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) |
|---|---|
| Pages (from-to) | 161-173 |
| Number of pages | 13 |
| Journal | Control Engineering Practice |
| Volume | 33 |
| DOIs | |
| State | Published - Dec 1 2014 |
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Keywords
- Biomedical applications
- Fibromyalgia
- Hybrid model predictive control
- Optimized adaptive behavioral interventions
- System identification
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Applied Mathematics
- Computer Science Applications
Cite this
Optimized treatment of fibromyalgia using system identification and hybrid model predictive control. / Deshpande, Sunil; Nandola, Naresh N.; Rivera, Daniel; Younger, Jarred W.
In: Control Engineering Practice, Vol. 33, 01.12.2014, p. 161-173.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Optimized treatment of fibromyalgia using system identification and hybrid model predictive control
AU - Deshpande, Sunil
AU - Nandola, Naresh N.
AU - Rivera, Daniel
AU - Younger, Jarred W.
PY - 2014/12/1
Y1 - 2014/12/1
N2 - 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.
AB - 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.
KW - Biomedical applications
KW - Fibromyalgia
KW - Hybrid model predictive control
KW - Optimized adaptive behavioral interventions
KW - System identification
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UR - http://www.scopus.com/inward/citedby.url?scp=84908264487&partnerID=8YFLogxK
U2 - 10.1016/j.conengprac.2014.09.011
DO - 10.1016/j.conengprac.2014.09.011
M3 - Article
AN - SCOPUS:84908264487
VL - 33
SP - 161
EP - 173
JO - Control Engineering Practice
JF - Control Engineering Practice
SN - 0967-0661
ER -