Comparative Study of Four Visualization Techniques and Positional Variations for Displaying Exercise Data on Smartwatches

Abstract

As smartwatches become increasingly prevalent, their built-in sensors provide a rich source for gathering various personal data, including physical activity and health metrics. We found that different brands and models use various visualization techniques. However, the effectiveness of these visualizations within the limited display space of smartwatches remains unclear. Therefore, this paper compares four popular visualizations—bar charts, radial bar charts, donut charts and multi-donut charts—used for displaying activity data on smartwatches. The evaluation focuses on their performance in three common user tasks: counting completed goals, estimating completion percentage and estimating exercise duration. Additionally, the study investigates the impact of the positioning of the target data item, within these visualizations on user performance. Our results indicate that bar charts are superior in terms of task completion time across all tasks. Radial bar charts and multi-donut charts are most effective in helping users perceive the completion ratio (percentage) of each activity and understand the time taken for each activity metric (in minutes). Interestingly, we found that the positioning of data items within the visualizations significantly influences user performance in many cases. Furthermore, it was noted that the visualizations users favoured the most were generally those that enabled them to achieve the highest accuracy in task completion. These insights provide valuable guidelines for future designs in visualizing exercise data on smartwatches. Supplementary material is available at https://osf.io/5u2ph/.