TY - GEN
T1 - An Optimized Behavioral Intervention for Managing Gestational Weight Gain Using Semi-Physical Modeling and Hybrid Model Predictive Control
AU - Khan, Owais
AU - Campregher, Francesco
AU - Rivera, Daniel E.
AU - Visioli, Antonio
AU - Pauley, Abigail M.
AU - Downs, Danielle Symons
N1 - Publisher Copyright:
© 2025 AACC.
PY - 2025
Y1 - 2025
N2 - This paper describes an optimized behavioral intervention Healthy Mom Zone (HMZ) for managing gestational weight gain featuring sequential decision-making using Hybrid Model Predictive Control (HMPC). Dynamical models incorporating both behavioral and physiological aspects of the problem are presented and estimated from HMZ participant data via constrained semi-physical modeling. Daily measurements are provided to a controller that ultimately makes judicious (though infrequent) augmentations on categorical dosages of healthy eating and physical activity intervention components. Consequently, an HMPC algorithm is required which must follow a logical sequence of control actions conforming to practical requirements. A case study shows the benefits relative to a conventional "IF-THEN"approach. The computational framework (both modeling and control) serves as the basis for the Healthy Mom Zone 2.0 intervention currently being evaluated in a randomized clinical trial (NIH R01DK134863, NCT05807594) at Penn State University.
AB - This paper describes an optimized behavioral intervention Healthy Mom Zone (HMZ) for managing gestational weight gain featuring sequential decision-making using Hybrid Model Predictive Control (HMPC). Dynamical models incorporating both behavioral and physiological aspects of the problem are presented and estimated from HMZ participant data via constrained semi-physical modeling. Daily measurements are provided to a controller that ultimately makes judicious (though infrequent) augmentations on categorical dosages of healthy eating and physical activity intervention components. Consequently, an HMPC algorithm is required which must follow a logical sequence of control actions conforming to practical requirements. A case study shows the benefits relative to a conventional "IF-THEN"approach. The computational framework (both modeling and control) serves as the basis for the Healthy Mom Zone 2.0 intervention currently being evaluated in a randomized clinical trial (NIH R01DK134863, NCT05807594) at Penn State University.
UR - https://www.scopus.com/pages/publications/105015667786
UR - https://www.scopus.com/pages/publications/105015667786#tab=citedBy
U2 - 10.23919/ACC63710.2025.11107916
DO - 10.23919/ACC63710.2025.11107916
M3 - Conference contribution
C2 - 41306560
AN - SCOPUS:105015667786
T3 - Proceedings of the American Control Conference
SP - 3317
EP - 3322
BT - 2025 American Control Conference, ACC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 American Control Conference, ACC 2025
Y2 - 8 July 2025 through 10 July 2025
ER -