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.
Deshpande, Sunil, Nandola, Naresh N., Rivera, Daniel E., & Younger, Jarred W. (2014). Optimized treatment of fibromyalgia using system identification and hybrid model predictive control. CONTROL ENGINEERING PRACTICE, 33, 161-173. http://dx.doi.org/10.1016/j.conengprac.2014.09.011
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