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A System Identification and Control Engineering Approach for Optimizing mHealth Behavioral Interventions Based on Social Cognitive Theory


Abstract Behavioral health problems such as physical inactivity are among the main causes of mortality around the world. Mobile and wireless health (mHealth) interventions offer the opportunity for applying control engineering concepts in behavioral change settings. Social Cognitive Theory (SCT) is among the most influential theories of health behavior and has been used as the conceptual basis of many behavioral interventions. This dissertation examines adaptive behavioral interventions for physical inactivity problems based on SCT using system identification and control engineering principles. First, a dynamical model of SCT using fluid analogies is developed. The model is used throughout the dissertation to evaluate system identification approache... (more)
Created Date 2016
Contributor Martin Moreno, Cesar Antonio (Author) / Rivera, Daniel E (Advisor) / Hekler, Eric B (Committee member) / Peet, Matthew M (Committee member) / Tsakalis, Konstantinos S (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Behavioral sciences / Control Systems Engineering / Emerging Control Applications / Low physical activity behavioral interventions / Modeling Human Behavior / Model Predictive Control / System Identification
Type Doctoral Dissertation
Extent 294 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Electrical Engineering 2016
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis