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Detection of eye closing/opening from EOG and its application in robotic arm control

机译:从Eog的眼睛关闭/开口检测及其在机械臂控制中的应用

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Detection of eye closing/opening from alpha-blocking in the EEG of occipital region has been used to build human-machine interfaces. This paper presents an alternative method for detection of eye closing/opening from EOG signals in an online setting. The accuracies for correct detection of eye closing and opening operations with the proposed techniques were found to be 95.6% and 91.9% respectively for 8 healthy subjects. These techniques were then combined with the detection of eye blinks, the accuracy of which turned out to be 96.9%. This was then used to build an interface for robotic arm control for a pick and place task. The same task was also carried out using a haptic device as a master. The speed and accuracy for these two methods were then compared to assess quantitatively the ease of using this interface. It appears that the proposed interface will be very useful for persons with neurodegenerative disorders who can perform eye closing/opening and eye blinks. (c) 2019 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
机译:从枕骨区脑电图中从α-封闭的眼睛闭合/开口的检测已被用于构建人机接口。本文介绍了在在线设置中从EOG信号检测眼睛关闭/开口的替代方法。对于8个健康受试者,发现具有所提出的技术的正确检测和开放式操作的精度分别为95.6%和91.9%。然后将这些技术与眼睛眨眼的检测相结合,精度为96.9%。然后,这将用于为机器人手臂控制构建接口,用于挑选和放置任务。也使用触觉设备作为主设备进行相同的任务。然后比较这两种方法的速度和精度,以定量评估使用该界面的易于评估。似乎所提出的界面对可以进行眼睛关闭/开口和眼睛闪烁的神经变性障碍的人非常有用。 (c)2019年纳雷斯州博士科学学院生物医学研究所。 elsevier b.v出版。保留所有权利。

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