title: A novel stimulation method for multi-class SSVEP-BCI using intermodulation frequencies.
abstract: Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has been widely investigated because of its easy system configuration, high information transfer rate (ITR) and little user training. However, due to the limitations of brain responses and the refresh rate of a monitor, the available stimulation frequencies for practical BCI application are generally restricted.
  
  
  
  This study introduced a novel stimulation method using intermodulation frequencies for SSVEP-BCIs that had targets flickering at the same frequency but with different additional modulation frequencies. The additional modulation frequencies were generated on the basis of choosing desired flickering frequencies. The conventional frame-based 'on/off' stimulation method was used to realize the desired flickering frequencies. All visual stimulation was present on a conventional LCD screen. A 9-target SSVEP-BCI based on intermodulation frequencies was implemented for performance evaluation. To optimize the stimulation design, three approaches (C: chromatic; L: luminance; CL: chromatic and luminance) were evaluated by online testing and offline analysis.
  
  
  
  SSVEP-BCIs with different paradigms (C, L, and CL) enabled us not only to encode more targets, but also to reliably evoke intermodulation frequencies. The online accuracies for the three paradigms were 91.67% (C), 93.98% (L), and 96.41% (CL). The CL condition achieved the highest classification performance.
  
  
  
  These results demonstrated the efficacy of three approaches (C, L, and CL) for eliciting intermodulation frequencies for multi-class SSVEP-BCIs. The combination of chromatic and luminance characteristics of the visual stimuli is the most efficient way for the intermodulation frequency coding method.
authors.affiliation: Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300192, People's Republic of China. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, People's Republic of China.
authors.forename: Xiaogang
authors.initials: X
authors.lastname: Chen
authors.forename: Yijun
authors.initials: Y
authors.lastname: Wang
authors.forename: Shangen
authors.initials: S
authors.lastname: Zhang
authors.forename: Shangkai
authors.initials: S
authors.lastname: Gao
authors.forename: Yong
authors.initials: Y
authors.lastname: Hu
authors.forename: Xiaorong
authors.initials: X
authors.lastname: Gao
mesh_terms: D000328:Adult; D000465:Algorithms; D062207:Brain-Computer Interfaces; D003116:Color; D004562:Electrocardiography / Q000379:methods*; D005074:Evoked Potentials, Visual / Q000502:physiology*; D005260:Female; D005425:Flicker Fusion / Q000502:physiology*; D006801:Humans; D008297:Male; D010775:Photic Stimulation / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014793:Visual Cortex / Q000502:physiology*