Eyes-Free Graph Legibility: Using Skin-Dragging to Provide a Tactile Graph Visualization on the Arm
Recent technological advances have enabled novel tactile displays which have mainly focused on providing shorter sensations for notifications and/or simple messages. These have been primarily been used to enhance the user experience. In contrast, conveying information via data charts, such as a line graph, remains largely unexplored. To address this gap, we developed a tactile display prototype. Our prototype uses skin-dragging, a method to produce longer tactile perceptions from dragging a tip on the skin, as the primary means to convey the data. We postulate that if such an approach is successful, it could convey the data in eyes-free scenarios, an element common for on-the-go computing. In an experiment (n=12), we compare the recognition performance of graphs with two different skin-dragging properties, Full-Drag and Dot. The results show that participants performed both techniques equally well, but our Full-Drag technique was greatly preferred. We conclude with design guidelines for tactile displays that focus on graph representations.
Sandra Bardot, Sawyer Rempel, Bradley Rey, Ali Neshati, Yumiko Sakamoto, Carlo Menon and Pourang Irani. 2020. Eyes-Free Graph Legibility: Using Skin-Dragging to Provide a Tactile Graph Visualization on the Arm. In 11th Augmented Human International Conference (AH ’20), May 27–29, 2020, Winnipeg, MB, Canada. ACM, NewYork, NY, USA, 8pages. https://doi.org/10.1145/3396339.3396344