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Control Entropy: What Is It and What Does It Tell Us?

Complex tasks of motor control in humans, such as locomotion or postural control, exhibit patterns of variability that until recently have been indiscernible from random noise. Tools from the field of non-linear dynamical systems have been increasingly applied to measurements of these tasks and chan...

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Published in:Clinical Kinesiology (Online Edition) Vol. 66; no. 1; pp. 7 - 13
Main Authors: McGregor, Stephen J., Bollt, Erik
Format: equations & formulas tables/charts Journal Article
Published: American Kinesiotherapy Association Spring2012
Online Access:View this record in EBSCOhost
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      dt: Spring2012
      vid: 66
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      pub: American Kinesiotherapy Association
      place: Hattiesburg, Mississippi
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        atl: Control Entropy: What Is It and What Does It Tell Us?
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          McGregor, Stephen J.
          Bollt, Erik
        affil: Human Factors-Dynamical Systems Laboratory, Eastern Michigan University, Ypsilanti, MI
      sug:
        subj:
          Balance, Postural Evaluation
          Neuromuscular Control Evaluation
          Movement Evaluation
          Exercise Physiology
          Data Analysis, Statistical Methods
          Biological Phenomena
          Walking
          Running
          Fatigue
          Exercise Test
      ab: Complex tasks of motor control in humans, such as locomotion or postural control, exhibit patterns of variability that until recently have been indiscernible from random noise. Tools from the field of non-linear dynamical systems have been increasingly applied to measurements of these tasks and changes in these complex patterns have been identified. A particular tool, control entropy (CE), is a measure of the regularity, or conversely, the complexity of a signal and is used to infer the constraints present on a system. More importantly, CE can be used under nonstationary conditions, and can therefore identify changes in the complexity or constraints on a system under dynamic exercise conditions. In this review, we summarize the insight that has been gained from application of CE to signals from studies involving walking, running and postural control. We show that changing constraints can be identified during dynamic exercise and that these are reflected in changing CE. We also discuss how CE can identify increased complexity of tasks such as postural control in the fatigued state.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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