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dc.contributor.author | Cevallos, Daniel | es_ES |
dc.contributor.author | Martín, César A. | es_ES |
dc.contributor.author | El Mistiri, Mohamed | es_ES |
dc.contributor.author | Rivera, Daniel E. | es_ES |
dc.contributor.author | Hekler, Eric | es_ES |
dc.date.accessioned | 2022-10-04T12:52:02Z | |
dc.date.available | 2022-10-04T12:52:02Z | |
dc.date.issued | 2022-06-29 | |
dc.identifier.issn | 1697-7912 | |
dc.identifier.uri | http://hdl.handle.net/10251/186933 | |
dc.description.abstract | [EN] Physical inactivity is a major contributor to morbidity and mortality worldwide. Many current physical activity behavioral interventions have shown limited success addressing the problem from a long-term perspective that includes maintenance. This paper proposes the design of a decision algorithm for a mobile and wireless health (mHealth) adaptive intervention that is based on control engineering concepts. The design process relies on a behavioral dynamical model based on Social Cognitive Theory (SCT), with a controller formulation based on hybrid model predictive control (HMPC) being used to implement the decision scheme. The discrete and logical features of HMPC coincide naturally with the categorical nature of the intervention components and the logical decisions that are particular to an intervention for physical activity. The intervention incorporates an online controller reconfiguration mode that applies changes in the penalty weights to accomplish the transition between the behavioral initiation and maintenance training stages. Controller performance is illustrated using an ARX model estimated from system identification data of a representative participant for Just Walk, a physical activity intervention designed on the basis of control systems principles. | es_ES |
dc.description.abstract | [ES] La inactividad física es uno de los principales factores que contribuyen a la morbilidad y la mortalidad en todo el mundo. Muchas intervenciones comportamentales de actividad física en la actualidad han mostrado un éxito limitado al abordar el problema desde una perspectiva a largo plazo que incluye el mantenimiento. Este artículo propone el diseño de un algoritmo de decisión para una intervención adaptativa de salud móvil e inalámbrica (mHealth) que se basa en conceptos de ingeniería de control. El proceso de diseño se basa en un modelo dinámico que representa el comportamiento basada en la Teoría Cognitiva Social (TCS), con una formulación de controlador fundamentada en el control predictivo por modelo híbrido (HMPC por sus siglas en inglés) la cual se utiliza para implementar el esquema de decisión. Las características discretas y lógicas del HMPC coinciden naturalmente con la naturaleza categórica de los componentes de la intervención y las decisiones lógicas que son propias de una intervención para actividad física. La intervención incorpora un modo de reconfiguración del controlador en línea que aplica cambios en los pesos de penalización para lograr la transición entre las etapas de entrenamiento de iniciación comportamental y mantenimiento. Resultados de simulación se presentan para ilustrar el desempeño del controlador utilizando un modelo ARX estimado de datos de un participante representativo de Just Walk, una intervención de actividad física diseñada usando principios de sistemas de control. | es_ES |
dc.description.sponsorship | El apoyo para este trabajo ha sido proporcionado por la Fundación Nacional de Ciencias (NSF por sus siglas en inglés) a través de la subvención IIS-449751, y el Instituto Nacional de la Salud (NIH por sus siglas en inglés) a través de la subvención R01CA244777. | es_ES |
dc.language | Español | es_ES |
dc.publisher | Universitat Politècnica de València | es_ES |
dc.relation.ispartof | Revista Iberoamericana de Automática e Informática industrial | es_ES |
dc.rights | Reconocimiento - No comercial - Compartir igual (by-nc-sa) | es_ES |
dc.subject | Model predictive control of hybrid systems | es_ES |
dc.subject | Control of physiological and clinical variables | es_ES |
dc.subject | System identification | es_ES |
dc.subject | Control predictivo híbrido | es_ES |
dc.subject | Control automático de variables fisiológicas y clínicas | es_ES |
dc.subject | Identificación de sistemas y estimación de parámetros | es_ES |
dc.title | Un esquema de decisiones para intervenciones adaptativas comportamentales de actividad física basado en control predictivo por modelo híbrido: ilustración con Just Walk | es_ES |
dc.title.alternative | A decision framework for an adaptive behavioral intervention for physical activity using hybrid model predictive control: illustration with Just Walk | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.4995/riai.2022.16798 | |
dc.relation.projectID | info:eu-repo/grantAgreement/NSF//IIS-449751 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/NIH//R01CA244777 | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Cevallos, D.; Martín, CA.; El Mistiri, M.; Rivera, DE.; Hekler, E. (2022). Un esquema de decisiones para intervenciones adaptativas comportamentales de actividad física basado en control predictivo por modelo híbrido: ilustración con Just Walk. Revista Iberoamericana de Automática e Informática industrial. 19(3):297-308. https://doi.org/10.4995/riai.2022.16798 | es_ES |
dc.description.accrualMethod | OJS | es_ES |
dc.relation.publisherversion | https://doi.org/10.4995/riai.2022.16798 | es_ES |
dc.description.upvformatpinicio | 297 | es_ES |
dc.description.upvformatpfin | 308 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 19 | es_ES |
dc.description.issue | 3 | es_ES |
dc.identifier.eissn | 1697-7920 | |
dc.relation.pasarela | OJS\16798 | es_ES |
dc.contributor.funder | National Science Foundation, EEUU | es_ES |
dc.contributor.funder | National Institutes of Health, EEUU | es_ES |
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