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Development of a human computer interaction system based on multi-modal gaze tracking methods

机译:基于多模式注视跟踪方法的人机交互系统的开发

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In this paper, we design a human computer interaction (HCI) system for the locked-in syndrome (LIS) patients which combines the eye movement signals and Electroencephalogram (EEG) signals. The LIS describes patients who are faced with the quadriplegia, aphonia and facial paralysis problems. However, they are still conscious, have the ability to hear and give a hint with the blink or eye movements. Thus, the LIS patients suffer great miseries due to the difficulty to communicate with the outside. This HCI system can help the LIS patients effectively communicate with the outside. Firstly, the system gets the subject's gaze point on the screen through the acquisition data of eye movement information, and obtains the button that the subject is focusing on. Then, the system confirms or cancels the button according to the classification results of the EEG signals. The computer can execute the commands of the corresponding button to bridge the communication between the subjects and the outside. When the subject stares at the screen unconsciously, the button will not respond because there is no confirmation of the EEG signals. The subject's eyes can be relaxed. The EEG signals are divided into two categories, and the classification results can be trained to reach a high classification accuracy (more than 90%). In the test, the average accuracy is about 80% in the case of using eye tracker alone. In the case of EEG, the average accuracy can reach more than 85%. The HCI system can realize some hardware control, simple voice interaction and typing with virtual keyboard. The system can make subjects communicate with the outside through the eye movement and EEG signals with high accuracy.
机译:在本文中,我们为锁定综合征(LIS)患者设计了一种人眼交互(HCI)系统,该系统结合了眼动信号和脑电图(EEG)信号。 LIS描述了面临四肢瘫痪,失音和面部瘫痪问题的患者。但是,他们仍然有意识,能够听到眨眼或眼球动作并给出提示。因此,LIS患者由于难以与外界交流而遭受极大的痛苦。该HCI系统可以帮助LIS患者有效地与外界沟通。首先,系统通过眼动信息的获取数据在屏幕上获取被摄对象的凝视点,并获取被摄对象聚焦的按钮。然后,系统根据EEG信号的分类结果确认或取消按钮。计算机可以执行相应按钮的命令,以桥接对象与外界之间的通信。当被摄对象不自觉地凝视屏幕时,该按钮将不会响应,因为未确认EEG信号。被摄对象的眼睛可以放松。脑电信号分为两类,可以训练分类结果以达到较高的分类精度(超过90%)。在测试中,仅使用眼动仪的平均准确度约为80%。对于EEG,平均准确度可以达到85%以上。 HCI系统可以实现一些硬件控制,简单的语音交互以及使用虚拟键盘的打字。该系统可以使被摄体通过眼球运动和EEG信号与外界进行高精度交流。

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