[1]笪铖璐,陈志阳,黄丽亚. 基于CCA的SSVEP性能研究[J].计算机技术与发展,2015,25(05):52-55.
　DA Cheng-lu,CHEN Zhi-yang,HUANG Li-ya. Study on Performance of SSVEP Based on CCA[J].,2015,25(05):52-55.
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 基于CCA的SSVEP性能研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年05期
页码:
52-55
栏目:
智能、算法、系统工程
出版日期:
2015-05-10

文章信息/Info

Title:
 Study on Performance of SSVEP Based on CCA
文章编号:
1673-629X（2015)05-0052-04
作者:
 笪铖璐; 陈志阳; 黄丽亚
 南京邮电大学 电子科学与工程学院
Author(s):
 DA Cheng-lu; CHEN Zhi-yang; HUANG Li-ya
关键词:
 ; 典型相关分析; 稳态视觉诱发电位; 功率谱密度分析; 准确率
Keywords:
 ; CCA; SSVEP; PSDA; accuracy
分类号:
TP31
文献标志码:
A
摘要:
 文中研究了典型相关分析( CCA)提取视觉稳态诱发电位( SSVEP)响应频率的各项性能指标，分析了数据长度、导联数量、大脑皮层区域对CCA准确率的影响，并得出了定量的结论。准确率会随着数据长度的增加而增加，可以从数据长度为1000的70%左右增长到数据长度为1500的80%。准确率会随着信道数目的增加而增加，也会随着信道在大脑中的位置改变而变化，在后枕部分的准确率是最高的。同时，比较了CCA与功率谱密度分析法( PSDA)在有、无噪声情况下的性能。文中的研究结果为后续SSVEP研究提供了一定的参考。
Abstract:
 It studies the performance of Canonical Correlation Analysis ( CCA) which extracts the frequency response of Steady-State Visual Evoked Potential ( SSVEP) ,analyzes the impact on CCA accuracy made by the data length,the number of leads and the cerebral cortex area,and draws quantitative conclusions. Accuracy of CCA increases with longer data. When the data length is 1 000 samples,the accuracy is about 70%. And when the data length reaches 1 500,the accuracy is up to 80%. Accuracy also increases when the number of channels increases. As well,it changes with the different areas of the brain. In the occipital area,the accuracy is the highest. Meanwhile, compare the performance of the CCA and Power Spectral Density Analysis ( PSDA) under conditions of noise and without noises. The re-sults provide a reference for subsequent SSVEP researches.

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更新日期/Last Update: 2015-06-23