Behavioral Modeling in Weight Loss Interventions.

ABSTRACT: Designing systems with human agents is difficult because it often requires models that characterize agents' responses to changes in the system's states and inputs. An example of this scenario occurs when designing treatments for obesity. While weight loss interventions through increasing physical activity and modifying diet have found success in reducing individuals' weight, such programs are difficult to maintain over long periods of time due to lack of patient adherence. A promising approach to increase adherence is through the personalization of treatments to each patient. In this paper, we make a contribution towards treatment personalization by developing a framework for predictive modeling using utility functions that depend upon both time-varying system states and motivational state

SUBMITTER: Aswani A 

PROVIDER: S-EPMC6377177 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature