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Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors

机译:使用眼球运动和两个时间性EEG传感器实时控制视频游戏

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摘要

EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of video game with eye movements for asynchronous and noninvasive communication system using two temporal EEG sensors. We used wavelets to detect the instance of eye movement and time-series characteristics to distinguish between six classes of eye movement. A control interface was developed to test the proposed algorithm in real-time experiments with opened and closed eyes. Using visual feedback, a mean classification accuracy of 77.3% was obtained for control with six commands. And a mean classification accuracy of 80.2% was obtained using auditory feedback for control with five commands. The algorithm was then applied for controlling direction and speed of character movement in two-dimensional video game. Results showed that the proposed algorithm had an efficient response speed and timing with a bit rate of 30 bits/min, demonstrating its efficacy and robustness in real-time control.
机译:EEG控制的游戏应用范围很广,从严格的医学应用到完全非医学的应用。游戏不仅可以提供娱乐性,而且可以提供强大的练习动力,从而通过康复系统实现更好的控制。在本文中,我们介绍了使用两个时域EEG传感器的异步和无创通信系统通过眼球运动对视频游戏的实时控制。我们使用小波检测眼睛运动的实例和时间序列特征,以区分六种眼睛运动。开发了一个控制界面,用于在睁眼和闭眼的实时实验中测试提出的算法。使用视觉反馈,使用六个命令进行控制可获得平均分类精度为77.3%。使用听觉反馈进行五个命令控制,平均分类准确率达到80.2%。然后将该算法应用于控制二维视频游戏中角色移动的方向和速度。结果表明,该算法具有高效的响应速度和时序,比特率为30µbits / min,证明了其在实时控制中的有效性和鲁棒性。

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