Optimized treatment of fibromyalgia using system identification and hybrid model predictive control

Sunil Deshpande, Naresh N. Nandola, Daniel Rivera, Jarred W. Younger

Research output: Contribution to journalArticle

13 Scopus citations

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 languageEnglish (US)
Pages (from-to)161-173
Number of pages13
JournalControl Engineering Practice
Volume33
DOIs
StatePublished - 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

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