EdgeSelect: Smartwatch Data Interaction with Minimal Screen Occlusion

Neshati, Ali; Faleel, Shariff Am; Li, Ziming; Liang, Hai-Ning; Latulipe, Celine; Irani, Pourang

doi:10.1145/3536221.3556586

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…This type of data plays a fundamental role in user decisions concerning the data [22]. In particular, data is represented in smartwatches through several visualization techniques, such as text, numbers, pictographs, animation, line graphs, bar and pie charts, or compressed versions of these visualization methods [52]. The most common data representation is an icon (e.g.…”

Section: Introductionmentioning

confidence: 99%

Understanding how to Design Health Data Visualizations for Chilean Older Adults on Mobile Devices

Cajamarca,

Herskovic,

Dondighual

et al. 2023

Proceedings of the 2023 ACM Designing Interactive Systems Conference

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Mobile devices, including activity trackers and smartwatches, can help older adults monitor health parameters passively and unobtrusively. Most user interactions with small devices consist of brief glances at the time or notifcations. Consuming information from small displays poses challenges, which have been seldom studied from the perspective of older users. In this paper, we worked with older adults towards creating health data visualizations for them for small devices. We conducted a mixed-methods study with 30 older adults, in which we (1) conducted group discussions to understand participants' opinions, (2) measured times taken to interpret health data visualizations with and without progress information, (3) measured how much information they could manage to see during brief glances. When data was visualized without progress indicators, participants took less time to understand the data and made fewer errors. Participants preferred health data visualizations that featured peaceful, and positive pictorial representations. We present design opportunities for older adults' data visualizations in small devices.

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Section: Introductionmentioning

confidence: 99%

Understanding how to Design Health Data Visualizations for Chilean Older Adults on Mobile Devices

Cajamarca,

Herskovic,

Dondighual

et al. 2023

Proceedings of the 2023 ACM Designing Interactive Systems Conference

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“…This brevity aligns well with the design goals, characteristics, and affordances of glanceable visualizations. Moreover, the constrained display size of these devices limits the utility of complex and information-dense visualizations [51], making glanceable formats a suitable fit.…”

Section: Introductionmentioning

confidence: 99%

Characterizing Glanceable Visualizations: From Perception to Behavior Change

Blascheck¹,

Bentley²,

Choe³

et al. 2021

Mobile Data Visualization

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W E detail and illustrate glanceability as a crucial requirement for several types of mobile visualizations. For example, in a difficult terrain, a runner can only check a smartwatch for elevation or heart rate data for a few hundred milliseconds before the eyes need to refocus on the trail ahead. Such quick information needs differ from those in traditional visualizations that are meant for deep analysis and interaction with possibly large and complex datasets. Visualizations designed for quick information needs are described under a variety of terms in the literature such as glanceable visualizations, glanceable displays, peripheral displays, ambient visualizations, or sometimes as forms of casual visualizations. To clarify how glanceability is used in the field of Visualization, we discuss these related terms with respect to visualization concepts, drawing from not only Visualization but also, Vision Sciences, Human-Computer Interaction, and Ubiquitous Computing, revealing how the use of the term glanceable differs in these communities. Drawing from these different perspectives, we discuss specific values for glanceable mobile visualizations: presence & accessibility, simplicity & understandability, as well as suitability & purposefulness. Based on these values, we explore different evaluation methodologies, ranging from lab studies, to online experiments, to evaluation in the field and conclude with a discussion of open challenges in the design of future glanceable mobile visualizations.

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