Changes of human movement complexity during maturation: quantitative assessment using multiscale entropy
M. C. Bisi and
R. Stagni
Computer Methods in Biomechanics and Biomedical Engineering, 2018, vol. 21, issue 4, 325-331
Abstract:
Movement complexity can be defined as the capability of using different strategies to accomplish a specific task and is expected to increase with maturation, reaching its highest level in adulthood.Multiscale Entropy (MSE) has been proposed to estimate complexity on different kinematic signals, at different time scales. When applied on trunk acceleration data during natural walking (NW) at different ages, MSE decreased from childhood to adulthood, apparently contradicting the premises. On the contrary, authors hypothesised that this decrease was dependent on the specific task analysed and resulted from the concurrent increase in gait automaticity.This work aims to test this hypothesis, applying MSE on a non-paradigmatic task (tandem walking, TW), in order to exclude aspects related to automaticity.MSE was estimated on trunk acceleration data, collected on children, adolescents, and young adults during TW and NW. As hypothesized, MSE increased significantly with age in TW and decreased in NW on the sagittal plane. Assuming the development of complexity in TW as reference, MSE in NW showed a reduction to half of the complexity of TW with maturation on the sagittal plane. These results indicate MSE as sensitive to differences in performance due to maturation and to expected changes in complexity related to the specific performed task.
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2018.1448392 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:21:y:2018:i:4:p:325-331
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20
DOI: 10.1080/10255842.2018.1448392
Access Statistics for this article
Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton
More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().