Seto, Edmund

Models of Individual Dietary Behavior Based on Smartphone Data: The Influence of Routine, Physical Activity, Emotion, and Food Environment.

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Publication Date: 
Apr 07, 2016

INTRODUCTION: Smartphone applications (apps) facilitate the collection of data on multiple aspects of behavior that are useful for characterizing baseline patterns and for monitoring progress in interventions aimed at promoting healthier lifestyles.

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Comparison of physical activity measures using mobile phone-based CalFit and Actigraph.

Publication Date: 
Jul 30, 2013

BACKGROUND: Epidemiological studies on physical activity often lack inexpensive, objective, valid, and reproducible tools for measuring physical activity levels of participants. Novel sensing technologies built into smartphones offer the potential to fill this gap.

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Improving estimates of air pollution exposure through ubiquitous sensing technologies.

Publication Date: 
Mar 13, 2013

Traditional methods of exposure assessment in epidemiological studies often fail to integrate important information on activity patterns, which may lead to bias, loss of statistical power, or both in health effects estimates.