A Novel Visual Keyboard System for Disabled People/Individuals Using Hybrid SSVEP Based Brain Computer Interface

D. Saravanakumar, M. Reddy
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引用次数: 3

Abstract

This paper aims to design a new stimulus paradigm for SSVEP based keyboard system. The proposed paradigm was implemented using black and white checkerboard flickering visual stimuli along with the integration of videooculography (VOG). The on-screen speller was designed using three frequencies. The goal of this study is how to increase more number of targets using less number of stimulus frequencies. It is achieved by the use of VOG data. The study was carried out using 36 selected characters. A webcam is integrated along with the system to obtain VOG data. The webcam captures the images of the eyes, which in turn is used to detect the eye gaze direction. This additional information from VOG overcomes the limitations of SSVEP based spelling system. The extended multivariate synchronization index (EMSI) method is used for SSVEP frequency recognition. Offline and online analysis of the experiment were conducted and the duration of recognition of each character required by the participant was calculated based on the classification accuracy. Online experiment was conducted on 10 subjects to validate the accuracy and information transfer rate (ITR) of the system. An average online detection accuracy of 90.46 % was obtained with the ITR of 65.98 bits/minutes.
一种基于混合SSVEP脑机接口的残疾人视觉键盘系统
本文旨在为基于SSVEP的键盘系统设计一种新的刺激范式。该方法采用黑白棋盘闪烁视觉刺激,并结合视频摄影技术(VOG)实现。屏幕上的拼写器是使用三个频率设计的。本研究的目的是如何使用更少的刺激频率来增加更多的目标。它是通过使用VOG数据实现的。选取36个性状进行研究。系统集成了一个网络摄像头来获取VOG数据。网络摄像头捕捉眼睛的图像,这些图像反过来被用来检测眼睛的凝视方向。来自VOG的这些附加信息克服了基于SSVEP的拼写系统的局限性。将扩展多元同步索引(EMSI)方法用于SSVEP频率识别。对实验进行离线和在线分析,并根据分类准确率计算参与者需要识别的每个字符的持续时间。对10名受试者进行了在线实验,验证了系统的准确性和信息传输率。平均在线检测准确率为90.46%,ITR为65.98 bits/min。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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