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Clinical Manifestations.

Emilie V Brotherhood1,2, Coty Chen1, Claire J Cadwallader1

  • 1Memory and Aging Center, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

Fitbit™ activity data reveals distinct patterns in frontotemporal lobar degeneration (FTLD) patients. These rest-activity patterns differ significantly from those with mild cognitive impairment or healthy individuals.

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Area of Science:

  • Neuroscience
  • Gerontology
  • Biomedical Engineering

Background:

  • Alzheimer's disease and related dementias (ADRD) significantly impact sleep-wake cycles.
  • Commercial wearable devices offer scalable passive actigraphy for real-world monitoring.
  • Characterizing rest-activity patterns can reveal differences between healthy adults and ADRD cohorts.

Purpose of the Study:

  • To characterize continuous rest-activity patterns using Fitbit™ data.
  • To examine differences in these patterns between healthy adults and various ADRD cohorts.
  • To investigate associations between activity patterns and cognitive/functional decline.

Main Methods:

  • Collected tri-axial actigraphy, clinical, cognitive, functional, and mood data from healthy adults, mild cognitive impairment (MCI), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD) cohorts.
  • Quantified activity patterns using rest-activity aggregates and minute-level step count features.
  • Applied Principal Component Analysis (PCA) for data reduction and identified five components explaining >85% of variance.

Main Results:

  • Principal Component 1 (PC1), representing activity variability and amplitude, was negatively associated with cognitive and functional decline scores (CDR®+FTLD-NACC).
  • PC1 also showed significant diagnostic group differences, with FTLD patients exhibiting reduced PC1 scores compared to healthy and MCI groups.
  • PC3, related to rest-activity start timing, was negatively associated with global cognitive scores.

Conclusions:

  • Activity variability and amplitude derived from Fitbit™ data highlight distinct behavioral profiles in FTLD syndromes.
  • These distinct activity profiles differentiate FTLD patients from those with MCI or who are functionally intact.
  • Passive actigraphy via wearables provides valuable insights into neurodegenerative disease progression.