Design and Implementation of Intelligent Wheelchair System Based on EEG Control

摘要

In order to improve the self-care ability of disabled people, this paper designs and implements an intelligent wheelchair system based on EEG control. The human EEG signal collected by the sensor is sent to the core control board through Bluetooth device. And the wavelet packet transform is used for noise reduction and feature extraction. Then the multi-class SVM technology is used to recognize the EEG signal and realize the intelligent control of the wheelchair in various motion states. In the experiment, the average Kappa coefficient reach 0.622, which is better than BP neural network. Moreover, the system has short response time and high recognition rate, which further showing the effectiveness and reliability of the proposed method.