Expanding Touch Interaction Capabilities for Smart-rings: An Exploration of Continual Slide and Microroll Gestures

Abstract

As smart-rings emerge in both research and commercial markets, their limited physical size remains to restrict the interaction potential and input vocabulary possible. Thus, focusing on touch interaction for its natural and preferred input potential, this early work explores the combination of slide and microroll gestures performed by the thumb in continual motion on a smart-ring’s touch capacitive surface. We first capture over 3000 slide and microroll gesture instances, extract features, and generate and test machine learning models that are able to discern the slide and microroll gestures within the same touch instance. Through the use of 18 features, our Random Forest model provides a 92.4% accuracy. We conclude with demonstrations of potential applications utilizing continual slide and microroll gestures, and a short discussion which provides future research directions stemming from the positive results obtained from this preliminary work.

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Publisher Link

https://doi.org/10.1145/3491101.3519714

Citation

Anuradha Herath, Bradley Rey, Sandra Bardot, Sawyer Rempel, Lucas Audette, Huizhe Zheng, Jun Li, Kevin Fan, Da-Yuan Huang, Wei Li, and Pourang Irani. 2022. Expanding Touch Interaction Capabilities for Smart-rings: An Exploration of Continual Slide and Microroll Gestures. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (CHI EA '22). Association for Computing Machinery, New York, NY, USA, Article 292, 1–7. https://doi.org/10.1145/3491101.3519714

Bibtext Entry

@inproceedings{10.1145/3491101.3519714,
author = {Herath, Anuradha and Rey, Bradley and Bardot, Sandra and Rempel, Sawyer and Audette, Lucas and Zheng, Huizhe and Li, Jun and Fan, Kevin and Huang, Da-Yuan and Li, Wei and Irani, Pourang},
title = {Expanding Touch Interaction Capabilities for Smart-Rings: An Exploration of Continual Slide and Microroll Gestures},
year = {2022},
isbn = {9781450391566},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3491101.3519714},
doi = {10.1145/3491101.3519714},
abstract = {As smart-rings emerge in both research and commercial markets, their limited physical size remains to restrict the interaction potential and input vocabulary possible. Thus, focusing on touch interaction for its natural and preferred input potential, this early work explores the combination of slide and microroll gestures performed by the thumb in continual motion on a smart-ring’s touch capacitive surface. We first capture over 3000 slide and microroll gesture instances, extract features, and generate and test machine learning models that are able to discern the slide and microroll gestures within the same touch instance. Through the use of 18 features, our Random Forest model provides a 92.4% accuracy. We conclude with demonstrations of potential applications utilizing continual slide and microroll gestures, and a short discussion which provides future research directions stemming from the positive results obtained from this preliminary work.},
booktitle = {Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems},
articleno = {292},
numpages = {7},
keywords = {smart ring, rolling/sliding gestures, touch interaction, one-handed, thumb interaction, microroll},
location = {New Orleans, LA, USA},
series = {CHI EA '22}
}