the adult algorithm were significantly related to mean activity of the 𝑥 epoch in NREM and REM sleep as well as age and sleep efficiency.
conclusionsThe S/W states in school-aged children can be reliably assessed using the developed algorithm for waist-worn actigraph FS-760. Since the accuracy of the adult algorithms decreased when applied it to children which have different activity levels during sleep, the establishment and validation of population-specific S/W algorithms should be required.
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