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Fractal Fluctuations in Human Walking: Comparison Between Auditory and Visually Guided Step**

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Abstract

In human locomotion, sensorimotor synchronization of gait consists of the coordination of step** with rhythmic auditory cues (auditory cueing, AC). AC changes the long-range correlations among consecutive strides (fractal dynamics) into anti-correlations. Visual cueing (VC) is the alignment of step lengths with marks on the floor. The effects of VC on the fluctuation structure of walking have not been investigated. Therefore, the objective was to compare the effects of AC and VC on the fluctuation pattern of basic spatiotemporal gait parameters. Thirty-six healthy individuals walked 3 × 500 strides on an instrumented treadmill with augmented reality capabilities. The conditions were no cueing (NC), AC, and VC. AC included an isochronous metronome. For VC, projected step** stones were synchronized with the treadmill speed. Detrended fluctuation analysis assessed the correlation structure. The coefficient of variation (CV) was also assessed. The results showed that AC and VC similarly induced a strong anti-correlated pattern in the gait parameters. The CVs were similar between the NC and AC conditions but substantially higher in the VC condition. AC and VC probably mobilize similar motor control pathways and can be used alternatively in gait rehabilitation. However, the increased gait variability induced by VC should be considered.

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Abbreviations

AC:

Auditory cueing

NC:

No cueing

VC:

Visual cueing

DFA:

Detrended fluctuation analysis

CV:

Coefficient of variation

References

  1. Accardo, A., M. Affinito, M. Carrozzi, and F. Bouquet. Use of the fractal dimension for the analysis of electroencephalographic time series. Biol. Cybern. 77:339–350, 1997.

    Article  CAS  PubMed  Google Scholar 

  2. Azulay, J.-P., S. Mesure, B. Amblard, O. Blin, I. Sangla, and J. Pouget. Visual control of locomotion in Parkinson’s disease. Brain 122:111–120, 1999.

    Article  PubMed  Google Scholar 

  3. Bauby, C. E., and A. D. Kuo. Active control of lateral balance in human walking. J. Biomech. 33:1433–1440, 2000.

    Article  CAS  PubMed  Google Scholar 

  4. Chang, M. D., S. Shaikh, and T. Chau. Effect of treadmill walking on the stride interval dynamics of human gait. Gait Posture 30:431–435, 2009.

    Article  PubMed  Google Scholar 

  5. Delignieres, D., and K. Torre. Fractal dynamics of human gait: a reassessment of the 1996 data of Hausdorff et al. J. Appl. Physiol. 106:1272–1279, 2009.

    Article  PubMed  Google Scholar 

  6. Dingwell, J. B., and J. P. Cusumano. Re-interpreting detrended fluctuation analyses of stride-to-stride variability in human walking. Gait Posture 32:348–353, 2010.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Dingwell, J. B., and J. P. Cusumano. Identifying stride-to-stride control strategies in human treadmill walking. PLoS ONE 10:e0124879, 2015.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Dingwell, J. B., and L. C. Marin. Kinematic variability and local dynamic stability of upper body motions when walking at different speeds. J. Biomech. 39:444–452, 2006.

    Article  PubMed  Google Scholar 

  9. Dingwell, J. B., J. John, and J. P. Cusumano. Do humans optimally exploit redundancy to control step variability in walking? PLoS Comput. Biol. 6:e1000856, 2010.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Eke, A., P. Herman, L. Kocsis, and L. Kozak. Fractal characterization of complexity in temporal physiological signals. Physiol. Meas. 23:R1, 2002.

    Article  CAS  PubMed  Google Scholar 

  11. Hamacher, D., F. Herold, P. Wiegel, D. Hamacher, and L. Schega. Brain activity during walking: a systematic review. Neurosci. Biobehav. R. 57:310–327, 2015.

    Article  Google Scholar 

  12. Hausdorff, J. M. Gait dynamics, fractals and falls: finding meaning in the stride-to-stride fluctuations of human walking. Hum. Mov. Sci. 26:555–589, 2007.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Hausdorff, J. M. Gait dynamics in Parkinson’s disease: common and distinct behavior among stride length, gait variability, and fractal-like scaling. Chaos 19:026113, 2009.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Hausdorff, J. M., C. K. Peng, Z. Ladin, J. Y. Wei, and A. L. Goldberger. Is walking a random walk? Evidence for long-range correlations in stride interval of human gait. J. Appl. Physiol. 78:349–358, 1995.

    CAS  PubMed  Google Scholar 

  15. Hausdorff, J. M., A. Lertratanakul, M. E. Cudkowicz, A. L. Peterson, D. Kaliton, and A. L. Goldberger. Dynamic markers of altered gait rhythm in amyotrophic lateral sclerosis. J. Appl. Physiol. 88:2045–2053, 2000.

    CAS  PubMed  Google Scholar 

  16. Hausdorff, J. M., J. Lowenthal, T. Herman, L. Gruendlinger, C. Peretz, and N. Giladi. Rhythmic auditory stimulation modulates gait variability in Parkinson’s disease. Eur. J. Neurosci. 26:2369–2375, 2007.

    Article  PubMed  Google Scholar 

  17. Heeren, A., M. W. van Ooijen, A. C. Geurts, B. L. Day, T. W. Janssen, P. J. Beek, M. Roerdink, and V. Weerdesteyn. Step by step: a proof of concept study of C-Mill gait adaptability training in the chronic phase after stroke. J. Rehabil. Med. 45:616–622, 2013.

    Article  PubMed  Google Scholar 

  18. Jordan, K., J. H. Challis, and K. M. Newell. Walking speed influences on gait cycle variability. Gait Posture 26:128–134, 2007.

    Article  PubMed  Google Scholar 

  19. Lewis, G. N., W. D. Byblow, and S. E. Walt. Stride length regulation in Parkinson’s disease: the use of extrinsic, visual cues. Brain 123(Pt 10):2077–2090, 2000.

    Article  PubMed  Google Scholar 

  20. Mandelbrot, B. B. Les objets fractals: forme, hasard et dimension. Flammarion 10:422–437, 1975.

    Google Scholar 

  21. Mandelbrot, B. B., and J. W. Van Ness. Fractional Brownian motions, fractional noises and applications. SIAM Rev 10:422–437, 1968.

    Article  Google Scholar 

  22. Maraun, D., H. W. Rust, and J. Timmer. Tempting long-memory—on the interpretation of DFA results. Nonlinear Proc. Geophys. 11:495–503, 2004.

    Article  Google Scholar 

  23. Marmelat, V., K. Torre, P. J. Beek, and A. Daffertshofer. Persistent fluctuations in stride intervals under fractal auditory stimulation. PLoS ONE 9:e91949, 2014.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Miall, R. C., and D. M. Wolpert. Forward models for physiological motor control. Neural Netw. 9:1265–1279, 1996.

    Article  PubMed  Google Scholar 

  25. Nascimento, L. R., C. Q. de Oliveira, L. Ada, S. M. Michaelsen, and L. F. Teixeira-Salmela. Walking training with cueing of cadence improves walking speed and stride length after stroke more than walking training alone: a systematic review. J. Physiother. 61:10–15, 2015.

    Article  PubMed  Google Scholar 

  26. O’Connor, S. M., H. Z. Xu, and A. D. Kuo. Energetic cost of walking with increased step variability. Gait Posture 36:102–107, 2012.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Owings, T. M., and M. D. Grabiner. Variability of step kinematics in young and older adults. Gait Posture 20:26–29, 2004.

    Article  PubMed  Google Scholar 

  28. Peng, C.-K., S. V. Buldyrev, S. Havlin, M. Simons, H. E. Stanley, and A. L. Goldberger. Mosaic organization of DNA nucleotides. Phys. Rev. E 49:1685, 1994.

    Article  CAS  Google Scholar 

  29. Peng, C. K., S. Havlin, H. E. Stanley, and A. L. Goldberger. Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos 5:82–87, 1995.

    Article  CAS  PubMed  Google Scholar 

  30. Peper, C. L. E., M. J. de Dreu, and M. Roerdink. Attuning one’s steps to visual targets reduces comfortable walking speed in both young and older adults. Gait Posture 41:830–834, 2015.

    Article  PubMed  Google Scholar 

  31. Repp, B. H. Sensorimotor synchronization: a review of the tap** literature. Psychon. Bull. Rev. 12:969–992, 2005.

    Article  PubMed  Google Scholar 

  32. Repp, B. H., and Y.-H. Su. Sensorimotor synchronization: a review of recent research (2006–2012). Psychon. Bull. Rev. 20:403–452, 2013.

    Article  PubMed  Google Scholar 

  33. Roerdink, M., B. H. Coolen, B. H. Clairbois, C. J. Lamoth, and P. J. Beek. Online gait event detection using a large force platform embedded in a treadmill. J. Biomech. 41:2628–2632, 2008.

    Article  PubMed  Google Scholar 

  34. Roerdink, M., A. Daffertshofer, V. Marmelat, and P. J. Beek. How to sync to the beat of a persistent fractal metronome without falling off the treadmill? PLoS ONE 10:e0134148, 2015.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Rossignol, S., R. Dubuc, and J. P. Gossard. Dynamic sensorimotor interactions in locomotion. Physiol. Rev. 86:89–154, 2006.

    Article  PubMed  Google Scholar 

  36. Sejdic, E., Y. Fu, A. Pak, J. A. Fairley, and T. Chau. The effects of rhythmic sensory cues on the temporal dynamics of human gait. PLoS ONE 7:e43104, 2012.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Sidaway, B., J. Anderson, G. Danielson, L. Martin, and G. Smith. Effects of long-term gait training using visual cues in an individual with Parkinson disease. Phys. Ther. 86:186–194, 2006.

    PubMed  Google Scholar 

  38. Terrier, P. Step-to-step variability in treadmill walking: influence of rhythmic auditory cueing. PLoS ONE 7:e47171, 2012.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Terrier, P., and O. Dériaz. Kinematic variability, fractal dynamics and local dynamic stability of treadmill walking. J. Neuroeng. Rehabil. 8:12, 2011.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Terrier, P., and O. Dériaz. Persistent and anti-persistent pattern in stride-to-stride variability of treadmill walking: influence of rythmic auditory cueing. Hum. Mov. Sci. 31:1585–1597, 2012.

    Article  PubMed  Google Scholar 

  41. Terrier, P., and O. Dériaz. Nonlinear dynamics of human locomotion: effects of rhythmic auditory cueing on local dynamic stability. Front. Physiol. 4:230, 2013.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Terrier, P., V. Turner, and Y. Schutz. GPS analysis of human locomotion: further evidence for long-range correlations in stride-to-stride fluctuations of gait parameters. Hum. Mov. Sci. 24:97–115, 2005.

    Article  PubMed  Google Scholar 

  43. Torre, K., D. Delignieres, and L. Lemoine. Detection of long-range dependence and estimation of fractal exponents through ARFIMA modelling. Brit. J. Math. Stat. Psychol. 60:85–106, 2007.

    Article  Google Scholar 

  44. van Ooijen, M. W., A. Heeren, K. Smulders, A. C. Geurts, T. W. Janssen, P. J. Beek, V. Weerdesteyn, and M. Roerdink. Improved gait adjustments after gait adaptability training are associated with reduced attentional demands in persons with stroke. Exp. Brain Res. 233:1007–1018, 2015.

    Article  PubMed  Google Scholar 

  45. van Wegen, E. E., M. A. Hirsch, M. Huiskamp, and G. Kwakkel. Harnessing Cueing Training for Neuroplasticity in Parkinson Disease. Top. Geriatr. Rehabil. 30:46–57, 2014.

    Article  Google Scholar 

  46. West, B. J., and N. Scafetta. Nonlinear dynamical model of human gait. Phys. Rev. E 67:051917, 2003.

    Article  Google Scholar 

  47. Wittwer, J. E., K. E. Webster, and K. Hill. Music and metronome cues produce different effects on gait spatiotemporal measures but not gait variability in healthy older adults. Gait Posture 37:219–222, 2013.

    Article  PubMed  Google Scholar 

  48. Zarrugh, M. Y., F. N. Todd, and H. J. Ralston. Optimization of energy expenditure during level walking. Eur. J. Appl. Physiol. Occup. Physiol. 33:293–306, 1974.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

The author warmly thanks Emilie Du Fay de Lavallaz for his valuable support in bibliographical research and Vincent Bonvin for his help in data collection. The study was funded by the Swiss accident insurance company SUVA, by the Clinique Romande de Réadaptation (CRR), and by the Institute for Research in Rehabilitation (IRR). The IRR is funded by the State of Valais and the City of Sion. Study funders had no role in the collection, analysis, and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication.

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  1. IRR, Institute for Research in Rehabilitation, Sion, Switzerland

    Philippe Terrier

  2. Clinique romande de réadaptation SUVACare, Av. Gd-Champsec 90, 1951, Sion, Switzerland

    Philippe Terrier

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Correspondence to Philippe Terrier.

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Associate Editor Thurmon E. Lockhart oversaw the review of this article.

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Terrier, P. Fractal Fluctuations in Human Walking: Comparison Between Auditory and Visually Guided Step**. Ann Biomed Eng 44, 2785–2793 (2016). https://doi.org/10.1007/s10439-016-1573-y

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