期刊文献+

基于眼电的智能输入系统研究 被引量:5

Research of Intelligent Speller System Based on EOG
下载PDF
导出
摘要 为了帮助肢体运动功能障碍患者与外界交流,设计一套基于眨眼眼电的便携式智能输入系统,使用者仅通过眨眼便能控制人机交互界面上的虚拟键盘进行字符输入。该系统中的信号采集模块先对眼电信号经行预处理,然后将其转换为数字信号传输至微处理。微处理首先通过数字形态学方法滤除信号中的尖峰噪声,然后通过动态阈值和归一化、微分算法识别主动眨眼信号,并完成对虚拟键盘的控制,实现中文、英文或数字的输入。选择12名受试者分别在常规实验室、电磁干扰较大的磁共振设备室和户外的运动场进行测试。结果表明,该系统在上述3个不同的环境中能够准确识别眨眼信号并实现中文、英文及数字的输入,而且输入字符的平均准确率不低于98%,中文、英文字符和数字的平均输入速度分别为(2.8±0.3)、(6.6±0.35)、(9.7±0.38)个/min。因此,该系统的抗干扰能力较强,能够帮助肢体运动功能障碍患者实现与外界交流。 A portable intelligent speller system based on blink electro-oculogram( EOG) was designed to help patients of limb movement function disorders to communicate with other people. The user can control virtual keyboard to spell characters by blinking on human-computer interaction( HCI) interface. The signal would be pre-processed by acquisition module of the system. Then the signal was converted to digital signal,and the digital signal was transmitted to microprocessor. Pike noise of the digital signal was firstly filtered by mathematical morphology. Then dynamical threshold algorithm and normalization,differential algorithm were used to detect the blink. According to the information of EOG,virtual keyboard was controlled to spell characters by microprocessor. In this paper,12 subjects were tested the system in three occasions( routine laboratory,magnetic resonance imaging equipment room with the large electromagnetic interference, and outdoor playground). Results showed that the system could accurately identify blink signal and spell characters including Chinese,English and numbers. Besides,the mean average precision of input character was above98%. The average input speeds of Chinese character,English character and number were 2. 8 ± 0. 3,6. 6 ±0. 35 and 9. 7 ± 0. 38( per / min),respectively. Hence the system which has higher interference rejection is appropriate for patient of limb movement function disorders.
出处 《中国生物医学工程学报》 CAS CSCD 北大核心 2015年第6期662-669,共8页 Chinese Journal of Biomedical Engineering
基金 国家重大科学仪器开发专项(2012YQ120046) 国家高技术研究发展计划(863计划)(2015AA020510)
关键词 眼电图 人机交互 嵌入式系统 图形化用户界面 electro-oculogram(EOG) human-computer interaction embedded system graphical user interface
  • 相关文献

参考文献6

  • 1郑敏敏,高小榕.基于眼电的字符输入系统研究[J].中国生物医学工程学报,2012,31(6):801-806. 被引量:5
  • 2Jacob RJK, Kam KS. Eye tracking in humancomputer interaction and usability research: Ready to deliver the promise [J]. Mind, 2003, 2: 573-605.
  • 3Stahl JS, Van Alphen AM, Zeeuw CD. Acomparison of video and magnetic search coil recording of mouse eye movements [J]. Journal of Neuroscience Methods, 2000, 99(1):101-110.
  • 4Kai\|Uwe S, Markus HM. Comparing eye movements recorded by search coil and infrared eye tracking [J]. Journal of Clinical Monitoring and Computing, 2007, 21(1):49-53.
  • 5李卫娜,侯文生,郑小林,彭承琳.基于Electrooculogram的眼动信息识别[J].仪器仪表学报,2007,28(8):1428-1433. 被引量:5
  • 6陈卫东,李昕,刘俊,郝耀耀,廖玉玺,苏煜,张韶岷,郑筱祥.基于数学形态学的眼电信号识别及其应用[J].浙江大学学报(工学版),2011,45(4):644-649. 被引量:4

二级参考文献36

共引文献11

同被引文献36

引证文献5

二级引证文献22

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