TY - GEN
T1 - A decision framework for an adaptive behavioral intervention for physical activity using hybrid model predictive control
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
Publisher Copyright:
© 2016 American Automatic Control Council (AACC).
PY - 2016/7/28
Y1 - 2016/7/28
N2 - Physical inactivity is a major contributor to morbidity and mortality worldwide. Many physical activity behavioral interventions at present 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. Simulation results are presented to illustrate the performance of the controller using a hypothetical model for physical activity interventions, under realistic conditions.
AB - Physical inactivity is a major contributor to morbidity and mortality worldwide. Many physical activity behavioral interventions at present 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. Simulation results are presented to illustrate the performance of the controller using a hypothetical model for physical activity interventions, under realistic conditions.
UR - http://www.scopus.com/inward/record.url?scp=84992159864&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84992159864&partnerID=8YFLogxK
U2 - 10.1109/ACC.2016.7525468
DO - 10.1109/ACC.2016.7525468
M3 - Conference contribution
AN - SCOPUS:84992159864
T3 - Proceedings of the American Control Conference
SP - 3576
EP - 3581
BT - 2016 American Control Conference, ACC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 American Control Conference, ACC 2016
Y2 - 6 July 2016 through 8 July 2016
ER -