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A control systems engineering approach for adaptive behavioral interventions: illustration with a fibromyalgia intervention

机译:适应性行为干预的控制系统工程方法:带有纤维肌痛干预的图示

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摘要

The term adaptive intervention has been used in behavioral medicine to describe operationalized and individually tailored strategies for prevention and treatment of chronic, relapsing disorders. Control systems engineering offers an attractive means for designing and implementing adaptive behavioral interventions that feature intensive measurement and frequent decision-making over time. This is illustrated in this paper for the case of a low-dose naltrexone treatment intervention for fibromyalgia. System identification methods from engineering are used to estimate dynamical models from daily diary reports completed by participants. These dynamical models then form part of a model predictive control algorithm which systematically decides on treatment dosages based on measurements obtained under real-life conditions involving noise, disturbances, and uncertainty. The effectiveness and implications of this approach for behavioral interventions (in general) and pain treatment (in particular) are demonstrated using informative simulations.
机译:适应性干预一词已在行为医学中用于描述预防和治疗慢性复发性疾病的可操作且个性化的策略。控制系统工程为设计和实施适应性行为干预提供了一种有吸引力的方法,这些措施的特征是需要进行大量测量并随着时间的推移频繁做出决策。本文针对低剂量纳曲酮治疗纤维肌痛的情况进行了说明。工程学的系统识别方法用于根据参与者完成的每日日记报告估算动力模型。这些动力学模型随后构成模型预测控制算法的一部分,该算法基于在涉及噪声,干扰和不确定性的现实条件下获得的测量结果,系统地决定治疗剂量。使用信息模拟,证明了这种方法对行为干预(一般而言)和疼痛治疗(尤其是疼痛治疗)的有效性和含义。

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