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人体运动的费茨定律数据集与新的推导

A New Derivation and Dataset for Fitts' Law of Human Motion

作者:Ken Goldberg;Siamak Faridani;Ron Alterovitz 作者单位:EECS Department,University of California, Berkeley 加工时间:2014-03-12 信息来源:EECS 索取原文[20 页]
关键词:费茨定律;人机交互界面;时间动作研究;人体运动时间
摘 要:This paper contributes new theory and new experiments. For the former, we provide a succinct derivation of the square-root model based on optimal control theory. We present data from two experimental user studies, one a controlled (in-lab) study and the second an uncontrolled (online) study with a total of 94,580 timing measurements. We consider three two-parameter models that relate motion duration to the ratio of target distance over target size: LOG (the classic logarithmic function), SQR (square-root), and LOG' (logarithmic plus 1.0). We find that: (1) the data from the controlled and uncontrolled studies are remarkably consistent; (2) for homogeneous targets, the SQR model yields a significantly better fit than LOG or LOG', except with the most difficult targets (i.e., the ratio of target distance over target size is large) where the models are not significantly different; (3) for heterogenous targets, SQR yields a significantly better fit than LOG for easier targets and LOG yields a significantly better fit than both LOG and SQR on more difficult targets.
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