2022 July 29
EdgeSelect: Smartwatch Data Interaction with Minimal Screen Occlusion
Type:
Conference
Authors:
Ali Neshati; Aaron Salo; Shariff AM Faleel; Ziming Li; Hai-Ning Liang; Celine Latulipe; Pourang Irani
Venue:
ICMI '22
Date of publication:
2022 July 29
Abstract:
We present EdgeSelect, a linear target selection interaction technique that utilizes a small portion of the smartwatch display, explicitly designed to mitigate the ‘fat finger’ and screen occlusion problems, two of the most common and well-known challenges when interacting with small displays. To design our technique, we first conducted a user study to answer which segments of the smartwatch display have the least screen occlusion while users are interacting with it. We use results from the first experiment to introduce EdgeSelect, a three-layer non-linear interaction technique, which can be used to interact with multiple co-adjacent graphs on the smartwatch by using a region that is the least prone to finger occlusion. In a second experiment, we explore the density limits of the targets possible with EdgeSelect. Finally, we demonstrate the generalizability of EdgeSelect to interact with various types of content.
Citation:
Ali Neshati, Aaron Salo, Shariff Am Faleel, Ziming Li, Hai-Ning Liang, Celine Latulipe, and Pourang Irani. 2022. EdgeSelect: Smartwatch Data Interaction with Minimal Screen Occlusion. In Proceedings of the 2022 International Conference on Multimodal Interaction (ICMI '22). Association for Computing Machinery, New York, NY, USA, 288–298. https://doi.org/10.1145/3536221.3556586
@inproceedings{10.1145/3536221.3556586,
author = {Neshati, Ali and Salo, Aaron and Faleel, Shariff Am and Li, Ziming and Liang, Hai-Ning and Latulipe, Celine and Irani, Pourang},
title = {EdgeSelect: Smartwatch Data Interaction with Minimal Screen Occlusion},
year = {2022},
isbn = {9781450393904},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3536221.3556586},
doi = {10.1145/3536221.3556586},
abstract = {We present EdgeSelect, a linear target selection interaction technique that utilizes a small portion of the smartwatch display, explicitly designed to mitigate the ‘fat finger’ and screen occlusion problems, two of the most common and well-known challenges when interacting with small displays. To design our technique, we first conducted a user study to answer which segments of the smartwatch display have the least screen occlusion while users are interacting with it. We use results from the first experiment to introduce EdgeSelect, a three-layer non-linear interaction technique, which can be used to interact with multiple co-adjacent graphs on the smartwatch by using a region that is the least prone to finger occlusion. In a second experiment, we explore the density limits of the targets possible with EdgeSelect. Finally, we demonstrate the generalizability of EdgeSelect to interact with various types of content.},
booktitle = {Proceedings of the 2022 International Conference on Multimodal Interaction},
pages = {288–298},
numpages = {11},
keywords = {smartwatch, visualization, target selection, interaction technique},
location = {Bengaluru, India},
series = {ICMI '22}
}