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      Sub-sensory vibratory noise augments the physiologic complexity of postural control in older adults

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          Abstract

          Background

          Postural control requires numerous inputs interacting across multiple temporospatial scales. This organization, evidenced by the “complexity” contained within standing postural sway fluctuations, enables diverse system functionality. Age-related reduction of foot-sole somatosensation reduces standing postural sway complexity and diminishes the functionality of the postural control system. Sub-sensory vibrations applied to the foot soles reduce the speed and magnitude of sway and improve mobility in older adults. We thus hypothesized that these vibration-induced improvements to the functionality of the postural control system are associated with an increase in the standing postural sway complexity.

          Method

          Twelve healthy older adults aged 74 ± 8 years completed three visits to test the effects of foot sole vibrations at 0 % (i.e., no vibration), 70 and 85 % of the sensory threshold. Postural sway was assessed during eyes-open and eyes-closed standing. The complexity of sway time-series was quantified using multiscale entropy. The timed up-and-go (TUG) was completed to assess mobility.

          Results

          When standing without vibration, participants with lower foot sole vibratory thresholds (better sensation) had greater mediolateral (ML) sway complexity ( r 2 = 0.49, p < 0.001), and those with greater ML sway complexity had faster TUG times (better mobility) ( r 2 = 0.38, p < 0.001). Foot sole vibrations at 70 and 85 % of sensory threshold increased ML sway complexity during eyes-open and eyes-closed standing ( p < 0.0001). Importantly, these vibration-induced increases in complexity correlated with improvements in the TUG test of mobility ( r 2 = 0.15 ~ 0.42, p < 0.001 ~ 0.03).

          Conclusions

          Sub-sensory foot sole vibrations augment the postural control system functionality and such beneficial effects are reflected in an increase in the physiologic complexity of standing postural sway dynamics.

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          Most cited references24

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          Stochastic resonance

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            Multiscale entropy analysis of biological signals

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              Multiscale entropy analysis of complex physiologic time series.

              There has been considerable interest in quantifying the complexity of physiologic time series, such as heart rate. However, traditional algorithms indicate higher complexity for certain pathologic processes associated with random outputs than for healthy dynamics exhibiting long-range correlations. This paradox may be due to the fact that conventional algorithms fail to account for the multiple time scales inherent in healthy physiologic dynamics. We introduce a method to calculate multiscale entropy (MSE) for complex time series. We find that MSE robustly separates healthy and pathologic groups and consistently yields higher values for simulated long-range correlated noise compared to uncorrelated noise.
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                Author and article information

                Contributors
                1-617-971-5346 , 1-617-971-5339 , JunhongZhou@hsl.harvard.edu
                Journal
                J Neuroeng Rehabil
                J Neuroeng Rehabil
                Journal of NeuroEngineering and Rehabilitation
                BioMed Central (London )
                1743-0003
                3 May 2016
                3 May 2016
                2016
                : 13
                : 44
                Affiliations
                [ ]Institute for Aging Research, Hebrew SeniorLife, Roslindale, MA USA
                [ ]Beth Israel Deaconess Medical Center, Boston, MA 02131 USA
                [ ]Harvard Medical School, 1200 Centre Street, Boston, MA 02131 USA
                Article
                152
                10.1186/s12984-016-0152-7
                4855814
                27142280
                3b34887c-91cc-4f95-a7d2-effd167d996b
                © Zhou et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 23 December 2015
                : 22 April 2016
                Funding
                Funded by: Merck Sharp and Dohme
                Funded by: the National Institute on Aging
                Award ID: AG025037/AGO41785
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100007299, Harvard Catalyst;
                Award ID: 1KL2RR025757-04
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

                Neurosciences
                stochastic resonance,vibration,somatosensation,postural sway,multiscale entropy
                Neurosciences
                stochastic resonance, vibration, somatosensation, postural sway, multiscale entropy

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