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Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running

Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit “fractality”—a specific temporal structure in consecutive str...

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Autores principales: Wilson, Taylor J., Mangalam, Madhur, Stergiou, Nick, Likens, Aaron D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10621042/
https://www.ncbi.nlm.nih.gov/pubmed/37928059
http://dx.doi.org/10.3389/fnetp.2023.1294545
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author Wilson, Taylor J.
Mangalam, Madhur
Stergiou, Nick
Likens, Aaron D.
author_facet Wilson, Taylor J.
Mangalam, Madhur
Stergiou, Nick
Likens, Aaron D.
author_sort Wilson, Taylor J.
collection PubMed
description Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit “fractality”—a specific temporal structure in consecutive strides that are ordered, stable but also variable, and adaptable. Previous research has primarily focused on a single fractality measure, “monofractality.” However, this measure can vary across time; strideto-stride variations can show “multifractality.” Greater multifractality in stride-tostride variations would highlight the ability to tune and adjust movements more. Methods: We investigated monofractality and multifractality in a cohort of eight healthy adults during self-paced walking and running trials, both on a treadmill and overground. Footfall data were collected through force-sensitive sensors positioned on their heels and feet. We examined the effects of self-paced walking vs. running and treadmill vs. overground locomotion on the measure of monofractality, α-DFA, in addition to the multifractal spectrum width, W, and the asymmetry in the multifractal spectrum, W (Asym) , of stride interval time series. Results: While the α-DFA was larger than 0.50 for almost all conditions, α-DFA was higher in running and locomoting overground than walking and locomoting on a treadmill. Similarly, W was greater while locomoting overground than on a treadmill, but an opposite trend indicated that W was greater in walking than running. Larger W (Asym) values in the negative direction suggest that walking exhibits more variation in the persistence of shorter stride intervals than running. However, the ability to tune and adjust movements does not differ between treadmill and overground, although both exhibit more variation in the persistence of shorter stride intervals. Discussion: Hence, greater heterogeneity in shorter than longer stride intervals contributed to greater multifractality in walking compared to running, indicated by larger negative W (Asym) values. Our results highlight the need to incorporate multifractal methods to test the predictions of the OMVH.
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spelling pubmed-106210422023-11-03 Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running Wilson, Taylor J. Mangalam, Madhur Stergiou, Nick Likens, Aaron D. Front Netw Physiol Network Physiology Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit “fractality”—a specific temporal structure in consecutive strides that are ordered, stable but also variable, and adaptable. Previous research has primarily focused on a single fractality measure, “monofractality.” However, this measure can vary across time; strideto-stride variations can show “multifractality.” Greater multifractality in stride-tostride variations would highlight the ability to tune and adjust movements more. Methods: We investigated monofractality and multifractality in a cohort of eight healthy adults during self-paced walking and running trials, both on a treadmill and overground. Footfall data were collected through force-sensitive sensors positioned on their heels and feet. We examined the effects of self-paced walking vs. running and treadmill vs. overground locomotion on the measure of monofractality, α-DFA, in addition to the multifractal spectrum width, W, and the asymmetry in the multifractal spectrum, W (Asym) , of stride interval time series. Results: While the α-DFA was larger than 0.50 for almost all conditions, α-DFA was higher in running and locomoting overground than walking and locomoting on a treadmill. Similarly, W was greater while locomoting overground than on a treadmill, but an opposite trend indicated that W was greater in walking than running. Larger W (Asym) values in the negative direction suggest that walking exhibits more variation in the persistence of shorter stride intervals than running. However, the ability to tune and adjust movements does not differ between treadmill and overground, although both exhibit more variation in the persistence of shorter stride intervals. Discussion: Hence, greater heterogeneity in shorter than longer stride intervals contributed to greater multifractality in walking compared to running, indicated by larger negative W (Asym) values. Our results highlight the need to incorporate multifractal methods to test the predictions of the OMVH. Frontiers Media S.A. 2023-10-19 /pmc/articles/PMC10621042/ /pubmed/37928059 http://dx.doi.org/10.3389/fnetp.2023.1294545 Text en Copyright © 2023 Wilson, Mangalam, Stergiou and Likens. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Network Physiology
Wilson, Taylor J.
Mangalam, Madhur
Stergiou, Nick
Likens, Aaron D.
Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running
title Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running
title_full Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running
title_fullStr Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running
title_full_unstemmed Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running
title_short Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running
title_sort multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running
topic Network Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10621042/
https://www.ncbi.nlm.nih.gov/pubmed/37928059
http://dx.doi.org/10.3389/fnetp.2023.1294545
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