期刊文献+

基于DSP和ARM的便携式脑电信号处理系统的实现 被引量:4

Portable EEG Signal Processing System Based on DSP and ARM
下载PDF
导出
摘要 为使脑一机接口技术(brain-computer interface,BCI)面向实用化、产品化,建立便携式的处理平台成为重要研究问题;系统采用现场可编程门阵列(FPGA)控制VGA显示器,设计了多功能视觉诱发刺激器,实时在线产生多种组合模式的刺激信号,诱发稳态视觉诱发电位;信号采集后放入到数字信号处理器(DSP)中,经过FIR滤波和FFT算法的处理后,得到辨识度较高的视觉诱发电位信号,并由无线将数据发送给STM32处理器,在LCD触屏上实时显示;实验结果表明系统实时采集、处理、显示脑电信号,相对于目前的BCI系统实现了多平台的便携式。 In order to make it possible for the brain - computer interface (BCI) to get rid of the PC, so establishing practical and pragmatic products, as well as a portable processing platform has become a vital study. This system adopts field-programmable gate array (FPGA) to control VGA monitor and design a multi purpose visual evoked stimulator, thus the system can produce a variety of combinations of real-time online mode stimulation signals to induce steady-state visual evoked potential of people. When the signal was collected into a digital signal processor (DSP), the FIR and FFT will process this signal so as to obtain a higher recognizable of the visual evoked potential signals. Then the data will be transmitted by radio to the processor STM32 and display on the LCD touch screen at the real time. This system acquires, processes and displays EEG at the real-time, thus it achieved the portable pattern from the stimulator, acquisition and processing platform to display. Besides, it is available to be transplanted into other miniature devices.
出处 《计算机测量与控制》 北大核心 2014年第9期2981-2982,2986,共3页 Computer Measurement &Control
基金 国家自然科学基金项目(61178081) 校级科研项目(KJ13-01 YJS10-03)
关键词 脑-机接口 视觉诱发电位 FIR FFT LCD brain- machine interfaces visual evoked potential FIR FFT LCD
  • 相关文献

参考文献7

二级参考文献26

共引文献47

同被引文献31

  • 1李维捉,郭强.液晶显示应用技术[M].北京:电子工业出版社,2003.
  • 2姚军,吕颖琦.液晶显示器响应时间光电自动测量仪[P].中国专利:200510049606.5,2005-9-28.
  • 3Wo|paw J R, Birbaumer N, Heetderks W J, et al. Brain-computer interface technology : a review of the first international meeting. IEEE Transactions on Rehabilitation Engineering, 2000; 8 (2) : 164--173.
  • 4Vaughan T M, Heetderks W J, Trejo L J, et al. Brain-computer in- terface technology: a review of the second international meeting. IEEE Transactions on Neural Systems and Rehabilitation Engineering: A Publication of The IEEE Engineering in Medicine and Biology Soci- ety, 2003; 11(2) : 94--109.
  • 5Nijhoh A, Tan D. Brain-computer interfacing for intelligent systems. Intelligent Systems, IEEE, 2008 ; 23 (3) : 72--79.
  • 6Wu Z, Yao D. A study on SSVEP-based BCI. Journal of Electronic Science and Technology of China, 2009 ; 7 ( 1 ) : 7--11.
  • 7Wei Q G, Zou X, Lu Z W, et al. Design and implementation of a mental telephone system based on steady-state visual evoked poten- tial. Journal of Computational Information Systems, 2014 ; 10 ( 2 ) : 547--554.
  • 8Lin Z L, Zhang C S, Wu W, et al. Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. Biomedical En- gineering, IEEE Transactions on, 2006 ; 53 (12) : 2610--2614.
  • 9Bin G, Gao X, Yan Z, et al. An online multi-channel SSVEP- based brain-computer interface using a canonical correlation analysis method. Journal of Neural Engineering, 2009; 6(4) :1771--1779.
  • 10邓志东,李修全,郑宽浩,姚文韬.一种基于SSVEP的仿人机器人异步脑机接口控制系统[J].机器人,2011,33(2):129-135. 被引量:16

引证文献4

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部