abstract: Nutrition instruction has become more accessible; it is no longer relegated to the doctor’s office, dietitian briefing, outpatient clinic, or hospital. Now it is available in people’s hands, pockets, and purses via their smartphone. Since nutrition instruction has become more accessible, health professionals and members of the general public are increasingly interested in using smartphone apps to assist with health-related dietary changes. With more and more of the population required to follow certain dietary recommendations and/or monitor specific nutrient intake, commercially available apps may be a useful and cost-effective resource for the public. The purpose of this four-week intervention was to determine if the popular calorie counter app, MyFitnessPal, can be used to reduce sodium intake to ≤ 2,300 mg/day compared to the traditional paper-and-pencil method. This four-week randomized parallel trial enrolled 30 generally healthy adults who were 18 to 80 years of age. Participants were randomly assigned to the MyFitnessPal (“APP”) group or to the paper (“PAP”) group and required to meet three times with the researcher for screening, baseline (start), and completion of the study. There was a significant difference in the mean urinary sodium change between the APP group and the PAP group from the start of the intervention to the completion (-24.0±32.6 and 8.5±41.9 mmol/g creatinine respectively, p = 0.027). Other positive trends that resulted from the intervention included a decline in dietary sodium in both groups and a higher adherence in the APP group compared to the PAP group regarding recording method. The MyFitnessPal app proved to be a useful tool in reducing and/or monitoring sodium intake. Thus, this trial reinforces the potential of this app to be used for monitoring other nutrients, but further research needs to be conducted. / Dissertation/Thesis / Masters Thesis Nutrition 2016

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Motivated by challenges and opportunities in nutritional epidemiology and food journaling, ubiquitous computing researchers have proposed numerous techniques for automated dietary monitoring (ADM) over the years. Although progress has been made, a truly practical system that can automatically recognize what people eat in real-world settings remains elusive. This dissertation addresses the problem of ADM by focusing on practical eating moment detection. Eating detection is a foundational element of ADM since automatically recognizing when a person is eating is required before identifying what and how much is being consumed. Additionally, eating detection can serve as the basis for new types of dietary self-monitoring practices such as semi-automated food journaling. In this thesis, I show that everyday eating moments such as breakfast, lunch, and dinner can be automatically detected in real-world settings by opportunistically leveraging sensors in practical, off-the-shelf wearable devices. I refer to this instrumentation approach as "commodity sensing". The work covered by this thesis encompasses a series of experiments I conducted with a total of 106 participants where I explored a variety of sensing modalities for automatic eating moment detection. The modalities studied include first-person images taken with wearable cameras, ambient sounds, and on-body inertial sensors. I discuss the extent to which first-person images reflecting everyday experiences can be used to identify eating moments using two approaches: human computation, and by employing a combination of state-of-the-art machine learning and computer vision techniques. Furthermore, I also describe privacy challenges that arise with first-person photographs. Next, I present results showing how certain sounds associated with eating can be recognized and used to infer eating activities. Finally, I elaborate on findings from three studies focused on the use of on-body inertial sensors (head and wrists) to recognize eating moments both in a semi-controlled laboratory setting and in real-world conditions. I conclude by relating findings and insights to practical applications, and highlighting opportunities for future work.