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Qifan Guo

dblp:217/9434 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input
gesture input
0.312018
WrisText: One-handed Text Entry on Smartwatch using Wrist Gestures · CHI 2018
Interaction techniques and input › text entry
smartwatch text entry
0.312018
WrisText: One-handed Text Entry on Smartwatch using Wrist Gestures · CHI 2018
Interaction techniques and input
text entry
0.312018
WrisText: One-handed Text Entry on Smartwatch using Wrist Gestures · CHI 2018
Interaction techniques and input › text entry
text entry evaluation
0.112018
WrisText: One-handed Text Entry on Smartwatch using Wrist Gestures · CHI 2018

Methods — techniques the papers use, named apart from their topics

user study · 0.3keyboard layout optimization · 0.3
YearPublicationVenuePosition
2018 WrisText: One-handed Text Entry on Smartwatch using Wrist Gestures
abstract
We present WrisText - a one-handed text entry technique for smartwatches using the joystick-like motion of the wrist. A user enters text by whirling the wrist of the watch hand, towards six directions which each represent a key in a circular keyboard, and where the letters are distributed in an alphabetical order. The design of WrisText was an iterative process, where we first conducted a study to investigate optimal key size, and found that keys needed to be 55º or wider to achieve over 90% striking accuracy. We then computed an optimal keyboard layout, considering a joint optimization problem of striking accuracy, striking comfort, word disambiguation. We evaluated the performance of WrisText through a five-day study with 10 participants in two text entry scenarios: hand-up and hand-down. On average, participants achieved a text entry speed of 9.9 WPM across all sessions, and were able to type as fast as 15.2 WPM by the end of the last day.
Jun Gong 0002, Zheer Xu, Qifan Guo, Teddy Seyed, Xiang 'Anthony' Chen, Xiaojun Bi 0001, Xing-Dong Yang
CHI3