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A Study of Mobile Robot Control using EEG Emotiv Epoch Sensor

机译:eEG EMEG EMEGIV IPoch传感器的移动机器人控制研究

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摘要

The study was using an EEG Emotiv Epoc+ sensor to recognize brain activity for controlling a mobile robot's movement. The study used Emotiv Control Panel software for EEG command identification. The commands will be interfaced inside Mind Your OSCs software and processing software which processed inside an Arduino Controller. The output of the Arduino is a movement command (ie. forward, backward, turn left, and turn right). The training methods of the system composed of three sets of thinking mode. First, thinking with doing facial expressions. Second, thinking with visual help. Third, thinking mentally without any help. In the first set, there are two configurations thinking with facial expression help as command of the mobile robot. Final results of the system are the second facial expressions configuration as the best facial expressions method with success rate 88.33 %. The second facial expression configuration has overall response time 1.60175 s faster than the first facial expressions configuration. In these two methods have dominant signals on the frontal lobe. The second facial expressions method have overall respond time 6.12 and 9.53 s faster than thinking with visual, and thinking without help respectively.
机译:该研究正在使用EEG EMECTIV +传感器来识别用于控制移动机器人运动的大脑活动。该研究使用了EMEG命令识别的EMECV控制面板软件。该命令将在内心介入您的OSCS软件和处理软件,该软件在Arduino控制器内部处理。 Arduino的输出是移动命令(即,向前,向后转,向左转,然后右转)。由三组思维模式组成的系统的训练方法。首先,思考面部表情。其次,思考视觉帮助。第三,在没有任何帮助的情况下思考。在第一组中,有两种配置与面部表情有助于移动机器人的命令。该系统的最终结果是第二个面部表达配置,作为最佳面部表达方法,成功率为88.33%。第二个面部表情配置具有总体响应时间1.60175 S比第一面部表达式更快。在这两种方法中,在额叶上具有主导信号。第二个面部表情方法总体响应时间为6.12和9.53,而不是视觉思维,分别没有帮助。

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