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A surrogate technique for investigating deterministic dynamics in discrete human movement
Taylor, Paul G. Small, Michael Lee, Kwee-Yum Landeo, Raul O'Meara, Damien M. Millett, Emma L.
Taylor, Paul G.
Small, Michael
Lee, Kwee-Yum
Landeo, Raul
O'Meara, Damien M.
Millett, Emma L.
Abstract
Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.
Keywords
Date
2016
Type
Journal article
Journal
Motor Control
Book
Volume
20
Issue
4
Page Range
459-470
Article Number
ACU Department
School of Behavioural and Health Sciences
Faculty of Health Sciences
Faculty of Health Sciences
Relation URI
Source URL
Event URL
Open Access Status
Published as green open access
License
File Access
Open
Controlled
Controlled
Notes
Authors accepted manuscript - as accepted for publication. © 2016 Human Kinetics, Inc.