Abstract
This study aimed to investigate the direct relationship between the joint degrees of freedom (DoF) of human movement system and its postural dynamics. In our pilot experiment we fixed the join DoF (knee and ankle) to constrain the functional DoFs (one for knee, two for ankle). Young healthy participants were required to perform the single-leg standing task with their dominant leg fixed. The center of pressure (COP) trajectory data were measured and analyzed using linear and nonlinear methods to assess static and dynamic property of their postural dynamics. Results of comparing across conditions (normal no-fixation, ankle and knee fixation condition) revealed that static measure (COP trajectory length) did not differ significantly. However, dynamic measures (sample entropy and the fractal scaling exponent) significantly differed. The ankle joint fixation affected sample entropy decline (losing efficiency of postural control) and the scaling behavior (weakening the anti-persistent postural control process) in the mediolateral direction. These results seemed to agree with the notion of the loss of complexity framework.
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References
Bernstein, N.A.: The Co-ordination and Regulation of Movements. Pergamon Press Ltd., New York (1967)
Bernstein, N.A.: Dexterity and Its Development. Psychology Press, London (1996)
Boccara, N.: Modeling Complex Systems, 1st edn. Springer, New York (2003). https://doi.org/10.1007/b97378
Borchers, H.W.: Package “pracma” (2018). https://cran.r-project.org/web/packages/pracma/pracma.pdf
Bravi, A., Longtin, A., Seely, A.J., Ca, B.: Review and classification of variability analysis techniques with clinical applications. BioMed. Eng. OnLine 10(October), 90 (2011). https://doi.org/10.1186/1475-925X-10-90
Brown, C.T., Liebovitch, L.S.: Fractal Analysis. SAGE Publications, London (2010). https://uk.sagepub.com/en-gb/asi/fractal-analysis/book233383
Cavanaugh, J.T., Guskiewicz, K.M., Stergiou, N.: A nonlinear dynamic approach for evaluating postural control: new directions for the management of sport-related cerebral concussion. Sports Med. 35(11), 935–950 (2005). https://doi.org/0112-1642/05/011-0935
Constantino, M., Garcia, A., Constantino, A., Sawitzki, G.: Package “nonlinearTseries” (2015). https://cran.r-project.org/web/packages/nonlinearTseries/nonlinearTseries.pdf
Costa, M., et al.: Noise and poise: enhancement of postural complexity in the elderly with a stochastic-resonance-based therapy. Europhys. Lett. 77, 68008 (2007). https://doi.org/10.1209/0295-5075/77/68008
Davids, K., Glazier, P., Araújo, D., Bartlett, R.: Movement systems as dynamical systems: the functional role of variability and its implications for sports medicine. Sports Med. 33(4), 245–260 (2003). https://doi.org/10.2165/00007256-200333040-00001
Delignières, D., Torre, K., Bernard, P.-L.: Transition from persistent to anti-persistent correlations in postural sway indicates velocity-based control. PLoS Comput. Biol. 7(2), e1001089 (2011). https://doi.org/10.1371/journal.pcbi.1001089
Delignières, D., Torre, K., Lemoine, L.: Methodological issues in the application of monofractal analyses in psychological and behavioral research. Nonlinear Dyn. Psychol. Life Sci. 9(4), 451–477 (2005). https://doi.org/10.1093/beheco/aru014
Donker, S.F., Roerdink, M., Greven, A.J., Beek, P.J.: Regularity of center-of-pressure trajectories depends on the amount of attention invested in postural control. Exp. Brain Res. 181(1), 1–11 (2007). https://doi.org/10.1007/s00221-007-0905-4
Eke, A., Herman, P., Kocsis, L., Kozak, L.R.: Fractal characterization of complexity in temporal physiological signals. Physiol. Meas. 23(1), R1–R38 (2002). https://doi.org/10.1088/0967-3334/23/1/201
Gibson, J.J.: The Senses Considered as Perceptual Systems. Praeger, New York (1966)
Goldberger, A.L., Amaral, L.A.N., Hausdorff, J.M., Ivanov, P.C., Peng, C., Stanley, H.E.: Fractal dynamics in physiology: alterations with disease and aging. Proc. Nat. Acad. Sci. 99(Supplement 1), 2466–2472 (2002). https://doi.org/10.1073/pnas.012579499
Guskiewicz, K.M., Perrin, D.H.: Research and clinical applications of assessing balance. J. Sport Rehabil. 5(1), 45–63 (1996). https://doi.org/10.1123/jsr.5.1.45
Haken, H.: Synergetics: An Introduction: Nonequilibrium Phase Transitions and Self-Organization in Physics, Chemistry and Biology. Springer, Heidelberg (1978). https://doi.org/10.1007/978-3-642-96469-5. https://books.google.co.jp/books/about/Synergetics.html?id=z9PuAAAAMAAJ&pgis=1
Hausdorff, J.M.: Gait dynamics in Parkinson’s disease: common and distinct behavior among stride length, gait variability, and fractal-like scaling. Chaos 19(2) (2009). https://doi.org/10.1063/1.3147408
Hidaka, S., Kashyap, N.: On the estimation of pointwise dimension (2013). http://arxiv.org/abs/1312.2298
Horak, F.: Components of postural dyscontrol in the elderly: a review. Neurobiol. Aging 10(6), 727–738 (1989). https://doi.org/10.1016/0197-4580(89)90010-9
Ito, M., Mishima, H., Sasaki, M.: The dynamical stability of visual coupling and knee flexibility in skilled kendama players, pp. 308–332 (2011). https://doi.org/10.1080/10407413.2011.617669
King, D.L., Zatsiorsky, V.M.: Periods of extreme ankle displacement during one-legged standing. Gait & Posture 15(2), 172–179 (2002). https://doi.org/10.1016/S0966-6362(01)00189-8
Kodama, K., Aoyama, K.: Foundation of ecological approach. In: Rehabilitation Based on Perception. CBR (2017)
Kodama, K., Kikuchi, Y., Yamagiwa, H.: Whole-body coordination skill for dynamic balancing on a slackline. In: Otake, M., Kurahashi, S., Ota, Y., Satoh, K., Bekki, D. (eds.) New Frontiers in Artificial Intelligence, JSAI-isAI 2015. Lecture Notes in Computer Science, vol. 10091, pp. 528–546. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-50953-2_39
Kudo, K., Ohtsuki, T.: Adaptive variability in skilled human movements. Trans. Jpn. Soc. Artif. Intell. 23(3), 151–162 (2008). https://www.jstage.jst.go.jp/article/tjsai/23/3/23_3_151/_pdf
Lipsitz, L.A., Goldberger, A.L.: Loss of “Complexity” and Aging. JAMA 267(13), 1806 (1992). https://doi.org/10.1001/jama.1992.03480130122036
Manor, B., et al.: Physiological complexity and system adaptability: evidence from postural control dynamics of older adults. J. Appl. Physiol. 109(6), 1786–1791 (2010). https://doi.org/10.1152/japplphysiol.00390.2010
Manor, B., Lipsitz, L.A.: Physiologic complexity and aging: Implications for physical function and rehabilitation. Prog. Neuropsychopharmacol. Biol. Psychiatry 45(617), 287–293 (2013). https://doi.org/10.1016/j.pnpbp.2012.08.020
Nicolis, G., Prigogine, I.: Self-organization in nonequilibrium systems: from dissipative structures to order through fluctuations. Wiley (1977). https://books.google.com/books?id=mZkQAQAAIAAJ&pgis=1
Nonaka, T.: Motor variability but functional specificity: the case of a C4 tetraplegic mouth calligrapher. Ecol. Psychol. 25(2), 131–154 (2013). https://doi.org/10.1080/10407413.2013.780492
Nonaka, T., Bril, B.: Nesting of asymmetric functions in skilled bimanual action: dynamics of hammering behavior of bead craftsmen. Hum. Mov. Sci. 31(1), 55–77 (2012). https://doi.org/10.1016/j.humov.2010.08.013
Nonaka, T., Bril, B.: Fractal dynamics in dexterous tool use: the case of hammering behavior of bead craftsmen. J. Exp. Psychol. Hum. Percept. Perform. 40(1), 218–231 (2014). https://doi.org/10.1037/a0033277
Peng, C., Buldyrev, S.V., Havlin, S., Simons, M., Stanley, H.E., Goldberger, A.L.: Mosaic organization of DNA nucleotides. Phys. Rev. E 49(2), 1685–1689 (1994). https://doi.org/10.1103/PhysRevE.49.1685
Peng, C., Havlin, S., Stanley, H.E., Goldberger, A.L.: Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos 5(1), 82–87 (1995). https://doi.org/10.1063/1.166141
Pincus, S.M.: Approximate entropy as a measure of system complexity. Mathematics 88(March), 2297–2301 (1991). https://doi.org/10.1073/pnas.88.6.2297
Richman, J.S., Moorman, J.R.: Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol. Heart Circ. Physiol. 278(6), H2039–H2049 (2000). https://doi.org/10.1103/physreva.29.975
Roerdink, M., De Haart, M., Daffertshofer, A., Donker, S.F., Geurts, A.C.H., Beek, P.J.: Dynamical structure of center-of-pressure trajectories in patients recovering from stroke. Exp. Brain Res. 174(2), 256–269 (2006). https://doi.org/10.1007/s00221-006-0441-7
Schmit, J.M., et al.: Deterministic center of pressure patterns characterize postural instability in Parkinson’s disease. Exp. Brain Res. 168(3), 357–367 (2006). https://doi.org/10.1007/s00221-005-0094-y
Shumway-Cook, A., Woollacott, M.H.: Motor control: translating research into clinical practice. Lippincott Williams & Wilkins (2013). https://books.google.com/books?id=BJcL3enz3xMC&pgis=1
Sleimen-malkoun, R., Temprado, J., Hong, S.L.: Aging induced loss of complexity and dedifferentiation: consequences for coordination dynamics within and between brain, muscular and behavioral levels. Front. Aging Neurosci. 6(June), 1–17 (2014). https://doi.org/10.3389/fnagi.2014.00140
Stergiou, N.: Nonlinear Analysis for Human Movement Variability. CRC Press, Boca Raton (2016)
Suwa, M.: Story-telling and encouragement as a research environment - what is “researchers learn from one another”? Artif. Intell. 28(5), 695–701 (2013)
Turvey, M.T.: Coordination. Am. Psychol. 45(8), 938–953 (1990)
Van Orden, G.C., Holden, J.G., Turvey, M.T.: Self-organization of cognitive performance. J. Exp. Psychol. Gen. 132(3), 331–350 (2003). https://doi.org/10.1037/0096-3445.132.3.331
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This work was supported by Kanagawa University Grant for Joint Research.
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Kodama, K., Yasuda, K., Yamagiwa, H. (2019). Constraints on Joint Degrees of Freedom Affect Human Postural Dynamics: A Pilot Study. In: Kojima, K., Sakamoto, M., Mineshima, K., Satoh, K. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2018. Lecture Notes in Computer Science(), vol 11717. Springer, Cham. https://doi.org/10.1007/978-3-030-31605-1_32
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