SF-LG: Space-Filling Line Graphs for Visualizing Interrelated Time-series Data on Smartwatches

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Abstract

Multiple embedded sensors enable smartwatch apps to amass large amounts of interrelated time-series data simultaneously, such as heart rate, oxygen levels or steps walked. Visualizing multiple interlinked datasets is possible on smartphones but remains challenging on small smartwatch displays. We propose a new technique, the Space-Filling Line Graph (SF-LG), that preserves the key visual properties of time-series graphs while making available space on the display to augment such graphs with additional information. Results from our first study (N=30) suggest that, while SF-LG makes available additional space on the small display, it also enables effective (i.e. quick and accurate) comprehension of key line graph tasks. We next implement a greedy algorithm to embed auxiliary information in the most suitable regions on the display. In a second study (N=27), we find that participants are efficient at locating and linking interrelated content using SF-LG in comparison to two baselines approaches. We conclude with guidelines for smartwatch space maximization for visual displays.

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APA

Neshati, A., Alallah, F., Rey, B., Sakamoto, Y., Serrano, M., & Irani, P. (2021). SF-LG: Space-Filling Line Graphs for Visualizing Interrelated Time-series Data on Smartwatches. In Proceedings of MobileHCI 2021 - ACM International Conference on Mobile Human-Computer Interaction: Mobile Apart, MobileTogether. Association for Computing Machinery, Inc. https://doi.org/10.1145/3447526.3472040

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