|Title||Exploration and visualization of race biking performance|
We develop methods and tools for visual analytics to help analysing performance parameters in race biking. The work described in this paper is done as a part of the Powerbike  project at the University of Konstanz, the goal of which is to provide methods to model, analyze, visualize, and improve the performance of athletes during the training and in competition in cycling. In a laboratory, the measurements combined from a series of devices, including conventional bike computers, GPS-recorders, and power meters are processed. The data is recorded by different devices and synchronized and fused beforehand, yielding a collection of time series (with sampling rate of 1Hz) for the various performance parameters. Paper addresses the problem to present all this data on one screen for the trainer or cyclist so they can quickly grasp the main trends in it to be able to make decisions about further training.
Overview of the existing visualization tools
Although we did not find any scientific study on the visualization problem, there are commercial products for which visual tools with only basic functionality are provided. We discuss drawbacks of the visualizations provided by CompuTrainer , Tacx , and SRM .
CompuTrainer provides professional bicycle simulator. USA Triathlon and USA Cycling teams rely on CompuTrainer to test and train their performance.
Tacx sells three types of ergometers: VR Trainer and Ergotrainer for professional athletes and Cycletrainer for hobbyists.
SRM is a training system developed to measure power of the cyclist while riding. In the software SRMWin basic visualization tools are supplied.
All the visualizations that come with these products depict raw time series. This kind of visualization suffers from cluttering making it difficult to extract the essential information from it. Moreover the user cannot adjust the level of detail of the visualization. Our proposed visualization technique overcomes these shortcomings.
Proposed visualization technique
The Powerbike project spans a range of research for cycling, requiring different visualization tasks to be solved. These can be grouped in three categories:
To solve this problem we follow the paradigm: "Analyze First - Show the Important — Zoom, Filter and Analyze Further — Details on Demand" . We aggregate all the data recorded during the course in one graph. The principal axes for the data display are speed and distance. So called information chunks are depicted on the curve that describes the speed of the cyclist. Information chunks show additional data; e.g., power, heart rate, and cadence. We propose automatic and manual methods for defining the initial number and positions of chunks. The advantages and disadvantages of each of the methods are discussed. The number of chunks can be adjusted by the user interactively setting the level of detail. With this technique the user can quickly grasp the main trends in the performance. This can be easily done setting the low level of detail. After that regions of interest can be examined more thoroughly. On demand user can explore the data completely, switching to another view.