Mobile Health Mashups: Making sense of multiple streams of wellbeing and contextual data for presentation on a mobile device

Abstract

In this paper we present the Mobile Health Mashups system, a mobile service that collects data from a variety of health and wellbeing sensors and presents significant correlations across sensors in a mobile widget as well as on a mobile web application. We found that long-term correlation data provided users with new insights about systematic wellness trends that they could not make using only the time series graphs provided by the sensor manufacturers. We describe the Mobile Health Mashups system with a focus on analyzing and detailing the technical solution, such as: integration of sensors, how to create correlations between various data sets, and the presentation of the statistical data as feeds and graphs. We will also describe the iterative design process that involved a 2-month field trial, the outcome of this trial, and implications for design of mobile data mashup systems.