A well-designed control-to-display gain function can improve pointing performance with indirect pointing devices like trackpads. However, the design of gain functions is challenging and mostly based on trial and error. AutoGain is a novel method to individualize a gain function for indirect pointing devices in contexts where cursor trajectories can be tracked. It gradually improves pointing efficiency by using a novel submovement-level tracking+optimization technique that minimizes aiming error (undershooting/overshooting) for each submovement. We first show that AutoGain can produce, from scratch, gain functions with performance comparable to commercial designs, in less than a half-hour of active use. Second, we demonstrate AutoGain's applicability to emerging input devices (here, a Leap Motion controller) with no reference gain functions. Third, a one-month longitudinal study of normal computer use with AutoGain showed performance improvements from participants' default functions.
|Title of host publication||CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems|
|Publisher||Association for Computing Machinery|
|Publication status||Published - 2020 Apr 21|
|Event||2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 - Honolulu, United States|
Duration: 2020 Apr 25 → 2020 Apr 30
|Name||Conference on Human Factors in Computing Systems - Proceedings|
|Conference||2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020|
|Period||20/4/25 → 20/4/30|
Bibliographical notePublisher Copyright:
© 2020 ACM.
All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design
- Human-Computer Interaction