Human Postural Control: Assessment of Two Alternative Interpretations of Center of Pressure Sample Entropy through a Principal Component Factorization of Whole-Body Kinematics

Sample entropy (SaEn), calculated for center of pressure (COP) trajectories, is often distinct for compromised postural control, e.g., in Parkinson, stroke, or concussion patients, but the interpretation of COP-SaEn remains subject to debate. The purpose of this paper is to test the hypotheses that COP-SaEn is related (Hypothesis 1; H1) to the complexity of the postural movement structures, i.e., to the utilization and coordination of the mechanical degrees of freedom; or (Hypothesis 2; H2) to the irregularity of the individual postural movement strategies, i.e., to the neuromuscular control of these movements. Twenty-one healthy volunteers (age 26.4 ± 2.4; 10 females), equipped with 27 reflective markers, stood on a force plate and performed 2-min quiet stances. Principal movement strategies (PMs) were obtained from a principal component analysis (PCA) of the kinematic data. Then SaEn was calculated for the COP and PM time-series. H1 was tested by correlating COP-SaEn to the relative contribution of the PMs to the subject specific overall movement and H2 by correlating COP-SaEn and PM-SaEn. Both hypotheses were supported. This suggests that in a healthy population the COP-SaEn is linked to the complexity of the coordinative structure of postural movements, as well as to the irregularity of the neuromuscular control of specific movement components.

[1]  Michael I. Jordan,et al.  Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.

[2]  Madalena Costa,et al.  Multiscale entropy analysis of biological signals. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  R. Enoka,et al.  Human motor unit recordings: Origins and insight into the integrated motor system , 2011, Brain Research.

[4]  U. Lindenberger,et al.  Interacting effects of cognitive load and adult age on the regularity of whole-body motion during treadmill walking. , 2009, Psychology and aging.

[5]  J Browne,et al.  A quality control procedure for force platforms. , 2000, Physiological measurement.

[6]  Richard E.A. van Emmerik,et al.  Multiscale entropy: A tool for understanding the complexity of postural control , 2016, Journal of sport and health science.

[7]  S. Marshall,et al.  Detecting altered postural control after cerebral concussion in athletes with normal postural stability , 2005, British Journal of Sports Medicine.

[8]  Mamede de Carvalho,et al.  Motor unit firing in amyotrophic lateral sclerosis and other upper and lower motor neurone disorders , 2012, Clinical Neurophysiology.

[9]  B. Nigg,et al.  Analysis of the multi-segmental postural movement strategies utilized in bipedal, tandem and one-leg stance as quantified by a principal component decomposition of marker coordinates. , 2013, Journal of biomechanics.

[10]  Danae M. Dinkel,et al.  Postural control strategies differ in normal weight and overweight infants. , 2017, Gait & posture.

[11]  Raimon Jané,et al.  Influence of Parameter Selection in Fixed Sample Entropy of Surface Diaphragm Electromyography for Estimating Respiratory Activity , 2017, Entropy.

[12]  Nicholas Stergiou,et al.  Recovery of postural control after cerebral concussion: new insights using approximate entropy. , 2006, Journal of athletic training.

[13]  Joseph Hamill,et al.  Multiscale entropy identifies differences in complexity in postural control in women with multiple sclerosis. , 2016, Gait & posture.

[14]  Yang Yang,et al.  Evaluating Human Motion Complexity Based on Un-Correlation and Non-smoothness , 2010, PCM.

[15]  Bernard C. Jiang,et al.  Resistance Training Exercise Program for Intervention to Enhance Gait Function in Elderly Chronically Ill Patients: Multivariate Multiscale Entropy for Center of Pressure Signal Analysis , 2014, Comput. Math. Methods Medicine.

[16]  Øyvind Gløersen,et al.  Technique analysis in elite athletes using principal component analysis , 2018, Journal of sports sciences.

[17]  James M. Wakeling,et al.  Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals , 2017, Front. Physiol..

[18]  Frédéric Bouchara,et al.  On the use of sample entropy to analyze human postural sway data. , 2009, Medical engineering & physics.

[19]  J. Frère,et al.  Dynamical analysis of balance in vestibular schwannoma patients. , 2017, Gait & posture.

[20]  Shinichi Amano,et al.  Decreased dynamical complexity during quiet stance in children with autism spectrum disorders. , 2014, Gait & posture.

[21]  N. Ichihashi,et al.  Correlation between movement complexity during static standing and balance function in institutionalized older adults , 2017, Clinical interventions in aging.

[22]  Avril Mansfield,et al.  Visual feedback of the centre of gravity to optimize standing balance. , 2015, Gait & posture.

[23]  Volker Dürr,et al.  Inter-joint coupling and joint angle synergies of human catching movements. , 2010, Human movement science.

[24]  Annie Schmied,et al.  Approximate entropy of motoneuron firing patterns during a motor preparation task , 2008, Journal of Neuroscience Methods.

[25]  Michael Ab,et al.  Non-Linear Techniques Reveal Adaptive and Maladaptive Postural Control Dynamics in Persons with Multiple Sclerosis , 2016 .

[26]  Andreas Daffertshofer,et al.  PCA in studying coordination and variability: a tutorial. , 2004, Clinical biomechanics.

[27]  N. Troje Decomposing biological motion: a framework for analysis and synthesis of human gait patterns. , 2002, Journal of vision.

[28]  Jianbo Gao,et al.  Shannon and Renyi Entropies to Classify Effects of Mild Traumatic Brain Injury on Postural Sway , 2011, PloS one.

[29]  Alexander S. Aruin,et al.  Frequency analysis approach to study balance control in individuals with multiple sclerosis , 2014, Journal of Neuroscience Methods.

[30]  Peter A Federolf A novel approach to study human posture control: "Principal movements" obtained from a principal component analysis of kinematic marker data. , 2016, Journal of biomechanics.

[31]  Nicholas Stergiou,et al.  Approximate entropy detects the effect of a secondary cognitive task on postural control in healthy young adults: a methodological report , 2007, Journal of NeuroEngineering and Rehabilitation.

[32]  P. Goldie,et al.  Force platform measures for evaluating postural control: reliability and validity. , 1989, Archives of physical medicine and rehabilitation.

[33]  Peter Federolf,et al.  A holistic approach to study the temporal variability in gait. , 2012, Journal of biomechanics.

[34]  L. Mainwaring,et al.  Heart Rate Variability of Athletes Across Concussion Recovery Milestones: A Preliminary Study , 2017, Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine.

[35]  Brice Isableu,et al.  Sample Entropy, Univariate, and Multivariate Multi-Scale Entropy in Comparison with Classical Postural Sway Parameters in Young Healthy Adults , 2017, Front. Hum. Neurosci..