Pereira Anna, Wachs Juan P, Park Kunwoo, Rempel David
University of California at Berkeley.
Purdue University, West Lafayette, Indiana.
Hum Factors. 2015 Jun;57(4):607-21. doi: 10.1177/0018720814559307. Epub 2014 Nov 24.
The purpose of this study was to develop a lexicon for 3-D hand gestures for common human-computer interaction (HCI) tasks by considering usability and effort ratings.
Recent technologies create an opportunity for developing a free-form 3-D hand gesture lexicon for HCI.
Subjects (N = 30) with prior experience using 2-D gestures on touch screens performed 3-D gestures of their choice for 34 common HCI tasks and rated their gestures on preference, match, ease, and effort. Videos of the 1,300 generated gestures were analyzed for gesture popularity, order, and response times. Gesture hand postures were rated by the authors on biomechanical risk and fatigue.
A final task gesture set is proposed based primarily on subjective ratings and hand posture risk. The different dimensions used for evaluating task gestures were not highly correlated and, therefore, measured different properties of the task-gesture match.
A method is proposed for generating a user-developed 3-D gesture lexicon for common HCIs that involves subjective ratings and a posture risk rating for minimizing arm and hand fatigue.
本研究旨在通过考虑可用性和努力程度评级,为常见的人机交互(HCI)任务开发一个三维手势词汇表。
最近的技术为开发用于人机交互的自由形式三维手势词汇表创造了机会。
有在触摸屏上使用二维手势经验的受试者(N = 30)对34项常见人机交互任务执行他们选择的三维手势,并对手势的偏好、匹配度、易用性和努力程度进行评级。对生成的1300个手势的视频进行分析,以确定手势的受欢迎程度、顺序和响应时间。作者对手势的手部姿势进行生物力学风险和疲劳评级。
主要基于主观评级和手部姿势风险提出了一个最终的任务手势集。用于评估任务手势的不同维度之间相关性不高,因此测量的是任务-手势匹配的不同属性。
提出了一种为常见人机交互生成用户开发的三维手势词汇表的方法,该方法涉及主观评级和姿势风险评级,以尽量减少手臂和手部疲劳。