ArticleIEEE transactions on control systems technology : a publication of the IEEE Control Systems Society2017
Control Engineering Methods for the Design of Robust Behavioral Treatments.
Article in IEEE transactions on control systems technology : a publication of the IEEE Control Systems Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Development of a Control-Oriented Model of Social Cognitive Theory for Optimized mHealth Behavioral Interventions.IEEE transactions on control systems technology : a publication of the IEEE Control Systems Society · 2020Article
- Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2020Article
- Personalized models of physical activity responses to text message micro-interventions: A proof-of-concept application of control systems engineering methods.Psychology of sport and exercise · 2019Article
- Precision Medicine.Annual review of statistics and its application · 2019Article
- Evaluating the effect of smoking cessation treatment on a complex dynamical system.Drug and alcohol dependence · 2017Article
- System Identification Algorithm for Non-Uniformly Sampled Data.IFAC-PapersOnLine · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
In this paper, a robust control approach is used to address the problem of adaptive behavioral treatment design. Human behavior (e.g., smoking and exercise) and reactions to treatment are complex and depend on many unmeasurable external stimuli, some of which are unknown. Thus, it is crucial to model human behavior over many subject responses. We propose a simple (low order) uncertain affine model subject to uncertainties whose response covers the most probable behavioral responses. The proposed model contains two different types of uncertainties: uncertainty of the dynamics and external perturbations that patients face in their daily life. Once the uncertain model is defined, we demonstrate how least absolute shrinkage and selection operator (lasso) can be used as an identification tool. The lasso algorithm provides a way to directly estimate a model subject to sparse perturbations. With this estimated model, a robust control algorithm is developed, where one relies on the special structure of the uncertainty to develop efficient optimization algorithms. This paper concludes by using the proposed algorithm in a numerical experiment that simulates treatment for the urge to smoke.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.