TY - GEN
T1 - A system identification approach for improving behavioral interventions based on Social Cognitive Theory
AU - Martin, Cesar A.
AU - Deshpande, Sunil
AU - Hekler, Eric B.
AU - Rivera, Daniel
N1 - Publisher Copyright:
© 2015 American Automatic Control Council.
PY - 2015/7/28
Y1 - 2015/7/28
N2 - Mobile and wireless health (mHealth) interventions offer the opportunity for applying control engineering and system identification concepts in behavioral change settings. Social Cognitive Theory provides a recognized theoretical framework that can be applied to explain changes in behavior over time. Based on earlier work describing a dynamical model of this theory, a semi-physical system identification approach is developed in this paper for interventions associated with improving physical activity. An initial informative experiment that relies on prior knowledge from similar interventions is first designed to obtain basic insights regarding the dynamics of the system. Based on these results a second, optimized experiment is developed which solves a constrained optimization problem to find the intervention component profiles needed to mirror a desired behavioral pattern and to provide sufficient information that allows a more precise estimation of the parameters. A simulation study is presented to illustrate the design procedure.
AB - Mobile and wireless health (mHealth) interventions offer the opportunity for applying control engineering and system identification concepts in behavioral change settings. Social Cognitive Theory provides a recognized theoretical framework that can be applied to explain changes in behavior over time. Based on earlier work describing a dynamical model of this theory, a semi-physical system identification approach is developed in this paper for interventions associated with improving physical activity. An initial informative experiment that relies on prior knowledge from similar interventions is first designed to obtain basic insights regarding the dynamics of the system. Based on these results a second, optimized experiment is developed which solves a constrained optimization problem to find the intervention component profiles needed to mirror a desired behavioral pattern and to provide sufficient information that allows a more precise estimation of the parameters. A simulation study is presented to illustrate the design procedure.
UR - http://www.scopus.com/inward/record.url?scp=84940952887&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84940952887&partnerID=8YFLogxK
U2 - 10.1109/ACC.2015.7172261
DO - 10.1109/ACC.2015.7172261
M3 - Conference contribution
AN - SCOPUS:84940952887
T3 - Proceedings of the American Control Conference
SP - 5878
EP - 5883
BT - ACC 2015 - 2015 American Control Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 American Control Conference, ACC 2015
Y2 - 1 July 2015 through 3 July 2015
ER -