Fingerstroke time estimates for touchscreen-based mobile gaming interaction

Human Movement Science (2015)

Ahreum Lee, Kiburm Song, Hokyoung Ryu,Jieun Kim & Gyuhyun Kwon

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Abstract:The growing popularity of gaming applications and ever-faster mobile carrier networks
have called attention to an intriguing issue that is closely related to command input
performance. A challenging mirroring game service, which simultaneously provides game
service to both PC and mobile phone users, allows them to play games against each other
with very different control interfaces. Thus, for efficient mobile game design, it is essential
to apply a new predictive model for measuring how potential touch input compares to the
PC interfaces. The present study empirically tests the keystroke-level model (KLM) for
predicting the time performance of basic interaction controls on the touch-sensitive smartphone
interface (i.e., tapping, pointing, dragging, and flicking). A modified KLM, tentatively
called the fingerstroke-level model (FLM), is proposed using time estimates on regression
models.

The present study developed a modified keystroke-level model (KLM), tentatively called the fingerstroke-level model (FLM), focusing on performance time estimates for touch-sensitive interactions with direct finger movements. This research contributes to extant literature on multiple fronts and a pragmatic solution to designing and assessing mobilebased game application.
Link to read more, http://dx.doi.org/10.1016/j.humov.2015.09.003