Mind-Wave Controlled Robot: An Arduino Robot Simulating the Wheelchair for Paralyzed Patients

Chi Hang Cheng, Shuai Li, Seifedine Kadry
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引用次数: 11

Abstract

This project attempts to implement an Arduino robot to simulate a brainwave-controlled wheelchair for paralyzed patients with an improved controlling method. The robot should be able to move freely in anywhere under the control of the user and it is not required to predefine any map or path. An accurate and natural controlling method is provided, and the user can stop the robot any time immediately to avoid risks or danger. This project is using a low-cost and a brainwave-reading headset which has only a single lead electrode (Neurosky mind wave headset) to collect the EEG signal. BCI will be developed by sending the EEG signal to the Arduino Mega and control the movement of the robot. This project used the eye blinking as the robot controlling method as the eye blinking will cause a significant pulse in the EEG signal. By using the neural network to classify the blinking signal and the noise, the user can send the command to control the robot by blinking twice in a short period of time. The robot will be evaluated by driving in different places to test whether it can follow the expected path, avoid the obstacles, and stop in a specific position.
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心波控制机器人:Arduino机器人模拟瘫痪患者轮椅
本项目试图通过改进控制方法,实现Arduino机器人模拟瘫痪患者的脑波控制轮椅。机器人应该能够在用户的控制下在任何地方自由移动,不需要预先定义任何地图或路径。提供了一种精确自然的控制方法,用户可以随时立即停止机器人,避免风险或危险。这个项目使用的是一种低成本的脑波读取耳机,它只有一个铅电极(Neurosky脑波耳机)来收集脑电图信号。BCI将通过将脑电图信号发送到Arduino Mega并控制机器人的运动来开发。本课题采用眨眼作为机器人的控制方法,因为眨眼会在脑电图信号中产生一个显著的脉冲。通过神经网络对眨眼信号和噪声进行分类,用户可以在短时间内发出两次眨眼的指令来控制机器人。机器人将通过在不同的地方行驶来评估,以测试它是否能遵循预期的路径,避开障碍物,并在特定的位置停下来。
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