Literature DB >> 28958046

Recurrence Quantification for the Analysis of Coupled Processes in Aging.

Timothy R Brick1, Allison L Gray2, Angela D Staples3.   

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. Method: We 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.
© The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Keywords:  Dyadic analysis; Dynamical systems analysis; Interpersonal systems; Longitudinal change; Recurrence quantification analysis

Mesh:

Year:  2017        PMID: 28958046      PMCID: PMC5927149          DOI: 10.1093/geronb/gbx018

Source DB:  PubMed          Journal:  J Gerontol B Psychol Sci Soc Sci        ISSN: 1079-5014            Impact factor:   4.077


  26 in total

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