Characterizing Normal and Pathological Gait through Permutation Entropy
Zanin, Massimiliano (Universidade Nova de Lisboa. Faculdade de Ciências e Tecnologia)
Gómez-Andrés, David (Hospital Universitari Vall d'Hebron)
Pulido-Valdeolivas, Irene (Institut d'Investigacions Biomèdiques August Pi i Sunyer)
Martín-Gonzalo, Juan Andrés (Escuela Universitaria de Fisioterapia de la ONCE-UAM, 28034 Madrid, Spain)
López-López, Javier (Hospital Universitario Infanta Sofía (San Sebastián de los Reyes))
Pascual-Pascual, Samuel Ignacio (Hospital Universitario La Paz (Madrid))
Rausell, Estrella (Universidad Autónoma de Madrid. Departamento de Anatomía, Histología y Neurociencia)
Universitat Autònoma de Barcelona

Date:	2018
Abstract:	Cerebral palsy is a physical impairment stemming from a brain lesion at perinatal time, most of the time resulting in gait abnormalities: the first cause of severe disability in childhood. Gait study, and instrumental gait analysis in particular, has been receiving increasing attention in the last few years, for being the complex result of the interactions between different brain motor areas and thus a proxy in the understanding of the underlying neural dynamics. Yet, and in spite of its importance, little is still known about how the brain adapts to cerebral palsy and to its impaired gait and, consequently, about the best strategies for mitigating the disability. In this contribution, we present the hitherto first analysis of joint kinematics data using permutation entropy, comparing cerebral palsy children with a set of matched control subjects. We find a significant increase in the permutation entropy for the former group, thus indicating a more complex and erratic neural control of joints and a non-trivial relationship between the permutation entropy and the gait speed. We further show how this information theory measure can be used to train a data mining model able to forecast the child's condition. We finally discuss the relevance of these results in clinical applications and specifically in the design of personalized medicine interventions.
Grants:	Instituto de Salud Carlos III PI05-90123
Note:	Altres ajuts: We acknowledge the contribution of the children and their families who generously collaborated to build the gait dataset used in this study. We are also grateful to Michael R. Paul for kindly editing the English style of this manuscript. The acquisition and processing of gait data were funded by Escuela de Fisioterapia de la ONCE-UAM, through a private donation, and Agencia de Evaluación de Tecnologías Sanitarias (Instituto de Salud Carlos III), .
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Permutation entropy ; Cerebral palsy ; Instrumental gait analysis
Published in:	Entropy, Vol. 20 (january 2018) , ISSN 1099-4300

DOI: 10.3390/e20010077
PMID: 33265160

19 p, 1.0 MB

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