AutoGain: Gain Function Adaptation with Submovement Efficiency Optimization
This method addresses the problem of inefficient pointing for users of trackpads and emerging devices, offering an incremental improvement over trial-and-error design approaches.
AutoGain tackles the challenge of designing gain functions for indirect pointing devices by individualizing them through submovement-level optimization, resulting in performance comparable to commercial designs in under 30 minutes and showing improvements in a one-month study.
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.