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. 2010 Feb;65(2):197-203.
doi: 10.1093/gerona/glp144. Epub 2009 Oct 12.

Nonlinear analysis of ambulatory activity patterns in community-dwelling older adults

James T Cavanaugh  1 , Naomi Kochi, Nicholas Stergiou
Affiliations

Nonlinear analysis of ambulatory activity patterns in community-dwelling older adults

James T Cavanaugh et al. J Gerontol A Biol Sci Med Sci. 2010 Feb.

Abstract

Background: The natural ambulatory activity patterns of older adults are not well understood. User-worn monitors illuminate patterns of ambulatory activity and generate data suitable for analysis using measures derived from nonlinear dynamics.

Methods: Ambulatory activity data were collected continuously from 157 community-dwelling older adults for 2 weeks. Participants were separated post hoc into groups based on the mean number of steps per day: highly active (steps > or = 10,000), moderately active (5,000 < or = steps < 10,000 steps), and inactive (steps <5,000 steps). Detrended fluctuation analysis (DFA), entropy rate (ER), and approximate entropy (ApEn) were used to examine the complexity of daily time series composed of 1-minute step count values. Coefficient of variation was used to examine time series variability. Between-group differences for each parameter were evaluated using analysis of variance.

Results: All groups displayed patterns of fluctuating step count values containing complex temporal structure. DFA, ER, and ApEn parameter values increased monotonically and significantly with increasing activity level (p < .001). The variability of step count fluctuations did not differ among groups.

Conclusions: Highly active participants had more complex patterns of ambulatory activity than less active participants. The results supported the idea that, in addition to the volume of activity produced by an individual, patterns of ambulatory activity contain unique information that shows promise for offering insights into walking behavior associated with healthy aging.

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Figures

Figure 1.
Figure 1.
(A) Representative time series of step counts in 1-minute intervals for a full day obtained from an active individual. (B and C) Conceptual illustration of the process for transforming representative raw step count time series into a binary sequence of minutes containing activity (1) or no activity (0). The transformation removed the effect of step count values (i.e., vertical structure) in preparation for calculating entropy rate.
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