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.

中文翻译：

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使用系统识别和混合模型预测控制优化纤维肌痛治疗

术语适应性干预在行为健康中用于描述预防和治疗慢性复发性疾病的个体化策略。本文描述了一种用于从临床数据中开发动态模型的系统识别方法，随后描述了一种混合模型预测控制方案，用于分配纳曲酮剂量作为治疗纤维肌痛（一种慢性疼痛病症）的方法。包含显着工厂模型不匹配条件的模拟研究证明了混合预测控制作为优化自适应干预的决策框架的好处。这项工作为针对慢性疼痛和行为健康相关疾病的新型个性化干预措施的设计提供了见解。