论文标题

基于功能的个性化键盘生成方法

Ability-Based Methods for Personalized Keyboard Generation

论文作者

Mitchell, Claire L., Cler, Gabriel J., Fager, Susan K., Contessa, Paola, Roy, Serge H., De Luca, Gianluca, Kline, Joshua C., Vojtech, Jennifer M.

论文摘要

这项研究介绍了一种基于个性化键盘生成的能力方法,其中个人的运动和人类计算机的交互数据用于自动计算个性化的虚拟键盘布局。我们的方法集成了一个多向点选择任务,以表征光标控制随时间,距离和方向。该表征会自动使用来开发计算高效的键盘布局,该布局通过捕获方向约束和偏好来优先考虑每个用户的运动能力。我们在一项研究中评估了我们的方法,该研究涉及16名参与者使用惯性感应和面部肌电图作为通道方法,与一般优化的键盘(47.9位/min)相比,使用个性化键盘(52.0位/min),使用个性化键盘(52.0位/分钟)显着提高了通信速率。我们的结果表明,能够有效地表征个人运动能力的能力,以设计个性化键盘以改善沟通。这项工作强调了在设计虚拟接口时集成用户的电机能力的重要性。

This study introduces an ability-based method for personalized keyboard generation, wherein an individual's own movement and human-computer interaction data are used to automatically compute a personalized virtual keyboard layout. Our approach integrates a multidirectional point-select task to characterize cursor control over time, distance, and direction. The characterization is automatically employed to develop a computationally efficient keyboard layout that prioritizes each user's movement abilities through capturing directional constraints and preferences. We evaluated our approach in a study involving 16 participants using inertial sensing and facial electromyography as an access method, resulting in significantly increased communication rates using the personalized keyboard (52.0 bits/min) when compared to a generically optimized keyboard (47.9 bits/min). Our results demonstrate the ability to effectively characterize an individual's movement abilities to design a personalized keyboard for improved communication. This work underscores the importance of integrating a user's motor abilities when designing virtual interfaces.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源