Continuous-time system identification of a smoking cessation intervention

Kevin P. Timms, Daniel E. Rivera, Linda M. Collins, Megan E. Piper

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Cigarette smoking is a major global public health issue and the leading cause of preventable death in the United States. Toward a goal of designing better smoking cessation treatments, system identification techniques are applied to intervention data to describe smoking cessation as a process of behaviour change. System identification problems that draw from two modelling paradigms in quantitative psychology (statistical mediation and self-regulation) are considered, consisting of a series of continuous-time estimation problems. A continuous-time dynamic modelling approach is employed to describe the response of craving and smoking rates during a quit attempt, as captured in data from a smoking cessation clinical trial. The use of continuous-time models provide benefits of parsimony, ease of interpretation, and the opportunity to work with uneven or missing data.

Original languageEnglish (US)
Pages (from-to)1423-1437
Number of pages15
JournalInternational Journal of Control
Volume87
Issue number7
DOIs
StatePublished - Jul 3 2014

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Continuous time systems
Identification (control systems)
Public health

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Timms, Kevin P. ; Rivera, Daniel E. ; Collins, Linda M. ; Piper, Megan E. / Continuous-time system identification of a smoking cessation intervention. In: International Journal of Control. 2014 ; Vol. 87, No. 7. pp. 1423-1437.
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Continuous-time system identification of a smoking cessation intervention. / Timms, Kevin P.; Rivera, Daniel E.; Collins, Linda M.; Piper, Megan E.

In: International Journal of Control, Vol. 87, No. 7, 03.07.2014, p. 1423-1437.

Research output: Contribution to journalArticle

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