Intuitive visualization technique to support eye tracking data analysis: A user-study

While fixation distribution is conventionally visualized using heat maps, there is still a lack of a commonly accepted technique to visualize saccade distributions. Inspired by wind maps and the Oriented Line Integral Convolution (OLIC) technique, we visualize saccades by drawing ink droplets which follow the direction indicated by a flow direction map. This direction map is computed using a kernel density estimation technique over the tangent directions to each saccade gaze point. The image is further blended with the corresponding heat map. It results in an animation or a static image showing main directions of the transitions between different areas of interest. We also present results from a web-based user study where naive non-expert users where asked to identify the direction of the flow and simple patterns. The results showed that these visualizations can successfully be used to support visual analysis of the eye-tracking data. It also showed that the use of animation allows to ease the task and to improve the performance

Visualizing Information on Smartwatch Faces: A Review and Design Space

We present a systematic review and design space for visualizations on smartwatches and the context in which these visualizations are displayed--smartwatch faces. A smartwatch face is the main smartwatch screen that wearers see when checking the time. Smartwatch faces are small data dashboards that present a variety of data to wearers in a compact form. Yet, the usage context and form factor of smartwatch faces pose unique design challenges for visualization. In this paper, we present an in-depth review and analysis of visualization designs for popular premium smartwatch faces based on their design styles, amount and types of data, as well as visualization styles and encodings they included. From our analysis we derive a design space to provide an overview of the important considerations for new data displays for smartwatch faces and other small displays. Our design space can also serve as inspiration for design choices and grounding of empirical work on smartwatch visualization design. We end with a research agenda that points to open opportunities in this nascent research direction. Supplementary material is available at: https://osf.io/nwy2r/.Comment: 13 pages, appendi

Preparing for Perceptual Studies: Position and Orientation of Wrist-worn Smartwatches for Reading Tasks

International audienceDespite the increasing demand for data visualization on mobile devices with small displays, few guidelines exist for designing visualizations for this form factor. To conduct perceptual studies with smartwatches under realistic conditions , we first need to know how to position these devices in front of a viewer. We report the results of a study, in which we investigate how people hold their smartwatches to read information. This is the first in a series of studies we are conducting to understand the perception of visualizations on smartwatches. Our study results show that people hold their watches at a distance of 28 cm in front of them, at a pitch angle of ~50 degrees, and at an angle of ~10 degrees from the line of sight

Reflections on Visualization in Motion for Fitness Trackers

International audienceIn this paper, we reflect on our past work towards understanding how to design visualizations for fitness trackers that are used in motion. We have coined the term "visualization in motion" for visualizations that are used in the presence of relative motion between a viewer and the visualization. Here, we describe how visualization in motion is relevant to sports scenarios. We also provide new data on current smartwatch visualizations for sports and discuss future challenges for visualizations in motion for fitness trackers

Eye-tracking based analysis concept for the evaluation of visualizations

Das Ziel einer Eyetracking-Benutzerstudie ist die Untersuchung und Auswertung einer Forschungsfragestellung anhand von aufgenommen Eyetracking-Daten mit Hilfe von Metriken, statistischen Berechnungen und Visualisierungen. Meist müssen anschließend die Ergebnisse in einem Bericht festgehalten und veröffentlicht werden. Ein Großteil des Arbeitsaufwandes bei einer Auswertung wird in manuelle Aufgaben wie das Eingeben von Fragebögen und Antworten, das Sortieren der Daten, das Durchführen von statistischen Tests und die Erstellung von Visualisierungen aufgewendet. In dieser Diplomarbeit wird ein Konzept für ein Framework vorgestellt, welches auf dem Visual Information Seeking Mantra basiert. Das Framework soll den Benutzer bei der Erstellung, Durchführung und Auswertung einer Eyetracking-Benutzerstudie unterstützen. Dafür werden die Eyetracking- und Probandendaten in einer Datenbank gespeichert und es werden verschiedene Metriken, Statistiken und Visualisierungen zur Verfügung gestellt, die der Benutzer für die Auswertung verwenden kann. Die Ergebnisse aller Berechnungen werden in einer Datenbank gespeichert, so dass der Benutzer die Berechnungen zu späteren Zeitpunkten zur Verfügung hat. Das Framework kann außerdem den Fragebogen der Probanden auswerten und einen Bericht in LaTeX erstellen, welcher die Probandendaten, Boxplotdiagramme und Heatmaps enthält

A Comparison of a Transition-based and a Sequence-based Analysis of AOI Transition Sequences

Several visual analytics (VA) systems are used for analyzing eye-tracking data because they synergize human-in-the-loop exploration with speed and accuracy of the computer. In the VA systems, the choices of visualization techniques could afford discovering certain types of insights while hindering others. Understanding these affordances and hindrances is essential to design effective VA systems. In this paper, we focus on two approaches for visualizing AOI transitions: the transition based approach (exemplified by the radial transition graph, RTG) and the sequence-based approach (exemplified by the Alpscarf). We captured the insights generated by two analysts who individually use each visualization technique on the same dataset. Based on the results, we identify four phases of analytic activities and discuss opportunities that the two visualization approaches can complement each other. We point out design implications for VA systems that combine these visualization approaches

Study: Heart Rate Visualizations on a Virtual Smartwatch to Monitor Physical Activity Intensity

We investigate three visualizations showing heart rate (HR) data collected over time and displayed on a virtual smartwatch, to monitor physical activity intensity allowing a person who is exercising to work towards a specific fitness goal. To understand exercise behavior, we first conducted a survey with 57 participants to know which data they are interested in collecting during the course of their activities (and how is it represented on their devices). To support reaching a specific fitness goal, we designed a bar chart visualization to represent HR data. Among the three visualizations two present an additional chart (i. e., a horizontal and radial bar chart summary), showing the amount of time spent per HR zone (i. e., low, moderate and high intensity). In a controlled study performed in virtual reality, we compared participants’ performance with each visualization asking participants to make a quick and accurate decision monitoring their physical activity intensity. Results from the study show evidence of a difference in task performance between visualizations with and without a summary chart—visualizations showing a summary chart performed better than the version without