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Characterizing Behavioral Activity Rhythms in Older Adults Using Actigraphy.

Ariel B Neikrug1, Ivy Y Chen1, Jake R Palmer2,3

  • 1Department of Psychiatry and Human Behavior, University of California, Irvine, CA 92697, USA.

Sensors (Basel, Switzerland)
|January 23, 2020
PubMed
Summary
This summary is machine-generated.

Wrist actigraphy reveals behavioral activity rhythms (BAR) in older adults. A new graphical method using generalized additive models effectively characterizes these activity patterns, offering meaningful clinical insights.

Keywords:
actigraphybehavioral activity rhythmscircadian rhythmsolder adults

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Area of Science:

  • Gerontology
  • Chronobiology
  • Biomedical Engineering

Background:

  • Wrist actigraphy has been a long-standing tool for sleep assessment in older adults.
  • Actigraphy data extends beyond sleep to characterize physical activity and circadian rhythms.
  • Behavioral activity rhythms (BAR) are clinically significant indicators of daily patterns.

Purpose of the Study:

  • To review rhythmometric approaches for BAR in older adults.
  • To introduce a novel graphical method for BAR characterization.
  • To apply this method to older adults with osteoarthritis pain and insomnia.

Main Methods:

  • Review of common rhythmometric approaches.
  • Development of a new graphical characterization method for BAR.
  • Application of generalized additive models (GAM) to actigraphy data from older adults (60+) with osteoarthritis and insomnia.

Main Results:

  • The new approach provides graphical characterization of BAR.
  • Generalized additive models demonstrated a strong model fit (R² = 0.82, SD = 0.09).
  • The method yielded meaningful outcome measures for activity patterns.

Conclusions:

  • The novel graphical approach effectively characterizes BAR in older adults.
  • This method offers valuable insights into activity patterns for clinical applications.
  • Actigraphy, analyzed with GAMs, provides robust characterization of behavioral rhythms.