Alaul Islam
Université Paris-Saclay, CNRS, Inria, LISN, Gif-Sur-Yvette, France
We present the findings of four studies related to the visualization of sleep data on wearables with two form factors: smartwatches and fitness bands. Our goal was to understand the interests, preferences, and effectiveness of different sleep visualizations by form factor. In a survey, we showed that wearers were mostly interested in weekly sleep duration, and nightly sleep phase data. Visualizations of this data were generally preferred over purely text-based representations, and the preferred chart type for fitness bands, and smartwatches was often the same. In one in-person pilot study, and two crowdsourced studies, we then tested the effectiveness of the most preferred representations for different tasks, and found that participants performed simple tasks effectively on both form factors but more complex tasks benefited from the larger smartwatch size. Lastly, we reflect on our crowdsourced study methodology for testing the effectiveness of visualizations for wearables. Supplementary material is available at https://osf.io/yz8ar/.
https://dl.acm.org/doi/abs/10.1145/3491102.3501921
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)