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J. A. Martín
Escuela de Fisioterapia de la ONCE, Universidad Autónoma de Madrid, España

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Journal article
Published: 23 December 2020 in Revista Iberoamericana de Automática e Informática industrial
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Un exoesqueleto robótico es un dispositivo electromecánico utilizado para aumentar la capacidad física de una persona, como ayuda a la locomoción o para procesos de rehabilitación de la marcha. En el caso de los exoesqueletos de rehabilitación se requiere que el sistema de control sea capaz de adaptarse adecuadamente a la evolución del paciente con el fin de optimizar su recuperación, esto implica el diseño de controladores robustos y precisos. En este trabajo se presenta el análisis cinemático, análisis dinámico y evaluación del sistema de control del exoesqueleto de rehabilitación ALICE. Dentro de las técnicas de control presentadas se encuentran: el controlador PD, PD adaptativo, y el controlador en modo deslizante. Además, se realiza un análisis de estabilidad utilizando el criterio de Lyapunov. Para probar el rendimiento de los reguladores, se utiliza un conjunto de datos de la Escuela de Fisioterapia de la ONCE de Madrid, correspondiente a personas sanas y personas con esclerosis múltiple. Se utiliza MATLAB como software de simulación y lenguaje de programación.

ACS Style

M. Cardona; F. Serrano; J. A. Martín; E. Rausell; R. Saltaren; C. García-Cena. El exoesqueleto de rehabilitación de la marcha ALICE: análisis dinámico y evaluación del sistema de control utilizando cuaternios de Hamilton. Revista Iberoamericana de Automática e Informática industrial 2020, 18, 48 -57.

AMA Style

M. Cardona, F. Serrano, J. A. Martín, E. Rausell, R. Saltaren, C. García-Cena. El exoesqueleto de rehabilitación de la marcha ALICE: análisis dinámico y evaluación del sistema de control utilizando cuaternios de Hamilton. Revista Iberoamericana de Automática e Informática industrial. 2020; 18 (1):48-57.

Chicago/Turabian Style

M. Cardona; F. Serrano; J. A. Martín; E. Rausell; R. Saltaren; C. García-Cena. 2020. "El exoesqueleto de rehabilitación de la marcha ALICE: análisis dinámico y evaluación del sistema de control utilizando cuaternios de Hamilton." Revista Iberoamericana de Automática e Informática industrial 18, no. 1: 48-57.

Journal article
Published: 06 September 2019 in Entropy
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Gait is a basic cognitive purposeful action that has been shown to be altered in late stages of neurodegenerative dementias. Nevertheless, alterations are less clear in mild forms of dementia, and the potential use of gait analysis as a biomarker of initial cognitive decline has hitherto mostly been neglected. Herein, we report the results of a study of gait kinematic time series for two groups of patients (mild cognitive impairment and mild Alzheimer’s disease) and a group of matched control subjects. Two metrics based on permutation patterns are considered, respectively measuring the complexity and irreversibility of the time series. Results indicate that kinematic disorganisation is present in early phases of cognitive impairment; in addition, they depict a rich scenario, in which some joint movements display an increased complexity and irreversibility, while others a marked decrease. Beyond their potential use as biomarkers, complexity and irreversibility metrics can open a new door to the understanding of the role of the nervous system in gait, as well as its adaptation and compensatory mechanisms.

ACS Style

Juan-Andrés Martín-Gonzalo; Irene Pulido-Valdeolivas; Yu Wang; Ting Wang; Guadalupe Chiclana-Actis; Maria Del Carmen Algarra-Lucas; Itziar Palmí-Cortés; Jorge Fernández Travieso; Maria Dolores Torrecillas-Narváez; Ambrosio A. Miralles-Martinez; Estrella Rausell; David Gómez-Andrés; Massimiliano Zanin. Permutation Entropy and Irreversibility in Gait Kinematic Time Series from Patients with Mild Cognitive Decline and Early Alzheimer’s Dementia. Entropy 2019, 21, 868 .

AMA Style

Juan-Andrés Martín-Gonzalo, Irene Pulido-Valdeolivas, Yu Wang, Ting Wang, Guadalupe Chiclana-Actis, Maria Del Carmen Algarra-Lucas, Itziar Palmí-Cortés, Jorge Fernández Travieso, Maria Dolores Torrecillas-Narváez, Ambrosio A. Miralles-Martinez, Estrella Rausell, David Gómez-Andrés, Massimiliano Zanin. Permutation Entropy and Irreversibility in Gait Kinematic Time Series from Patients with Mild Cognitive Decline and Early Alzheimer’s Dementia. Entropy. 2019; 21 (9):868.

Chicago/Turabian Style

Juan-Andrés Martín-Gonzalo; Irene Pulido-Valdeolivas; Yu Wang; Ting Wang; Guadalupe Chiclana-Actis; Maria Del Carmen Algarra-Lucas; Itziar Palmí-Cortés; Jorge Fernández Travieso; Maria Dolores Torrecillas-Narváez; Ambrosio A. Miralles-Martinez; Estrella Rausell; David Gómez-Andrés; Massimiliano Zanin. 2019. "Permutation Entropy and Irreversibility in Gait Kinematic Time Series from Patients with Mild Cognitive Decline and Early Alzheimer’s Dementia." Entropy 21, no. 9: 868.

Journal article
Published: 19 January 2018 in Entropy
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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.

ACS Style

Massimiliano Zanin; David Gómez-Andrés; Irene Pulido-Valdeolivas; Juan Andrés Martín-Gonzalo; Javier López-López; Samuel Ignacio Pascual-Pascual; Estrella Rausell. Characterizing Normal and Pathological Gait through Permutation Entropy. Entropy 2018, 20, 77 .

AMA Style

Massimiliano Zanin, David Gómez-Andrés, Irene Pulido-Valdeolivas, Juan Andrés Martín-Gonzalo, Javier López-López, Samuel Ignacio Pascual-Pascual, Estrella Rausell. Characterizing Normal and Pathological Gait through Permutation Entropy. Entropy. 2018; 20 (1):77.

Chicago/Turabian Style

Massimiliano Zanin; David Gómez-Andrés; Irene Pulido-Valdeolivas; Juan Andrés Martín-Gonzalo; Javier López-López; Samuel Ignacio Pascual-Pascual; Estrella Rausell. 2018. "Characterizing Normal and Pathological Gait through Permutation Entropy." Entropy 20, no. 1: 77.