Changes of human movement complexity during maturation: quantitative assessment using multiscale entropy

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.

[1]  P. Beek,et al.  Children with cerebral palsy exhibit greater and more regular postural sway than typically developing children , 2007, Experimental Brain Research.

[2]  Elliot Saltzman,et al.  Discovery of the Pendulum and Spring Dynamics in the Early Stages of Walking , 2006, Journal of motor behavior.

[3]  Karen Hooker,et al.  Handbook of Intraindividual Variability Across the Life Span , 2014 .

[4]  Thomas D Brown,et al.  Entropy analysis of tri‐axial leg acceleration signal waveforms for measurement of decrease of physiological variability in human gait , 2012, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[5]  M. C. Bisi,et al.  Measures of gait stability: performance on adults and toddlers at the beginning of independent walking , 2014, Journal of NeuroEngineering and Rehabilitation.

[6]  Kamiar Aminian,et al.  Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes. , 2002, Journal of biomechanics.

[7]  C. Lamoth,et al.  Gait stability and variability measures show effects of impaired cognition and dual tasking in frail people , 2011, Journal of NeuroEngineering and Rehabilitation.

[8]  Subhabrata Chakraborti,et al.  Nonparametric Statistical Inference , 2011, International Encyclopedia of Statistical Science.

[9]  I. McKinley.  The Development of Mature Walking , 1989 .

[10]  Maria Cristina Bisi,et al.  Development of gait motor control: what happens after a sudden increase in height during adolescence? , 2016, Biomedical engineering online.

[11]  H. Houdijk,et al.  Variability and stability analysis of walking of transfemoral amputees. , 2010, Medical engineering & physics.

[12]  Sally Goddard Blythe.  Neuromotor Immaturity in Children and Adults: The INPP Screening Test for Clinicians and Health Practitioners , 2014 .

[13]  L. Rochester,et al.  Walking in the real world: concepts related to functional gait , 2007 .

[14]  Kate Smith-Miles.  Exploratory data analysis , 2011 .

[15]  E K Antonsson,et al.  The frequency content of gait. , 1985, Journal of biomechanics.

[16]  Nicolas Vuillerme,et al.  Multiscale and Shannon entropies during gait as fall risk predictors-A prospective study. , 2017, Gait & posture.

[17]  Fabio Storm,et al.  Moving from laboratory to real life conditions: Influence on the assessment of variability and stability of gait. , 2018, Gait & posture.

[18]  E. Spada,et al.  Italian cross-sectional growth charts for height, weight and BMI (2 to 20 yr) , 2006, Journal of endocrinological investigation.

[19]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

[20]  P. Beek,et al.  Assessing the stability of human locomotion: a review of current measures , 2013, Journal of The Royal Society Interface.

[21]  B. Vereijken.  The Complexity of Childhood Development: Variability in Perspective , 2010, Physical Therapy.

[22]  Nicholas Stergiou,et al.  Nonlinear Analysis for Human Movement Variability , 2016 .

[23]  Alan Bourke,et al.  The complexity of daily life walking in older adult community-dwelling fallers and non-fallers. , 2016, Journal of biomechanics.

[24]  Jeffrey M. Hausdorff,et al.  Multiscale entropy analysis of human gait dynamics. , 2003, Physica A.

[25]  Melvyn Roerdink,et al.  Regularity of center-of-pressure trajectories depends on the amount of attention invested in postural control , 2007, Experimental Brain Research.

[26]  R. Harbourne,et al.  Variability in Postural Control During Infancy: Implications for Development, Assessment, and Intervention , 2010, Physical Therapy.

[27]  W. Kruskal,et al.  Use of Ranks in One-Criterion Variance Analysis , 1952 .

[28]  Anil K. Bera,et al.  A test for normality of observations and regression residuals , 1987 .

[29]  Mijna Hadders-Algra,et al.  Variation and Variability: Key Words in Human Motor Development , 2010, Physical Therapy.

[30]  M. C. Bisi,et al.  Complexity of human gait pattern at different ages assessed using multiscale entropy: From development to decline. , 2016, Gait & posture.

[31]  K. Newell,et al.  Changing complexity in human behavior and physiology through aging and disease , 2002, Neurobiology of Aging.