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Frequency-Specific Fractal Analysis of Postural Control Accounts for Control Strategies

Overview of attention for article published in Frontiers in Physiology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Frequency-Specific Fractal Analysis of Postural Control Accounts for Control Strategies
Published in
Frontiers in Physiology, March 2018
DOI 10.3389/fphys.2018.00293
Pubmed ID
Authors

Pierre Gilfriche, Véronique Deschodt-Arsac, Estelle Blons, Laurent M. Arsac

Abstract

Diverse indicators of postural control in Humans have been explored for decades, mostly based on the trajectory of the center-of-pressure. Classical approaches focus on variability, based on the notion that if a posture is too variable, the subject is not stable. Going deeper, an improved understanding of underlying physiology has been gained from studying variability in different frequency ranges, pointing to specific short-loops (proprioception), and long-loops (visuo-vestibular) in neural control. More recently, fractal analyses have proliferated and become useful additional metrics of postural control. They allowed identifying two scaling phenomena, respectively in short and long timescales. Here, we show that one of the most widely used methods for fractal analysis, Detrended Fluctuation Analysis, could be enhanced to account for scalings on specific frequency ranges. By computing and filtering a bank of synthetic fractal signals, we established how scaling analysis can be focused on specific frequency components. We called the obtained method Frequency-specific Fractal Analysis (FsFA) and used it to associate the two scaling phenomena of postural control to proprioceptive-based control loop and visuo-vestibular based control loop. After that, convincing arguments of method validity came from an application on the study of unaltered vs. altered postural control in athletes. Overall, the analysis suggests that at least two timescales contribute to postural control: a velocity-based control in short timescales relying on proprioceptive sensors, and a position-based control in longer timescales with visuo-vestibular sensors, which is a brand-new vision of postural control. Frequency-specific scaling exponents are promising markers of control strategies in Humans.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 84 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 23%
Researcher 9 11%
Professor > Associate Professor 7 8%
Student > Doctoral Student 7 8%
Student > Bachelor 7 8%
Other 13 15%
Unknown 22 26%
Readers by discipline Count As %
Engineering 12 14%
Sports and Recreations 10 12%
Nursing and Health Professions 9 11%
Neuroscience 8 10%
Psychology 4 5%
Other 12 14%
Unknown 29 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 July 2018.
All research outputs
#5,178,591
of 24,597,084 outputs
Outputs from Frontiers in Physiology
#2,646
of 15,110 outputs
Outputs of similar age
#94,041
of 334,256 outputs
Outputs of similar age from Frontiers in Physiology
#94
of 418 outputs
Altmetric has tracked 24,597,084 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,110 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 334,256 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 418 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.