Finding a dynamical model of a social norm physical activity intervention

Low levels of physical activity in sedentary individuals constitute a major concern in public health. Effective physical activity interventions can be designed relying on mobile technologies, such that interactions can occur in opportune moments. The purpose of this work is to find a dynamical model of a social norm physical activity intervention relying on Social Cognitive Theory, and using an experimental data set. The model will serve as a framework for the design of future optimized interventions. To obtain model parameters, two strategies are developed: first, an algorithm that randomly varies the values of each model parameter around initial guesses. The second approach utilizes traditional system identification concepts to obtain model parameters relying on semi-physical identification routines. For both cases, the obtained model is assessed through the computation of percentage fits to a validation data set, and by a correlational analysis.