Abstract
The term adaptive intervention is used in behavioral health to describe individually tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health.
Original language | English (US) |
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Pages (from-to) | 161-173 |
Number of pages | 13 |
Journal | Control Engineering Practice |
Volume | 33 |
DOIs | |
State | Published - Dec 1 2014 |
Keywords
- Biomedical applications
- Fibromyalgia
- Hybrid model predictive control
- Optimized adaptive behavioral interventions
- System identification
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics