AutoGain: Gain Function Adaptation with Submovement Efficiency Optimization

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A4 Artikkeli konferenssijulkaisussa

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2020-04-21

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en

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12

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CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract

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.

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| openaire: EC/H2020/637991/EU//COMPUTED

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Lee, B, Nancel, M, Kim, S & Oulasvirta, A 2020, AutoGain: Gain Function Adaptation with Submovement Efficiency Optimization . in CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems ., 3376244, ACM, ACM SIGCHI Annual Conference on Human Factors in Computing Systems, Honolulu, Hawaii, United States, 26/04/2020 . https://doi.org/10.1145/3313831.3376244