System Identification Approaches For Energy Intake Estimation: Enhancing Interventions For Managing Gestational Weight Gain.

Excessive maternal weight gain during pregnancy represents a major public health concern that calls for novel and effective gestational weight management interventions. In Healthy Mom Zone (HMZ), an on-going intervention study, energy intake underreporting has been found to be an important consideration that interferes with accurate weight control assessment, and the effective use of energy balance models in an intervention setting. In this paper, a series of estimation approaches that address measurement noise and measurement losses are developed to better understand the extent of energy intake underreporting. These include back-calculating energy intake from an energy balance model developed for gestational weight gain prediction, a Kalman filtering-based approach to recursively estimate energy intake from intermittent measurements in real-time, and an approach based on semi-physical identification principles which features the capability of adjusting future self-reported energy intake by parameterizing the extent of underreporting. The three approaches are illustrated by evaluating with participant data obtained through the HMZ intervention study, with the results demonstrating the potential of these methods to promote the success of weight control. The pros and cons of the presented approaches are discussed to generate insights for users in future applications.