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

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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 a scalable method for monitoring these changes through passive actigraphy.
  • Characterizing rest-activity patterns can provide insights into cognitive decline.

Purpose of the Study:

  • To characterize continuous rest-activity patterns using Fitbit™ data.
  • To examine differences in these patterns between healthy adults and individuals with ADRD.
  • To identify potential biomarkers for cognitive and functional decline.

Main Methods:

  • Collected tri-axial actigraphy data (step counts), clinical, cognitive, functional, and mood information from healthy adults, mild cognitive impairment (MCI), Alzheimer's disease dementia (AD), and frontotemporal lobar degeneration (FTLD) cohorts.
  • Quantified activity patterns using rest-activity aggregates and minute-level features.
  • Applied Principal Component Analysis (PCA) for data reduction and identified five key components explaining over 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 differences between diagnostic groups, with FTLD patients exhibiting reduced PC1 scores compared to healthy and MCI cohorts.
  • PC3, related to rest-activity start timing, was negatively associated with the global cognitive score.

Conclusions:

  • Activity variability and amplitude derived from Fitbit™ data can distinguish FTLD patients.
  • These distinct activity profiles differ from those observed in individuals with mild cognitive impairment or those who are functionally intact.
  • Wearable actigraphy shows promise for identifying syndrome-specific rest-activity patterns in neurodegenerative diseases.