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Quantifying postural sway dynamics using burstiness and interevent time distributions

Author

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  • Sergio Picoli

    (Departamento de Física and National Institute of Science and Technology for Complex Systems, Universidade Estadual de Maringá)

  • Edenize S. D. Santos

    (Departamento Acadêmico de Física, Universidade Tecnológica Federal do Paraná)

  • Pedro P. Deprá

    (Departamento de Educação Física, Laboratory of Biomechanics and Motor Behaviour, Universidade Estadual de Maringá)

  • Renio S. Mendes

    (Departamento de Física and National Institute of Science and Technology for Complex Systems, Universidade Estadual de Maringá)

Abstract

We propose an approach for analysing the dynamics of human postural sway using measures applied to study inhomogeneous temporal processes. Basically, we defined zero-crossings of center of pressure (COP) trajectories as events, obtained the sequence of interevent times and investigated the mean interevent time, the burstiness coefficient and the full functional form of the interevent time distribution. We applied this approach to data obtained for healthy young adults during quiet standing, under bipedal and unipedal conditions. We found that the proposed COP-based measures are able to detect differences between bipedal and unipedal postural sway temporal patterns, including the presence (or absence) of burstiness. We discussed the potential of this analysis to quantify temporal patterns of postural sway. Graphical abstract

Suggested Citation

  • Sergio Picoli & Edenize S. D. Santos & Pedro P. Deprá & Renio S. Mendes, 2019. "Quantifying postural sway dynamics using burstiness and interevent time distributions," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 92(7), pages 1-5, July.
  • Handle: RePEc:spr:eurphb:v:92:y:2019:i:7:d:10.1140_epjb_e2019-90737-2
    DOI: 10.1140/epjb/e2019-90737-2
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    Cited by:

    1. Picoli, Sergio & Bombo, Giorgio & Santos, Edenize S.D. & Deprá, Pedro P. & Mendes, Renio S., 2022. "Characterizing postural sway signals by the analysis of zero-crossing patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).

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    Keywords

    Statistical and Nonlinear Physics;

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