Visualizing Running Races through the Multivariate Time-Series of Multiple Runners

The recent widespread of heart rate (HR) monitors is allowing people to measure body response during and after exercise, which produces a collection of time-series on multivariate aspects, such as heartbeat, speed, geolocation, etc. Such monitoring can be extremely important for people with low fitness levels, since they are susceptible to cardiovascular diseases or other physical injuries when exercising at high heartbeat frequencies. Even though most monitors provide tools to export and display this information for each individual, the ability to visualize the collection of multiple runners in a given running race is mostly unexplored. In this work, we present a design study that aims to support analysis and answer several questions raised by an expert on exercise physiology about a given running race. We describe each visualization design and how they individually, or in collaboration, can be used to reveal interesting aspects of the data. We illustrate our results with use cases that provide evaluation and feedback about the visualization designs proposed.