Detecting users handedness for ergonomic adaptation of mobile user interfaces

Markus Löchtefeld; Phillip Schardt; Antonio Krüger; Sebastian Boring

doi:10.1145/2836041.2836066

Detecting users handedness for ergonomic adaptation of mobile user interfaces

Markus Löchtefeld, Phillip Schardt, Antonio Krüger, Sebastian Boring

Department of Computer Science

15 Citations (Scopus)

Abstract

Often, we operate mobile devices using only one hand. The hand thereby serves two purposes: holding the device and operating the touch screen with the thumb. The current trend of increasing screen sizes however, makes it close to impossible to reach all parts of the screen (especially the top area) for users with average hand sizes. One solution is to offer adaptive user interfaces for such one-handed interactions. These modes have to be triggered manually and thus induce a critical overhead. They are further designed to bring all content closer, regardless of whether the phone is operated with the left or right hand. In this paper, we present an algorithm that allows determining the users' interacting hand from their unlocking behavior. Our algorithm correctly distinguishes one- and twohanded usage as well as left- and right handed unlocking in 98.51% of all cases. This is achieved through a k-nearest neighbor comparison of the internal sensor readings of the smartphone during the unlocking process.

Original language	English
Title of host publication	MUM '15 Proceedings of the 14th International Conference on Mobile and Ubiquitous Multimedia
Number of pages	5
Publisher	Association for Computing Machinery
Publication date	2015
Pages	245-249
ISBN (Print)	978-1-4503-3605-5
DOIs	https://doi.org/10.1145/2836041.2836066
Publication status	Published - 2015
Event	14th International Conference on Mobile and Ubiquitous Multimedia, MUM 2015 - Linz, Austria Duration: 30 Nov 2015 → 2 Dec 2015

Conference

Conference	14th International Conference on Mobile and Ubiquitous Multimedia, MUM 2015
Country/Territory	Austria
City	Linz
Period	30/11/2015 → 02/12/2015
Sponsor	ACM Special Interest Group on Computer-Human Interaction (SIGCHI), Association for Computing Machinery, Johannes Kepler Universitat Linz, University of Applied Sciences Upper Austria (FH OOE)

Keywords

Adaptive interfaces
Ergonomics
Handedness
Sensor fusion
Unlocking

Access to Document

10.1145/2836041.2836066

Cite this

Detecting users handedness for ergonomic adaptation of mobile user interfaces. / Löchtefeld, Markus; Schardt, Phillip; Krüger, Antonio et al.

MUM '15 Proceedings of the 14th International Conference on Mobile and Ubiquitous Multimedia. Association for Computing Machinery, 2015. p. 245-249.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Löchtefeld, M, Schardt, P, Krüger, A & Boring, S 2015, Detecting users handedness for ergonomic adaptation of mobile user interfaces. in MUM '15 Proceedings of the 14th International Conference on Mobile and Ubiquitous Multimedia. Association for Computing Machinery, pp. 245-249, 14th International Conference on Mobile and Ubiquitous Multimedia, MUM 2015, Linz, Austria, 30/11/2015. https://doi.org/10.1145/2836041.2836066

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AU - Krüger, Antonio

AU - Boring, Sebastian

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AB - Often, we operate mobile devices using only one hand. The hand thereby serves two purposes: holding the device and operating the touch screen with the thumb. The current trend of increasing screen sizes however, makes it close to impossible to reach all parts of the screen (especially the top area) for users with average hand sizes. One solution is to offer adaptive user interfaces for such one-handed interactions. These modes have to be triggered manually and thus induce a critical overhead. They are further designed to bring all content closer, regardless of whether the phone is operated with the left or right hand. In this paper, we present an algorithm that allows determining the users' interacting hand from their unlocking behavior. Our algorithm correctly distinguishes one- and twohanded usage as well as left- and right handed unlocking in 98.51% of all cases. This is achieved through a k-nearest neighbor comparison of the internal sensor readings of the smartphone during the unlocking process.

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KW - Unlocking

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ER -

Detecting users handedness for ergonomic adaptation of mobile user interfaces

Abstract

Conference

Keywords

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