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A virtual speller system using SSVEP and electrooculogram
Advanced Engineering Informatics ( IF 8.0 ) Pub Date : 2020-02-20 , DOI: 10.1016/j.aei.2020.101059
D. Saravanakumar , M. Ramasubba Reddy

In this study a novel hybrid speller/keyboard system that combines electro-oculogram (EOG) with steady state visual evoked potential (SSVEP) is designed. Conventional EOG based speller system needs continuous eye movements for selecting a single target and it has a limitation on total number of targets. In this proposed speller, 36 targets are divided into nine groups, which includes alphabets, numbers and special characters. Target selection consists of two stages. Various eye movements (gaze, blinks, winks) are used for selecting the target groups and SSVEP is used to identify the target from the selected group. The cue guided online and free spelling tasks were performed on 10 subjects to validate the proposed system. The average classification accuracy of the proposed system is 94.16% with the information transfer rate (ITR) of 70.99 (±9.95) bits/min. For validating the proposed speller system, the classification accuracy and ITR were compared with conventional speller systems.



中文翻译:

使用SSVEP和眼电图的虚拟拼写系统

在这项研究中,设计了一种新颖的混合式拼写/键盘系统,该系统将眼电位图(EOG)与稳态视觉诱发电位(SSVEP)相结合。传统的基于EOG的拼写系统需要连续的眼球运动来选择单个目标,并且目标总数有限。在此拟议的拼写器中,将36个目标分为9个组,其中包括字母,数字和特殊字符。目标选择包括两个阶段。各种眼动(凝视,眨眼,眨眼)用于选择目标组,SSVEP用于从所选组中识别目标。提示引导的在线和免费拼写任务在10个主题上执行,以验证建议的系统。所提出系统的平均分类精度为94.16%,信息传输率(ITR)为70.99(±9)。95)位/分钟。为了验证提议的拼写系统,将分类准确性和ITR与常规拼写系统进行了比较。

更新日期:2020-02-20
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