Text entry tap accuracy and exploration of tilt controlled layered interaction on smartwatches

Mark D Dunlop; Marc Roper; Gennaro Imperatore

doi:10.1145/3098279.3098560

Text entry tap accuracy and exploration of tilt controlled layered interaction on smartwatches

Mark D Dunlop, Marc Roper, Gennaro Imperatore

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

6 Citations (Scopus)

194 Downloads (Pure)

Abstract

Design of text entry on small screen devices, e.g. smartwatches, faces two related challenges: trading off a reasonably sized keyboard area against space to display the entered text and the concern over "fat fingers". This paper investigates tap accuracy and revisits layered interfaces to explore a novel layered text entry method. A two part user study identifies preferred typing and reading tilt angles and then investigates variants of a tilting layered keyboard against a standard layout. We show good typing speed (29 wpm) and very high accuracy on the standard layout – contradicting fears of fat-fingers limiting watch text-entry. User feedback is positive towards tilting interaction and we identify ~14° tilt as a comfortable typing angle. However, layering resulted in slightly slower and more erroneous entry. The paper contributes new data on tilt angles and key offsets for smartwatch text entry and supporting evidence for the suitability of QWERTY on smartwatches.

Original language	English
Title of host publication	MobileHCI '17
Subtitle of host publication	Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services
Place of Publication	New York
Number of pages	11
DOIs	https://doi.org/10.1145/3098279.3098560
Publication status	Published - 7 Sept 2017
Event	MobileHCI 2017 - Vienna, Austria Duration: 4 Sept 2017 → 7 Sept 2017 http://mobilehci.acm.org/2017/

Conference

Conference	MobileHCI 2017
Country/Territory	Austria
City	Vienna
Period	4/09/17 → 7/09/17
Internet address	http://mobilehci.acm.org/2017/

Keywords

HCI
usability
text-entry
interaction design
user studies
smartwatch
human-computer interaction
tap accuracy
layered text entry
tilting

Access to Document

10.1145/3098279.3098560

Dunlop-etal-MobileHCI-2017-Text-entry-tap-accuracy-and-exploration-of-tilt-controlled-layered-interactionAccepted author manuscript, 1.23 MB

Cite this

@inproceedings{1dc1e808b20744a493c84bb8f4ce67c1,

title = "Text entry tap accuracy and exploration of tilt controlled layered interaction on smartwatches",

abstract = "Design of text entry on small screen devices, e.g. smartwatches, faces two related challenges: trading off a reasonably sized keyboard area against space to display the entered text and the concern over {"}fat fingers{"}. This paper investigates tap accuracy and revisits layered interfaces to explore a novel layered text entry method. A two part user study identifies preferred typing and reading tilt angles and then investigates variants of a tilting layered keyboard against a standard layout. We show good typing speed (29 wpm) and very high accuracy on the standard layout – contradicting fears of fat-fingers limiting watch text-entry. User feedback is positive towards tilting interaction and we identify ~14° tilt as a comfortable typing angle. However, layering resulted in slightly slower and more erroneous entry. The paper contributes new data on tilt angles and key offsets for smartwatch text entry and supporting evidence for the suitability of QWERTY on smartwatches.",

keywords = "HCI, usability, text-entry, interaction design, user studies, smartwatch, human-computer interaction, tap accuracy, layered text entry, tilting",

author = "Dunlop, {Mark D} and Marc Roper and Gennaro Imperatore",

note = "{\textcopyright} {Owner/Author | ACM} {2017}. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in MobileHCI '17 Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services , http://dx.doi.org/10.1145/10.1145/3098279.3098560.; MobileHCI 2017 ; Conference date: 04-09-2017 Through 07-09-2017",

year = "2017",

month = sep,

day = "7",

doi = "10.1145/3098279.3098560",

language = "English",

isbn = "9781450350754",

booktitle = "MobileHCI '17",

url = "http://mobilehci.acm.org/2017/",

}

Text entry tap accuracy and exploration of tilt controlled layered interaction on smartwatches. / Dunlop, Mark D ; Roper, Marc ; Imperatore, Gennaro.
MobileHCI '17 : Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services. New York, 2017. 23.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

TY - GEN

T1 - Text entry tap accuracy and exploration of tilt controlled layered interaction on smartwatches

AU - Dunlop, Mark D

AU - Roper, Marc

AU - Imperatore, Gennaro

N1 - © {Owner/Author | ACM} {2017}. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in MobileHCI '17 Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services , http://dx.doi.org/10.1145/10.1145/3098279.3098560.

PY - 2017/9/7

Y1 - 2017/9/7

N2 - Design of text entry on small screen devices, e.g. smartwatches, faces two related challenges: trading off a reasonably sized keyboard area against space to display the entered text and the concern over "fat fingers". This paper investigates tap accuracy and revisits layered interfaces to explore a novel layered text entry method. A two part user study identifies preferred typing and reading tilt angles and then investigates variants of a tilting layered keyboard against a standard layout. We show good typing speed (29 wpm) and very high accuracy on the standard layout – contradicting fears of fat-fingers limiting watch text-entry. User feedback is positive towards tilting interaction and we identify ~14° tilt as a comfortable typing angle. However, layering resulted in slightly slower and more erroneous entry. The paper contributes new data on tilt angles and key offsets for smartwatch text entry and supporting evidence for the suitability of QWERTY on smartwatches.

AB - Design of text entry on small screen devices, e.g. smartwatches, faces two related challenges: trading off a reasonably sized keyboard area against space to display the entered text and the concern over "fat fingers". This paper investigates tap accuracy and revisits layered interfaces to explore a novel layered text entry method. A two part user study identifies preferred typing and reading tilt angles and then investigates variants of a tilting layered keyboard against a standard layout. We show good typing speed (29 wpm) and very high accuracy on the standard layout – contradicting fears of fat-fingers limiting watch text-entry. User feedback is positive towards tilting interaction and we identify ~14° tilt as a comfortable typing angle. However, layering resulted in slightly slower and more erroneous entry. The paper contributes new data on tilt angles and key offsets for smartwatch text entry and supporting evidence for the suitability of QWERTY on smartwatches.

KW - HCI

KW - usability

KW - text-entry

KW - interaction design

KW - user studies

KW - smartwatch

KW - human-computer interaction

KW - tap accuracy

KW - layered text entry

KW - tilting

UR - http://mobilehci.acm.org/2017/

UR - http://dl.acm.org/event.cfm?id=RE395

U2 - 10.1145/3098279.3098560

DO - 10.1145/3098279.3098560

M3 - Conference contribution book

SN - 9781450350754

BT - MobileHCI '17

CY - New York

T2 - MobileHCI 2017

Y2 - 4 September 2017 through 7 September 2017

ER -

Text entry tap accuracy and exploration of tilt controlled layered interaction on smartwatches

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Mark Dunlop

MobileHCI 2017 Watch Text Entry Data

Cite this

Text entry tap accuracy and exploration of tilt controlled layered interaction on smartwatches

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Profiles

Mark Dunlop

Datasets

MobileHCI 2017 Watch Text Entry Data

Cite this