具有肌电和脑电图输入接口的注视控制义肢

Tomasz Kocejko
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引用次数: 3

摘要

本文设计了一种基于眼动追踪和脑电肌电分析的混合界面来控制假肢臂。所呈现的界面是为完全失去行动能力的四肢瘫痪(由神经退行性疾病或脊髓损伤引起)患者设计的。这个界面的一般目的是部分恢复他们在周围区域移动物体的能力。交互设计假设这样的用户看着环境中的特定物品,并考虑他想要执行的动作,并且假肢手臂执行特定的动作。便携式眼动仪用于确定用户在3D空间中的关注点,而脑电图/肌电图分析允许向处理单元发送伸手,抓取或伸手抓取命令。眼动追踪器的数据使手臂的定位精度达到10厘米。脑电图被证明只能确认某些动作,而肌电模块获得的数据允许通过神经网络对不同的手势(最多三种手势)进行分类,准确率为84%。整个界面允许义肢在无阻碍的3D环境中导航。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gaze controlled prosthetic arm with EMG and EEG input interface
In this paper the hybrid interface for controlling the prosthetic arm by means of eye tracking and EEG/EMG analysis is shown. The presented interface was designed for people with quadriplegia (caused by neurodegenerative disease or spinal cord injure) who completely lost their mobility. The general purpose of this interface is to partially restore their ability of moving the objects in the surrounding area. The interaction design assumes that such a user looks at a specific item in the environment and thinks about the movement he wants to perform and the prosthetic arm performs certain action. The portable eye tracker was used to determine users point of regards in 3D space while EEG/EMG analysis allowed to send a reach, grab or reach'n'grab command to the processing unit. The data from the eye tracker allowed to position the arm with an accuracy up to 10 cm. The EEG was proved only to confirm certain action while the data acquired by the EMG module allowed for classification of different gestures (up to three gestures) by means of neural networks with an 84% accuracy. The overall interface allow navigation of the prosthetic arm in unobstructed 3D environment.
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