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.
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- Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control
- Deshpande, Sunil (Author)
- Nandola, Naresh (Author)
- Rivera, Daniel (Author)
- Younger, Jarred W. (Author)
- Control Systems Engineering Laboratory (Contributor)
- Digital object identifier: 10.1016/j.conengprac.2014.09.011
- Identifier TypeInternational standard serial numberIdentifier Value0967-0661
- NOTICE: this is the author's version of a work that was accepted for publication. Changes may have been made to this work since it was submitted. A definitive version was subsequently published at http://dx.doi.org/10.1016/j.conengprac.2014.09.011
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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