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Periodicities (repeating patterns) are observed in many human behaviors. Their strength may capture untapped patterns that incorporate sleep, sedentary, and active behaviors into a single metric indicative of better health.

Periodicities (repeating patterns) are observed in many human behaviors. Their strength may capture untapped patterns that incorporate sleep, sedentary, and active behaviors into a single metric indicative of better health. We present a framework to detect periodicities from longitudinal wrist-worn accelerometry data. GENEActiv accelerometer data were collected from 20 participants (17 men, 3 women, aged 35–65) continuously for 64.4±26.2 (range: 13.9 to 102.0) consecutive days. Cardiometabolic risk biomarkers and health-related quality of life metrics were assessed at baseline.

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    Date Created
    • 2016-01-04
    Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1155/2016/4856506
    • Identifier Type
      International standard serial number
      Identifier Value
      2314-6133
    • Identifier Type
      International standard serial number
      Identifier Value
      2314-6141

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    Buman, M. P., Hu, F., Newman, E., Smeaton, A. F., & Epstein, D. R. (2016). Behavioral Periodicity Detection from 24 h Wrist Accelerometry and Associations with Cardiometabolic Risk and Health-Related Quality of Life. BioMed Research International, 2016, 1-9. doi:10.1155/2016/4856506

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