吉林大学学报(信息科学版) ›› 2021, Vol. 39 ›› Issue (1): 121-126.

• • 上一篇    

基于脑机接口的智能家居控制系统

王增尉1a, 刘佳奇1b, 戴 露1b, 李芷萱1b, 王启月1b, 李 蛟2, 赵宏伟b   

  1. 1. 吉林大学 a. 电子科学与技术学院; b. 计算机科学与技术学院, 长春 130012; 2. 吉林大学 图书馆, 长春 130012
  • 收稿日期:2020-05-12 出版日期:2021-03-19 发布日期:2021-03-22
  • 通讯作者: 李蛟(1988— ), 女, 长春人, 吉林大学图书馆馆员, 主要从事科技传播与图书管理研究, (Tel)86-13844899366(E-mail)331754970@qq.com
  • 作者简介:王增尉(1999— ), 男, 山东济宁人, 吉林大学本科生, 主要从事嵌入式人工智能研究,( Tel)86-18804315012 (E-mail)2419274459@qq.com
  • 基金资助:
    吉林省科技发展计划技术攻关基金资助项目(20190302026GX); 吉林省自然科学基金资助项目(20200201037JC); 吉林省高等教育学会高教科研基金资助项目(JGJX2018D10)

Intelligent Home Control System Based on Brain-Computer Interface

WANG Zengwei1a, LIU Jiaqi1b, DAI Lu1b, LI Zhixuan1b, WANG Qiyueb, LI Jiao2, ZHAO Hongwei1b   

  1. 1a. College of Electronic Science and Technology; 1b. College of Computer Science and Technology, Jilin University,Changchun 130012, China; 2. Library, Jilin University, Changchun 130012, China
  • Received:2020-05-12 Online:2021-03-19 Published:2021-03-22

摘要: 为实现家居系统的智能控制, 提出一种基于脑机接口、 脑电信号识别分类和增强现实(AR: Augmented Reality)的解决方案。 通过佩戴设备收集提取脑电图(EEG: Electro Encephalo Gram)信号, 对数据使用小波变换去噪并利用短时傅立叶变换进一步处理, 利用主成分分析(PCA: Principal Component Analysis)进行降维和卷积神经网络(CNN: Convolutional Neural Network)进行分类, 形成分类模型。 根据分类结果得到大脑发出的指令,以此对家居进行控制, 结合 AR 技术能使控制过程可视化且更具交互性, 符合未来智能家居控制方法的发展趋势。

关键词: 脑机接口, 智能家居, EEG 信号, 卷积神经网络, AR 技术

Abstract: In order to achieve the intelligent control of home system, a solution based on brain computer interface, recognition and classification of brain electrical signals and AR (Augmented Reality) is proposed.EEG (Electro Encephalo Gram) signals are collected and extracted from the brain by wearing a device, and the data is de-noised by wavelet transform and further processed by STFT ( Short Time Fourier Transform). Then,PCA(Principal Component Analysis) and CNN(Convolutional Neural Network) are used for classification to form a classification model. According to the classification results, the instructions is obtained from the brain to control the home. Combined with AR technology, the control process can be visualized and is more interactive,which is in line with the development trend of the control method of the future smart home.

Key words: brain computer interface, smart home, the electro encephalo gram (EEG) signal, convolutional neural network(CNN), augmented reality (AR) technology

中图分类号: 

  • TP391