Recurrence Quantification Analysis as a Tool for Discrimination Among Different Dynamics Classes: The Heart Rate Variability Associated to Different Age Groups

  • Laurita dos Santos
  • Joaquim J. Barroso
  • Moacir F. de Godoy
  • Elbert E. N. Macau
  • Ubiratan S. Freitas
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 103)


We propose a classification method based on recurrence quantification analysis (RQA) combined with support vector machines (SVM). This method combines in an effective way various quantitative descriptors to allow a refined discrimination among dynamical non linear systems that presents dynamics which are very similar to each other. To show how effective this methodology is, firstly, based on synthetic data, it is applied on time series generated from the logistic map with nearby parameter values and in the chaotic regime. Next, it is applied to human biosignals, namely, heart rate variability (HRV) time series obtained from four groups of individuals (premature newborns, full-term newborns, healthy young adults, and adults with severe coronary disease). Roughly the proposed methodology works as follows: The signals are transformed into recurrence plots (RP) and a set of RQA statistical features (recurrence rate, determinism, averaged and maximal diagonal line lengths, entropy, laminarity, trapping time, and length of longest vertical line) are extracted to form the input vector for a SVM classifier. Results show that the method discriminates groups of different ages with classification accuracy better than \(75\,\%\). Given that heart rate continuously fluctuates over time and reflects different mechanisms to maintain cardiovascular homeostasis of an individual, the results obtained may allow to draw important information on the autonomic control of circulation in normal and diseased conditions.


Recurrence quantification analysis Heart rate variability Different age groups 



The authors thank CAPES/Brazil (process \(8954-11-9\)) and CNPq/Brazil (process \(151597/2013-8\)) for financial support. E.E.N.M. would like to thanks CNPq and FAPESP (process \(2011/50151-0\)).


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Laurita dos Santos
    • 1
  • Joaquim J. Barroso
    • 2
  • Moacir F. de Godoy
    • 3
  • Elbert E. N. Macau
    • 2
  • Ubiratan S. Freitas
    • 4
  1. 1.Universidade do Vale do Paraíba - UNIVAPSão PauloBrazil
  2. 2.Instituto Nacional de Pesquisas EspaciaisSão PauloBrazil
  3. 3.Faculdade de Medicina de so José do Rio Preto - FamerpSão PauloBrazil
  4. 4.Complexe de Recherche Interprofessionnel en Aérothermochimie - CORIAUniversité de RouenRouenFrance

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