title: Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control.
abstract: The termadaptive interventionis 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.
authors.affiliation: Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 USA.
authors.forename: Sunil
authors.initials: S
authors.lastname: Deshpande
authors.affiliation: Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 USA.
authors.forename: Naresh N
authors.initials: NN
authors.lastname: Nandola
authors.affiliation: Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 USA.
authors.forename: Daniel E
authors.initials: DE
authors.lastname: Rivera
authors.affiliation: Department of Psychology, Departments of Anesthesiology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL 35233 USA.
authors.forename: Jarred W
authors.initials: JW
authors.lastname: Younger
keywords: biomedical applications; fibromyalgia; hybrid model predictive control; optimized adaptive behavioral interventions; system identification