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Design and evaluation of a time adaptive multimodal virtual keyboard

机译:时间自适应多模式虚拟键盘的设计与评估

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The usability of virtual keyboard based eye-typing systems is currently limited due to the lack of adaptive and user-centered approaches leading to low text entry rate and the need for frequent recalibration. In this work, we propose a set of methods for the dwell time adaptation in asynchronous mode and trial period in synchronous mode for gaze based virtual keyboards. The rules take into account commands that allow corrections in the application, and it has been tested on a newly developed virtual keyboard for a structurally complex language by using a two-stage tree-based character selection arrangement. We propose several dwell-based and dwell-free mechanisms with the multimodal access facility wherein the search of a target item is achieved through gaze detection and the selection can happen via the use of a dwell time, soft-switch, or gesture detection using surface electromyography in asynchronous mode; while in the synchronous mode, both the search and selection may be performed with just the eye-tracker. The system performance is evaluated in terms of text entry rate and information transfer rate with 20 different experimental conditions. The proposed strategy for adapting the parameters over time has shown a significant improvement (more than 40%) over non-adaptive approaches for new users. The multimodal dwell-free mechanism using a combination of eye-tracking and soft-switch provides better performance than adaptive methods with eye-tracking only. The overall system receives an excellent grade on adjective rating scale using the system usability scale and a low weighted rating on the NASA task load index, demonstrating the user-centered focus of the system.
机译:由于缺乏自适应和以用户为中心的方法,导致文本输入率较低,并且需要频繁进行重新校准,因此基于虚拟键盘的眼型系统目前受到限制。在这项工作中,我们提出了一套方法,用于基于注视的虚拟键盘在异步模式下的停留时间适应和在同步模式下的试用期适应。该规则考虑了允许在应用程序中进行更正的命令,并且已使用基于树的两阶段字符选择安排在新开发的虚拟键盘上针对结构复杂的语言对其进行了测试。我们提出了几种具有多模式访问功能的基于驻留和无驻留的机制,其中通过凝视检测来实现对目标项目的搜索,并且可以通过使用驻留时间,软开关或使用表面进行手势检测来进行选择异步模式下的肌电图;在同步模式下,仅通过眼动仪即可执行搜索和选择。通过在20种不同的实验条件下的文本输入率和信息传输率来评估系统性能。与新用户的非自适应方法相比,提出的随时间调整参数的策略已显示出显着改进(超过40%)。与仅使用眼动追踪的自适应方法相比,结合了眼动追踪和软开关功能的多模式无驻留机制提供了更好的性能。整个系统使用系统可用性量表在形容词评定量表上获得了优异的评分,并且在NASA任务负载指数上获得了较低的加权评分,从而证明了系统以用户为中心。

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