PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
Tytuł artykułu

A new multi-attractor model for the human posture stability system aimed to follow self-organized dynamics

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Human postural stability is a complex nonlinear system, which naturally exhibits coexisting attractors and influenced by various factors. This system continuously requires to employ the self-organization mechanisms to maintain postural stability. This functionality is equivalent to switching the system dynamics among its attractors. The aim of our study is to follow the variations of the postural dynamics at different time intervals. The center-of-pressure (CoP) was recorded during 60 s routine walk from twenty healthy young adult men with no evidence of neuromuscular system diseases. The experiment was repeated three times for each subject. We designed a map-based model with multiple attractors and defined two indicators to quantify the system dynamics at various time intervals. To model the system self-organization, we slid a window along the CoP time series. For each window, the parameters and the state variables of the model were set based on the proposed indicators (nonlinear local features). Tracking the behavioral patterns of the posture system is one of the prominent results of this research. The proposed model not only can follow the local (short-time interval) behavior of the system but also its global dynamics variation is like the experimental data based on the correlation dimension (CD). The CD reveals system dynamics in the long-time intervals and reflects the number of the effective system's degrees of freedom. The proposed methods can be used to quantify the variation of information in other biological systems.
Twórcy
  • Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran
  • Department of Biomedical Engineering, Amirkabir University of Technology, 424 Hafez Avenue, Tehran, Iran
  • Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran
Bibliografia
  • [1] Shumway-Cook A, Woollacott MH. Motor control: translating research into clinical practice. Lippincott Williams & Wilkins; 2007.
  • [2] Wang Z, Ko JH, Challis JH, Newell KM. The degrees of freedom problem in human standing posture: collective and component dynamics. PLoS One 2014;9(1).
  • [3] Gurses S, Celik H. Correlation dimension estimates of human postural sway. Hum Mov Sci [Internet] 2013;32 (1):48–64. Available from: http://www.sciencedirect.com/science/article/pii/ S0167945712001005.
  • [4] Fortune E, Crenshaw J, Lugade V, Kaufman KR. Dynamic assessment of center of pressure measurements from an instrumented AMTI treadmill with controlled precision. Med Eng Phys [Internet] 2017;42:99–104. Available from: http://www.sciencedirect.com/science/article/pii/ S1350453317300036.
  • [5] van Emmerik REA, Ducharme SW, Amado AC, Hamill J. Comparing dynamical systems concepts and techniques for biomechanical analysis. J Sport Health Sci 2016;5(1):3–13.
  • [6] Grönqvist R, Abeysekera J, Gard G, Hsiang SM, Leamon TB, Newman DJ, et al. Human-centred approaches in slipperiness measurement. Ergonomics 2001;44(13):1167–99.
  • [7] Ducharme SW, van Emmerik REA. Fractal dynamics, variability, and coordination in human locomotion. Kinesiol Rev 2018;7(1):26–35.
  • [8] Dutt-Mazumder A, Rand TJ, Mukherjee M, Newell KM. Scaling oscillatory platform frequency reveals recurrence of intermittent postural attractor states. Sci Rep 2018;8(1):1–10.
  • [9] Marigold DS, Patla AE. Strategies for dynamic stability during locomotion on a slippery surface: effects of prior experience and knowledge. J Neurophysiol [Internet] 2002;88(1):339–53. Available from: http://jn.physiology.org/lookup/doi/10.1152/jn.00691.2001.
  • [10] Dutt-Mazumder A, King AC, Newell KM. Recurrence dynamics reveals differential control strategies to maintain balance on sloped surfaces. Gait Posture [Internet] 2019;69:169–75. http://dx.doi.org/10.1016/j.gaitpost.2019.01.040.
  • [11] Chatard H, Tepenier L, Jankowski O, Aussems A, Allieta A, Beydoun T, et al. Effects of age-related macular degeneration on postural sway. Front Hum Neurosci [Internet] 2017;11:158. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374199/.
  • [12] Bonnet CT, Kinsella-Shaw JM, Frank TD, Bubela DJ, Harrison SJ, Turvey MT. Deterministic and stochastic postural processes: effects of task, environment, and age. J Mot Behav [Internet] 2009;42(1):85–97. http://dx.doi.org/10.1080/00222890903498521.
  • [13] Doná F, Aquino CC, Gazzola JM, Borges V, Silva SMCA, Ganança FF, et al. Changes in postural control in patients with Parkinson's disease: a posturographic study. Physiotherapy [Internet] 2016;102(3):272–9. Available from: http://www.sciencedirect.com/science/article/pii/ S0031940615038213.
  • [14] Santuz A, Ekizos A, Eckardt N, Kibele A, Arampatzis A. Challenging human locomotion: stability and modular organisation in unsteady conditions. Sci Rep 2018;8(1):1–13.
  • [15] Ekizos A, Santuz A, Schroll A, Arampatzis A. The maximum Lyapunov exponent during walking and running: reliability assessment of different marker-sets. Front Physiol 2018;9 (August):1–11.
  • [16] Amoud H, Abadi M, Hewson DJ, Michel-Pellegrino V, Doussot M, Duchêne J. Fractal time series analysis of postural stability in elderly and control subjects. J Neuroeng Rehabil 2007;4:12.
  • [17] Li C, Ding GH, Wu GQ, Poon CS. Fractal, entropic and chaotic approaches to complex physiological time series analysis: a critical appraisal. Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 [Internet]; 2009. p. 3429–32. Available from: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm? arnumber=5332501.
  • [18] Blaszczyk JW, Klonowski W. Postural stability and fractal dynamics. Acta Neurobiol Exp (Wars) 2001;61(2):105–12.
  • [19] Müller W, Jung A, Ahammer H. Advantages and problems of nonlinear methods applied to analyze physiological time signals: human balance control as an example. Sci Rep 2017;7(1):1–11.
  • [20] Mitra S, Amazeen PG, Turvey MT. Intermediate motor learning as decreasing active (dynamical) degrees of freedom. Hum Mov Sci [Internet] 1998;17(1):17–65. Available from: http://linkinghub.elsevier.com/retrieve/pii/ S0167945797000237.
  • [21] Hilborn RC, Sprott JC. Chaos and nonlinear dynamics: an introduction for scientists and engineers. Am J Phys [Internet] 1994;62(9):861–2. http://dx.doi.org/10.1119/1.17477.
  • [22] Grassberger P, Procaccia I. Measuring the strangeness of strange attractors. Phys D: Nonlinear Phenom [Internet] 1983;9(1–2):189–208. Available from: http://www.sciencedirect.com/science/article/pii/ 0167278983902981.
  • [23] Kay BA. The dimensionality of movement trajectories and the degrees of freedom problem: a tutorial. Hum Mov Sci [Internet] 1988;7(2–4):343–64. Available from: http://linkinghub.elsevier.com/retrieve/pii/ 0167945788900164.
  • [24] Hilborn RC, Sprott JC. Chaos and nonlinear dynamics: an introduction for scientists and engineers. Am J Phys [Internet] 1994;62(9):861–2. Available from: http://aapt.scitation.org/doi/10.1119/1.17477.
  • [25] Kennel MB, Brown R, Abarbanel HDI. Determining embedding dimension for phase-space reconstruction using a geometrical construction. Phys Rev A 1992;45 (6):3403.
  • [26] Pascolo PB, Marini A, Carniel R, Barazza F. Posture as a chaotic system and an application to the Parkinson's disease. Chaos Solitons Fractals [Internet] 2005;24(5):1343–6. Available from: http://linkinghub.elsevier.com/retrieve/pii/ S0960077904006307 [cited 3.12.2013].
  • [27] Kilby MC, Slobounov SM, Newell KM. Augmented feedback of COM and COP modulates the regulation of quiet human standing relative to the stability boundary. Gait Posture 2016;47:18–23.
  • [28] Kilby MC, Molenaar PCM, Slobounov SM, Newell KM. Real- time visual feedback of COM and COP motion properties differentially modifies postural control structures. Exp Brain Res 2016;1–12.
  • [29] Tanabe H, Fujii K, Kouzaki M. Intermittent muscle activity in the feedback loop of postural control system during natural quiet standing. Sci Rep [Internet] 2017;7(1):1–21. http://dx.doi.org/10.1038/s41598-017-10015-8.
  • [30] Medrano-Cerda G, Shapiro J, Brown M, Dallali H, Kowalczyk P, Glendinning P. Modelling human balance using switched systems with linear feedback control. J R Soc Interface 2011;9(67):234–45.
  • [31] Harbourne RT, Stergiou N. Movement variability and the use of nonlinear tools: principles to guide physical therapist practice. Phys Ther 2009;89(3):267–82.
  • [32] Tanabe H, Fujii K, Suzuki Y, Kouzaki M. Effect of intermittent feedback control on robustness of human-like postural control system. Sci Rep 2016;6.
  • [33] Eurich CW, Milton JG. Noise-induced transitions in human postural sway. Phys Rev E 1996;54(6):6681–4.
  • [34] Heylighen F. Self-organization of complex, intelligent systems: an action ontology for transdisciplinary integration. Integr Rev [Internet] 2011;1–39. Available from: http://pespmc1.vub.ac.be/papers/ECCO-paradigm.pdf.
  • [35] Crétual A. Which biomechanical models are currently used in standing posture analysis? Quels sont les modèles biomécaniques utilisés actuellement. Neurophysiol Clin/ Clin Neurophysiol [Internet] 2015;45(4–5):285–95. http://dx.doi.org/10.1016/j.neucli.2015.07.004.
  • [36] Hooker C. From being to becoming: time and complexity in the physical sciences. Ilya Prigogine Philos Sci [Internet] 1984;51(2):355–7. http://dx.doi.org/10.1086/289186.
  • [37] FEUDEL U. Complex dynamics in multistable systems. Int J Bifurc Chaos 2008;18(6):1607–26.
  • [38] Liu Y, Wiercigroch M, Ing J, Pavlovskaia E. Intermittent control of coexisting attractors. Philos Trans A: Math Phys Eng Sci [Internet] 2013;371(1993):20120428. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23690639.
  • [39] Attneave F. Multistability in perception. Sci Am [Internet] 1971;25(6):62–71. Available from: http://www.ncbi.nlm.nih.gov/pubmed/5116412.
  • [40] Mergner T, Schweigart G, Maurer C, Blümle A. Human postural responses to motion of real and virtual visual environments under different support base conditions. Exp Brain Res [Internet] 2005;167(4):535–56. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16132969 [cited 13.11.2013].
  • [41] Arecchi FT, Meucci R, Puccioni G, Tredicce J. Experimental evidence of subharmonic bifurcations, multistability, and turbulence in a Q-switched gas laser. Phys Rev Lett [Internet] 1982;49(17):1217–20. Available from: http://link.aps.org/doi/10.1103/PhysRevLett.49.1217.
  • [42] Feudel U, Grebogi C, Hunt BR, Yorke JA. Map with more than 100 coexisting low-period periodic attractors. Phys Rev E 1996;54(1):71.
  • [43] Hurmuzlu Y, Basdogan C. On the measurement of dynamic stability of human locomotion. J Biomech Eng Trans ASME [Internet] 1994;118(3):405–11. Available from: http://network.ku.edu.tr/_cbasdogan/Papers/ DynamicStabilityJBioMech.pdf.
  • [44] Kantz H, Schreiber T. Nonlinear time series analysis, vol. 7. Cambridge University Press; 2004.
  • [45] Sutton RS, Barto AG. Introduction to reinforcement learning, vol. 135. Cambridge: MIT Press; 1998.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5bc16db7-d90e-49dc-9aa9-cc1ab360528a
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.