WalkNRide: contextualising feedback in physical activity trackers

Increasing levels of sedentarism and obesity, along with advances in sensor technologies have instigated a market for wearable activity trackers, electronic devices that sense users’ physical activity levels with the goals of self-monitoring and behaviour change. Nowadays, activity trackers are one of the most desirable technologies, making up for a market of over $230 million in 2013. However, despite the spike of users’ interest, activity trackers have been shown to lose their appeal over time, with a recent survey suggesting that one out of three users discard the tracker in the course of the first six months of use. The question we pose is: how can we design activity tracker so that users’ interests is sustained over the long term? Our design approach focuses on contextualising physical activity. We do this through sensing users’ locations and activities (such as being still, walking or commuting through a car, bus or other means) and thus providing innovative ways of presenting feedback on users. This thesis presents the design and evaluation of WalkNRide, a physical activity tracker for Google Android. Through a longitudinal field study of WalkNRide, we attempt to inquire into the factors that drive the adoption (or non-adoption) of the tool as well as the ways in which the use of the tool contributes towards habit formation.

High body mass index is not a barrier to physical activity: Analysis of international rugby players' anthropometric data

Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.