TY - GEN
T1 - One-thumb Text Acquisition on Force-assisted Miniature Interfaces for Mobile Headsets
AU - Lee, Lik Hang
AU - Zhu, Yiming
AU - Yau, Yui Pan
AU - Braud, Tristan
AU - Su, Xiang
AU - Hui, Pan
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - Touchscreen interfaces are shrinking and even dis-appearing on mobile headsets. The existing approaches for text acquisition on mobile headsets, for instance, speech commands and hand gestures, are cumbersome and coarse. In this paper, we show the feasibility of interaction on a miniature area as small as 12 ∗ 13 mm2 that offers an input alternative on small form-factor devices such as smartwatches, smart rings, or the spectacles frames of mobile headsets. To this end, we propose and implement two interaction approaches, namely FRS and DupleFR, for acquiring textual contents on mobile headsets. Both approaches leverage force-assisted interaction on a miniature-size interface. They enable the user to acquire textual content with various granularities such as characters, words, sentences, paragraphs, and the entire text. After 8 sessions, 22 participants with FRS and DupleFR achieve the peak performance of respectively 11.455 and 10.611 seconds per textual acquisition with accuracy rates of 91.41% and 94.95%. Although FRS and DupleFR as indirect manipulations are disadvantageous, they are at least 37.06% faster than the commercial standards designated to direct manipulation on touchscreens.
AB - Touchscreen interfaces are shrinking and even dis-appearing on mobile headsets. The existing approaches for text acquisition on mobile headsets, for instance, speech commands and hand gestures, are cumbersome and coarse. In this paper, we show the feasibility of interaction on a miniature area as small as 12 ∗ 13 mm2 that offers an input alternative on small form-factor devices such as smartwatches, smart rings, or the spectacles frames of mobile headsets. To this end, we propose and implement two interaction approaches, namely FRS and DupleFR, for acquiring textual contents on mobile headsets. Both approaches leverage force-assisted interaction on a miniature-size interface. They enable the user to acquire textual content with various granularities such as characters, words, sentences, paragraphs, and the entire text. After 8 sessions, 22 participants with FRS and DupleFR achieve the peak performance of respectively 11.455 and 10.611 seconds per textual acquisition with accuracy rates of 91.41% and 94.95%. Although FRS and DupleFR as indirect manipulations are disadvantageous, they are at least 37.06% faster than the commercial standards designated to direct manipulation on touchscreens.
UR - http://www.scopus.com/inward/record.url?scp=85086768015&partnerID=8YFLogxK
U2 - 10.1109/PerCom45495.2020.9127378
DO - 10.1109/PerCom45495.2020.9127378
M3 - Conference article published in proceeding or book
AN - SCOPUS:85086768015
SN - 9781728146584
T3 - 18th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2020
BT - 18th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2020
Y2 - 23 March 2020 through 27 March 2020
ER -