title: Combining canonical correlation analysis and infinite reference for frequency recognition of steady-state visual evoked potential recordings: a comparison with periodogram method.
abstract: Steady-state visual evoked potentials (SSVEP) are the visual system responses to a repetitive visual stimulus flickering with the constant frequency and of great importance in the study of brain activity using scalp electroencephalography (EEG) recordings. However, the reference influence for the investigation of SSVEP is generally not considered in previous work. In this study a new approach that combined the canonical correlation analysis with infinite reference (ICCA) was proposed to enhance the accuracy of frequency recognition of SSVEP recordings. Compared with the widely used periodogram method (PM), ICCA is able to achieve higher recognition accuracy when extracts frequency within a short span. Further, the recognition results suggested that ICCA is a very robust tool to study the brain computer interface (BCI) based on SSVEP.
authors.affiliation: Bio-Information College, Chongqing University of Posts and Telecommunications, Chongqing 400065, China Bioimaging Core, Faculty of Health Sciences, University of Macau, Macau SAR, China Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
authors.forename: Yin
authors.initials: Y
authors.lastname: Tian
authors.affiliation: Bio-Information College, Chongqing University of Posts and Telecommunications, Chongqing 400065, China Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
authors.forename: Fali
authors.initials: F
authors.lastname: Li
authors.affiliation: Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Xu
authors.affiliation: Bioimaging Core, Faculty of Health Sciences, University of Macau, Macau SAR, China.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Yuan
authors.affiliation: Bio-Information College, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
authors.forename: Dechun
authors.initials: D
authors.lastname: Zhao
authors.affiliation: Bio-Information College, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
authors.forename: Haiyong
authors.initials: H
authors.lastname: Zhang
mesh_terms: D000328:Adult; D000465:Algorithms; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods*; D005074:Evoked Potentials, Visual / Q000502:physiology*; D006801:Humans; D008297:Male; D009991:Oscillometry / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010775:Photic Stimulation / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013223:Statistics as Topic
keywords: Steady-state visual evoked potentials; brain computer interface; canonical correlation analysis with infinite reference; frequency recognition; periodogram