Abstract
This paper presents closed-loop intervention simulations for an identified, data-validated model of Social Cognitive Theory (SCT). A reduced-complexity SCT model structure consisting of dynamic operant conditioning and self-efficacy loops is considered for the prediction of physical activity behavior. Consistent with real-world requirements, including the need for hybrid decision rules policies, the proposed closed-loop intervention design follows a Hybrid Model Predictive Control formulation. The prime goal of this paper is to reinforce the viability of the system identification and control engineering frameworks in the design of optimized and perpetually adaptive behavioral health interventions.
Original language | English (US) |
---|---|
Pages (from-to) | 31-36 |
Number of pages | 6 |
Journal | IFAC-PapersOnLine |
Volume | 54 |
Issue number | 7 |
DOIs | |
State | Published - Jul 1 2021 |
Event | 19th IFAC Symposium on System Identification, SYSID 2021 - Padova, Italy Duration: Jul 13 2021 → Jul 16 2021 |
Keywords
- Adaptive mHealth interventions
- Emerging control applications
- Grey-box identification
- Hybrid model predictive control
- Social cognitive theory
ASJC Scopus subject areas
- Control and Systems Engineering