Evidence map›Paper›PMID 32351405›Full record

ArticleFrontiers in physiology2020

Fractal Analysis of Human Gait Variability via Stride Interval Time Series.

Angkoon Phinyomark, Robyn Larracy, Erik Scheme

Abstract read
In one paragraph

Article in Frontiers in physiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Assessing running stability: a systematic review of methods.BMC sports science, medicine & rehabilitation · 2026
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  7. Subtle to significant: Enhancing heaviness perception with stochastic resonance.Journal of experimental psychology. Human perception and performance · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Angkoon PhinyomarkInstitute of Biomedical Engineering, University of New Brunswick, Fredericton, NB, Canada.
Robyn LarracyInstitute of Biomedical Engineering, University of New Brunswick, Fredericton, NB, Canada.
Erik SchemeInstitute of Biomedical Engineering, University of New Brunswick, Fredericton, NB, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fractal analysis of stride interval time series is a useful tool in human gait research which could be used as a marker for gait adaptability, gait disorder, and fall risk among patients with movement disorders. This study is designed to systematically and comprehensively investigate two practical aspects of fractal analysis which significantly affect the outcome: the series length and the parameters used in the algorithm. The Hurst exponent, scaling exponent, and/or fractal dimension are computed from both simulated and experimental data using three fractal methods, namely detrended fluctuation analysis, box-counting dimension, and Higuchi's fractal dimension. The advantages and drawbacks of each method are discussed, in terms of biases and variability. The results demonstrate that a careful selection of fractal analysis methods and their parameters is required, which is dependent on the aim of study (either analyzing differences between experimental groups or estimating an accurate determination of fractal features). A set of guidelines for the selection of the fractal methods and the length of stride interval time series is provided, along with the optimal parameters for a robust implementation for each method.

Indexed as

box-counting dimensiondetrended fluctuation analysisgait analysisgait variabilityHiguchi's fractal dimensionhurst exponentnonlinear dynamicsstride interval time series

Identifiers

PMID32351405
PMCPMC7174763

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.