TY - GEN
T1 - A control engineering approach for optimizing physical activity behavioral interventions
AU - Martin, Cesar A.
AU - Rivera, Daniel
AU - Hekler, Eric B.
N1 - Funding Information:
Support for this work has been provided by the National Science Foundation (NSF) through grant IIS-1449751. The opinions expressed in this article are the authors' own and do not necessarily reflect the views of NSF. Special thanks to Escuela Superior Politécnica del Litoral (ESPOL) and Secretaria de Educación Superior, Ciencia, Tecnolgía e Innovación (SENESCYT) from Ecuador.
Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/21
Y1 - 2016/11/21
N2 - This paper presents the use of control engineering principles to optimize mobile and wireless health (mHealth) adaptive behavioral interventions for physical activity based on Social Cognitive Theory (SCT). SCT is a conceptual framework that describes human behavior and has been used in many health behavior interventions. An intervention for physical activity is formulated as a control systems problem relying on a dynamical model of SCT that is developed utilizing fluid analogies. To obtain values for model parameters, system identification experiments are designed including two phases: An initial informative stage followed by an optimized stage that incorporates 'patient-friendly' conditions. With the estimated model, a closed-loop intervention is formulated relying on Hybrid Model Predictive Control (HMPC). The HMPC algorithm includes a representation of categorical and discrete constraints that are inherent to behavioral interventions, and the recognition of behavioral initiation and maintenance phases. A simulation study is performed illustrating representative scenarios of the system (in both open and closed-loop).
AB - This paper presents the use of control engineering principles to optimize mobile and wireless health (mHealth) adaptive behavioral interventions for physical activity based on Social Cognitive Theory (SCT). SCT is a conceptual framework that describes human behavior and has been used in many health behavior interventions. An intervention for physical activity is formulated as a control systems problem relying on a dynamical model of SCT that is developed utilizing fluid analogies. To obtain values for model parameters, system identification experiments are designed including two phases: An initial informative stage followed by an optimized stage that incorporates 'patient-friendly' conditions. With the estimated model, a closed-loop intervention is formulated relying on Hybrid Model Predictive Control (HMPC). The HMPC algorithm includes a representation of categorical and discrete constraints that are inherent to behavioral interventions, and the recognition of behavioral initiation and maintenance phases. A simulation study is performed illustrating representative scenarios of the system (in both open and closed-loop).
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U2 - 10.1109/ETCM.2016.7750851
DO - 10.1109/ETCM.2016.7750851
M3 - Conference contribution
AN - SCOPUS:85007021327
T3 - 2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016
BT - 2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016
Y2 - 12 October 2016 through 14 October 2016
ER -