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Brain Based Control of Wheelchair

机译：轮椅的基于脑的控制

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摘要

This paper presents a brain based control of the wheelchair for physically impaired users. The design of the system is focused on receiving electroencephalographic (EEG) signals from the brain, processing and turning the system and then performing control of the wheelchair. The number of experimental measurements of brain activity has been obtained using human control commands of the wheelchair. The obtained data including EEG signals and control commands are used to design brain based control mechanism in training mode. The classification of brain signals has been done using a Support Vector Machine (SVM) and neural networks. The training data is used before using the system under real conditions. Then test data is applied to measure the accuracy of the control. The system designed in this paper is adjusted to control a wheelchair with five commands: move forward, move backward, stop, turn left and turn right in real conditions. The provided approach allows reducing the probability of misclassification and improving control accuracy of the wheelchair.
机译：本文介绍了针对残障人士的轮椅基于大脑的控制方法。该系统的设计集中在从大脑接收脑电图（EEG）信号，处理和转动系统，然后执行轮椅控制。已经使用轮椅的人类控制命令获得了大脑活动的实验测量次数。所获得的包括脑电信号和控制命令的数据被用于设计训练模式下基于大脑的控制机制。使用支持向量机（SVM）和神经网络已经完成了脑信号的分类。在实际条件下使用系统之前，请先使用训练数据。然后，将测试数据应用于测量控件的准确性。本文中设计的系统通过五个命令进行了调整，以控制轮椅：在实际情况下前进，后退，停止，左转和右转。所提供的方法允许减少错误分类的可能性并提高轮椅的控制精度。

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