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Recurrence Quantification for the Analysis of Coupled Processes in Aging

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  • Timothy R Brick
  • Allison L Gray
  • Angela D Staples

Abstract

Objectives: Aging is a complex phenomenon, with numerous simultaneous processes that interact with each other on a moment-to-moment basis. One way to quantify the interactions of these processes is by measuring how much a process is similar to its own past states or the past states of another system through the analysis of recurrence. This paper presents an introduction to recurrence quantification analysis (RQA) and cross-recurrence quantification analysis (CRQA), two dynamical systems analysis techniques that provide ways to characterize the self-similar nature of each process and the properties of their mutual temporal co-occurrence.MethodWe present RQA and CRQA and demonstrate their effectiveness with an example of conversational movements across age groups. Results: RQA and CRQA provide methods of analyzing the repetitive processes that occur in day-to-day life, describing how different processes co-occur, synchronize, or predict each other and comparing the characteristics of those processes between groups. Discussion: With intensive longitudinal data becoming increasingly available, it is possible to examine how the processes of aging unfold. RQA and CRQA provide information about how one process may show patterns of internal repetition or echo the patterning of another process and how those characteristics may change across the process of aging.

Suggested Citation

  • Timothy R Brick & Allison L Gray & Angela D Staples, 2018. "Recurrence Quantification for the Analysis of Coupled Processes in Aging," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 73(1), pages 134-147.
    • Handle: RePEc:oup:geronb:v:73:y:2018:i:1:p:134-147.
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    References listed on IDEAS

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    1. Facchini, Angelo & Mocenni, Chiara & Marwan, Norbert & Vicino, Antonio & Tiezzi, Enzo, 2007. "Nonlinear time series analysis of dissolved oxygen in the Orbetello Lagoon (Italy)," Ecological Modelling, Elsevier, vol. 203(3), pages 339-348.
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