A system identification approach for improving behavioral interventions based on Social Cognitive Theory

Cesar A. Martin, Sunil Deshpande, Eric B. Hekler, Daniel Rivera

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781479986842
StatePublished - Jul 28 2015
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2015 American Control Conference, ACC 2015
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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