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Demonstrating palm touch: the palm as an additional input modality on commodity smartphones

Published: 03 September 2018 Publication History

Abstract

Touchscreens are the most successful input method for smartphones. Despite their flexibility, touch input is limited to the location of taps and gestures. We present Palm Touch, an additional input modality that differentiates between touches of fingers and the palm. Touching the display with the palm can be a natural gesture since moving the thumb towards the device's top edge implicitly places the palm on the touchscreen. We developed a model that differentiates between finger and palm touch with an accuracy of 99.53% in realistic scenarios. In this demonstration, we exhibit different use cases for Palm Touch, including the use as a shortcut and for improving reachability. In a previous evaluation, we showed that participants perceive the input modality as intuitive and natural to perform. Moreover, they appreciate Palm Touch as an easy and fast solution to address the reachability issue during one-handed smartphone interaction compared to thumb stretching or grip changes.

References

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Sebastian Boring, David Ledo, Xiang 'Anthony' Chen, Nicolai Marquardt, Anthony Tang, and Saul Greenberg. 2012. The Fat Thumb: Using the Thumb's Contact Size for Single-handed Mobile Interaction. In Proceedings of the 14th International Conference on Human-computer Interaction with Mobile Devices and Services (Mobile HCI '12). ACM, New York, NY, USA, 39--48.
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Ashley Colley and Jonna Häkkilä. 2014. Exploring Finger Specific Touch Screen Interaction for Mobile Phone User Interfaces. In Proceedings of the 26th Australian Computer-Human Interaction Conference on Designing Futures: The Future of Design (OzCHI '14). ACM, New York, NY, USA, 539--548.
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Hyunjae Gil, Do Young Lee, Seunggyu Im, and Ian Oakley. 2017. Tri Tap: Identifying Finger Touches on Smartwatches. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). ACM, New York, NY, USA, 3879--3890.
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Chris Harrison, Julia Schwarz, and Scott E. Hudson. 2011. Tap Sense: Enhancing Finger Interaction on Touch Surfaces. In Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology (UIST '11). ACM, New York, NY, USA, 627--636.
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Seongkook Heo and Geehyuk Lee. 2011. Forcetap: Extending the Input Vocabulary of Mobile Touch Screens by Adding Tap Gestures. In Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services (Mobile HCI '11). ACM, New York, NY, USA, 113--122.
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Huy Viet Le, Patrick Bader, Thomas Kosch, and Niels Henze. 2016. Investigating Screen Shifting Techniques to Improve One-Handed Smartphone Usage. In Proceedings of the 9th Nordic Conference on Human-Computer Interaction (Nordi CHI '16). ACM, New York, NY, USA.
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Huy Viet Le, Thomas Kosch, Patrick Bader, Sven Mayer, and Niels Henze. 2018. Palm Touch: Using the Palm as an Additional Input Modality on Commodity Smartphones. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, 10.
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Huy Viet Le, Sven Mayer, Patrick Bader, Frank Bastian, and Niels Henze. 2017. Interaction Methods and Use Cases for a Full-Touch Sensing Smartphone. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '17). ACM, New York, NY, USA, 2730--2737.
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Huy Viet Le, Sven Mayer, Patrick Bader, and Niels Henze. 2017. A Smartphone Prototype for Touch Interaction on the Whole Device Surface. In Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services (Mobile HCI '17). ACM, New York, NY, USA, Article 100, 8 pages.
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Huy Viet Le, Sven Mayer, Patrick Bader, and Niels Henze. 2018. Fingers' Range and Comfortable Area for One-Handed Smartphone Interaction Beyond the Touchscreen. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI'18). ACM, New York, NY, USA.
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Huy Viet Le, Sven Mayer, Katrin Wolf, and Niels Henze. 2016. Finger Placement and Hand Grasp During Smartphone Interaction. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '16). ACM, New York, NY, USA, 2576--2584.
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Sven Mayer, Huy Viet Le, and Niels Henze. 2017. Estimating the Finger Orientation on Capacitive Touchscreens Using Convolutional Neural Networks. In Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces (ISS '17). ACM, New York, NY, USA, 220--229.
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Robert Xiao, Julia Schwarz, and Chris Harrison. 2015. Estimating 3D Finger Angle on Commodity Touchscreens. In Proceedings of the 2015 International Conference on Interactive Tabletops & Surfaces (ITS '15). ACM, New York, NY, USA, 47--50.

Cited By

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  • (2021)Review of Capacitive Touchscreen Technologies: Overview, Research Trends, and Machine Learning ApproachesSensors10.3390/s2114477621:14(4776)Online publication date: 13-Jul-2021
  • (2019)Investigating Unintended Inputs for One-Handed Touch Interaction Beyond the TouchscreenProceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services10.1145/3338286.3340145(1-14)Online publication date: 1-Oct-2019
  • (2019)Investigating the feasibility of finger identification on capacitive touchscreens using deep learningProceedings of the 24th International Conference on Intelligent User Interfaces10.1145/3301275.3302295(637-649)Online publication date: 17-Mar-2019
  1. Demonstrating palm touch: the palm as an additional input modality on commodity smartphones

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    cover image ACM Conferences
    MobileHCI '18: Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct
    September 2018
    445 pages
    ISBN:9781450359412
    DOI:10.1145/3236112
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Publication History

    Published: 03 September 2018

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    Author Tags

    1. capacitive image
    2. machine learning
    3. palm
    4. smartphone

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    Overall Acceptance Rate 202 of 906 submissions, 22%

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    Cited By

    View all
    • (2021)Review of Capacitive Touchscreen Technologies: Overview, Research Trends, and Machine Learning ApproachesSensors10.3390/s2114477621:14(4776)Online publication date: 13-Jul-2021
    • (2019)Investigating Unintended Inputs for One-Handed Touch Interaction Beyond the TouchscreenProceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services10.1145/3338286.3340145(1-14)Online publication date: 1-Oct-2019
    • (2019)Investigating the feasibility of finger identification on capacitive touchscreens using deep learningProceedings of the 24th International Conference on Intelligent User Interfaces10.1145/3301275.3302295(637-649)Online publication date: 17-Mar-2019

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