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

PROCEEDINGS OF 23RD ACM INTERNATIONAL CONFERENCE ON MOBILE HUMAN-COMPUTER INTERACTION (MOBILEHCI 2021): MOBILE APART, MOBILE TOGETHER(2021)

引用 4|浏览25
暂无评分
摘要
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.
更多
查看译文
关键词
Smartwatches, data visualization, line graph, graph simplification, time-series data
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要