Detail View

Quantifying Wrist-Aiming Habits with A Dual-Sensor Mouse: Implications for Player Performance and Workload
Citations

WEB OF SCIENCE

Citations

SCOPUS

Metadata Downloads

DC Field Value Language
dc.contributor.author Kang, Donghyeon -
dc.contributor.author Kim, Namsub -
dc.contributor.author Kang, Daekaun -
dc.contributor.author Yoon, June-Seop -
dc.contributor.author Kim, Sunjun -
dc.contributor.author Lee, Byungjoo -
dc.date.accessioned 2025-01-20T17:10:15Z -
dc.date.available 2025-01-20T17:10:15Z -
dc.date.created 2024-06-14 -
dc.date.issued 2024-05-14 -
dc.identifier.isbn 9798400703300 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/57544 -
dc.description.abstract Computer mice are widely used today as the primary input device in competitive video games. If a player exhibits more wrist rotation than other players when moving the mouse laterally, the player is said to have stronger wrist-aiming habits. Despite strong public interest, there has been no affordable technique to quantify the extent of a player's wrist-aiming habits and no scientific investigation into how the habits affect player performance and workload. We present a reliable and affordable technique to quantify the extent of a player's wrist-aiming habits using a mouse equipped with two optical sensors (i.e., a dual-sensor mouse). In two user studies, we demonstrate the reliability of the technique and examine the relationship between wrist-aiming habits and player performance or workload. In summary, player expertise and mouse sensitivity significantly impacted wrist-aiming habits; the extent of wrist-aiming showed a positive correlation with upper limb workload. © 2024 Copyright held by the owner/author(s) -
dc.language English -
dc.publisher Association for Computing Machinery -
dc.relation.ispartof CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems -
dc.title Quantifying Wrist-Aiming Habits with A Dual-Sensor Mouse: Implications for Player Performance and Workload -
dc.type Conference Paper -
dc.identifier.doi 10.1145/3613904.3642797 -
dc.identifier.wosid 001266059701052 -
dc.identifier.scopusid 2-s2.0-85194813222 -
dc.identifier.bibliographicCitation Kang, Donghyeon. (2024-05-14). Quantifying Wrist-Aiming Habits with A Dual-Sensor Mouse: Implications for Player Performance and Workload. ACM Conference on Human Factors in Computing Systems, 1–18. doi: 10.1145/3613904.3642797 -
dc.identifier.url https://programs.sigchi.org/chi/2024/program/content/146862 -
dc.citation.conferenceDate 2024-05-11 -
dc.citation.conferencePlace US -
dc.citation.conferencePlace Honolulu -
dc.citation.endPage 18 -
dc.citation.startPage 1 -
dc.citation.title ACM Conference on Human Factors in Computing Systems -
Show Simple Item Record

File Downloads

  • There are no files associated with this item.

공유

qrcode
공유하기

Related Researcher

김선준
Kim, Sunjun김선준

Department of Electrical Engineering and Computer Science

read more

Total Views & Downloads