微特电机 ›› 2019, Vol. 47 ›› Issue (3): 82-86.doi: 1004-7018-47-3-82

• 读者园地 • 上一篇    

基于脑电波控制的智能轮椅系统

常宇,杨风,郝骞   

  1. 中北大学,太原 030051
  • 收稿日期:2018-06-13 出版日期:2019-03-28 发布日期:2019-04-02
  • 作者简介:常宇(1994—),女,硕士研究生,主要研究方向为机器人智能控制。

Intelligent Wheelchair System Based on EEG Control

CHANG Yu,YANG Feng,HAO Qian   

  1. North University of China,Taiyuan 030051,China
  • Received:2018-06-13 Online:2019-03-28 Published:2019-04-02

摘要:

针对重度残疾病人四肢丧失活动能力而无法自由行动的问题,研究了一种基于脑电波控制轮椅的方法。脑电波传感器采集脑电波数据后通过蓝牙发送给核心控制模块,并采用改进后的小波变换法、共空间模式法、模糊支持向量机对脑电波信号进行去噪、特征处理以及模式识别处理。结合基于蚁群算法的路径规划,实现轮椅准确无碰撞地到达目的地的要求。

关键词: 脑电波, 小波变换, 特征提取, 模式识别, 路径规划

Abstract:

For severely disabled patients who are unable to move freely because of their disability, a wheelchair control method based on EEG was presented. The EEG sensor collects the EEG data and sends it to the core control module via bluetooth. The improved wavelet transform method, co-space mode method and fuzzy support vector machine were designed to realize denoising, feature processing and pattern recognition processing of EEG signals. Finally, the path planning based on ant colony algorithm was combined to meet the requirement for wheelchair to reach the destination accurately without collision.

Key words: EEG, wavelet transform, feature extraction, pattern recognition, path planning

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