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ZENODO
Conference object . 2014
License: CC 0
Data sources: ZENODO
https://doi.org/10.1109/embc.2...
Article . 2014 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2018
Data sources: DBLP
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The importance of behavior theory in control system modeling of physical activity sensor data

Authors: William T. Riley; Cesar A. Martin; Daniel E. Rivera;

The importance of behavior theory in control system modeling of physical activity sensor data

Abstract

Among health behaviors, physical activity has the most extensive record of research using passive sensors. Control systems and other system dynamic approaches have long been considered applicable for understanding human behavior, but only recently has the technology provided the precise and intensive longitudinal data required for these analytic approaches. Although sensors provide intensive data on the patterns and variations of physical activity over time, the influences of these variations are often unmeasured. Health behavior theories provide an explanatory framework of the putative mediators of physical activity changes. Incorporating the intensive longitudinal measurement of these theoretical constructs is critical to improving the fit of control system model of physical activity and for advancing behavioral theory. Theory-based control models also provide guidance on the nature of the controllers which serve as the basis for just-in-time adaptive interventions based on these control system models.

Keywords

Health Behavior, Humans, Tuberculosis, Models, Theoretical, Motor Activity, Severity of Illness Index, Wireless Technology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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16
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