{
  "abstract": "Introduction Recent times have seen the emergence of Rest-Activity Rhythms - an actigraphic approximation of circadian rhythms - as scalable biomarkers for sleep health, neurodevelopment, and psychiatric risk. Despite the popularity of Consumer Sleep Technologies such as Fitbit in research and practice, the utility and validity of these devices in deriving RAR metrics (e.g., MESOR, amplitude, acrophase) remains underexplored, particularly in young adolescents. We therefore examine the face validity of Fitbit-derived RAR metrics by comparing them with established sleep timing measures from portable EEG (Muse headband) and daily sleep diaries in healthy individuals aged 7-20 years.Methods Twenty-eight (28) participants were asked to wear Fitbit and Muse EEG devices across multiple nights while completing daily sleep diaries. RAR metrics (MESOR, amplitude, and acrophase) were extracted from Fitbit actigraphy using singular spectrum analysis (SSA). These actigraphic circadian estimates were compared with total time in bed (TiB), sleep onset latency (SOL), and mid-sleep time derived from EEG and diaries. Cross-modality Pearson correlations were calculated to assess the alignment between Fitbit-derived RAR metrics and established sleep timing measures.Results MESOR and amplitude showed modest positive correlations with diary-based TiB (r = 0.14 - 0.29, p<0.05), suggesting some alignment with self-reported sleep duration. Acrophase demonstrated stronger correlations with bedtime and mid-sleep timing, indicating its potential to capture individual differences in circadian phase. However, EEG-derived TiB showed weaker and more variable associations with Fitbit-derived RAR metrics.Discussion Fitbit-derived RAR metrics demonstrated preliminary face validity in youth when compared with EEG- and diary-based sleep timing measures. These findings provide initial support for the potential of consumer wearables to deliver scalable circadian monitoring in developmental and clinical research. However, the modest effect sizes and variability highlight the need for further work to validate these circadian constructs against gold-standard measures and in a larger, more diverse cohort.",
  "authors": [
    {
      "affiliations": [
        "University of Bristol, School of Engineering Mathematics and Technology, Bristol, United Kingdom"
      ],
      "name": "Abiola Saka"
    },
    {
      "affiliations": [
        "University of Bristol, School of Engineering Mathematics and Technology, Bristol, United Kingdom"
      ],
      "name": "Zahraa Abdallah"
    },
    {
      "affiliations": [
        "University of Bristol, School of Physiology, Pharmacology and Neuroscience, Bristol, United Kingdom"
      ],
      "name": "Matt Jones"
    }
  ],
  "title": "P64 Validation of fitbit-derived rest-activity rhythms in youth using portable EEG and sleep diaries",
  "uid": "39e47842-7f21-5988-8873-c043ecb88c90"
}