TY - JOUR
T1 - Un esquema de decisiones para intervenciones adaptativas comportamentales de actividad física basado en control predictivo por modelo híbrido
T2 - ilustración con Just Walk
AU - Cevallos, Daniel
AU - Martín, César A.
AU - El Mistiri, Mohamed
AU - Rivera, Daniel E.
AU - Hekler, Eric Chambers
N1 - Funding Information:
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-1449751, y el Instituto Nacional de la Salud (NIH por sus siglas en inglés) a través de la subvención R01CA244777. Las opiniones expresadas en este artículo son de los autores y no reflejan necesariamente los puntos de vista de NSF o NIH.
Publisher Copyright:
© 2022 Universitat Politecnica de Valencia. All rights reserved.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Model predictive control of hybrid systems
KW - control of physiological and clinical variables
KW - system identification
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U2 - 10.4995/RIAI.2022.16798
DO - 10.4995/RIAI.2022.16798
M3 - Article
AN - SCOPUS:85134596139
SN - 1697-7912
VL - 19
SP - 297
EP - 308
JO - RIAI - Revista Iberoamericana de Automatica e Informatica Industrial
JF - RIAI - Revista Iberoamericana de Automatica e Informatica Industrial
IS - 3
ER -