Cecotti H, Meena Y K, Prasad G
Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:3330-3333. doi: 10.1109/EMBC.2018.8512909.
A large number of people with disabilities rely on assistive technologies to communicate with their families, to use social media, and have a social life. Despite a significant increase of novel assitive technologies, robust, non-invasive, and inexpensive solutions should be proposed and optimized in relation to the physical abilities of the users. A reliable and robust identification of intentional visual commands is an important issue in the development of eye-movements based user interfaces. The detection of a command with an eyetracking system can be achieved with a dwell time. Yet, a large number of people can use simple hand gestures as a switch to select a command. We propose a new virtual keyboard based on the detection of ten commands. The keyboard includes all the letters of the Latin script (upper and lower case), punctuation marks, digits, and a delete button. To select a command in the keyboard, the user points the desired item with the gaze, and select it with hand gesture. The system has been evaluated across eight healthy subjects with five predefined hand gestures, and a button for the selection. The results support the conclusion that the performance of a subject, in terms of speed and information transfer rate (ITR), depends on the choice of the hand gesture. The best gesture for each subject provides a mean performance of $8 . 77 \pm 2 .90$ letters per minute, which corresponds to an ITR of $57 . 04 \pm 14 .55$ bits per minute. The results highlight that the hand gesture assigned for the selection of an item is inter-subject dependent.
大量残疾人依靠辅助技术与家人交流、使用社交媒体并拥有社交生活。尽管新型辅助技术有了显著增加，但仍应根据用户的身体能力提出并优化强大、非侵入性且价格低廉的解决方案。在基于眼动的用户界面开发中，可靠且强大的有意视觉命令识别是一个重要问题。使用眼动追踪系统检测命令可以通过停留时间来实现。然而，许多人可以使用简单的手势作为选择命令的开关。我们提出了一种基于十种命令检测的新型虚拟键盘。该键盘包括拉丁字母表的所有字母（大写和小写）、标点符号、数字以及一个删除按钮。要在键盘中选择一个命令，用户用目光指向所需项目，并用手势进行选择。该系统已通过五个预定义的手势和一个选择按钮，在八名健康受试者身上进行了评估。结果支持这样的结论：受试者在速度和信息传输率（ITR）方面的表现取决于手势的选择。每个受试者的最佳手势每分钟平均能输入$8.77 \pm 2.90$个字母，这对应着每分钟$57.04 \pm 14.55$比特的信息传输率。结果突出表明，用于选择项目的手势因受试者而异。
