A System Identification Approach to Dynamically Modeling and Understanding Physical Activity Behaviors

• Other Authors: Seixas, Gustavo Mesel Lobo (Author)
• Format: Dissertation
• Language: English
• Published: 2016
• Subjects: Chemical engineering; Behavioral interventions; Physical activity; System identification
• Online Access: http://hdl.handle.net/2286/R.I.40795

abstract: The lack of healthy behaviors - such as physical activity and balanced diet - in modern society is responsible for a large number of diseases and high mortality rates in the world. Adaptive behavioral interventions have been suggested as a way to promote sustained behavioral changes to address these issues. These adaptive interventions can be modeled as closed-loop control systems, and thus applying control systems engineering and system identification principles to behavioral settings might provide a novel way of improving the quality of such interventions. Good understanding of the dynamic processes involved in behavioral experiments is a fundamental step in order to design such interventions with control systems ideas. In the present work, two different behavioral experiments were analyzed under the light of system identification principles and modelled as dynamic systems. In the first study, data gathered over the course of four days served as the basis for ARX modeling of the relationship between psychological constructs (negative affect and self-efficacy) and the intensity of physical activity. The identified models suggest that this behavioral process happens with self-regulation, and that the relationship between negative affect and self-efficacy is represented by a second order underdamped system with negative gain, while the relationship between self-efficacy and physical activity level is an overdamped second order system with positive gain. In the second study, which consisted of single-bouts of intense physical activity, the relation between a more complex set of behavioral variables was identified as a semi-physical model, with a theoretical set of system equations derived from behavioral theory. With a prescribed set of physical activity intensities, it was found that less fit participants were able to get higher increases in affective state, and that self-regulation processes are also involved in the system. === Dissertation/Thesis === Masters Thesis Chemical Engineering 2016