title: Toward a hybrid brain-computer interface based on repetitive visual stimuli with missing events.
abstract: Steady-state visually evoked potentials (SSVEPs) can be elicited by repetitive stimuli and extracted in the frequency domain with satisfied performance. However, the temporal information of such stimulus is often ignored. In this study, we utilized repetitive visual stimuli with missing events to present a novel hybrid BCI paradigm based on SSVEP and omitted stimulus potential (OSP).
  
  
  
  Four discs flickering from black to white with missing flickers served as visual stimulators to simultaneously elicit subject's SSVEPs and OSPs. Key parameters in the new paradigm, including flicker frequency, optimal electrodes, missing flicker duration and intervals of missing events were qualitatively discussed with offline data. Two omitted flicker patterns including missing black/white disc were proposed and compared. Averaging times were optimized with Information Transfer Rate (ITR) in online experiments, where SSVEPs and OSPs were identified using Canonical Correlation Analysis in the frequency domain and Support Vector Machine (SVM)-Bayes fusion in the time domain, respectively.
  
  
  
  The online accuracy and ITR (mean ± standard deviation) over nine healthy subjects were 79.29 ± 18.14 % and 19.45 ± 11.99 bits/min with missing black disc pattern, and 86.82 ± 12.91 % and 24.06 ± 10.95 bits/min with missing white disc pattern, respectively. The proposed BCI paradigm, for the first time, demonstrated that SSVEPs and OSPs can be simultaneously elicited in single visual stimulus pattern and recognized in real-time with satisfied performance. Besides the frequency features such as SSVEP elicited by repetitive stimuli, we found a new feature (OSP) in the time domain to design a novel hybrid BCI paradigm by adding missing events in repetitive stimuli.
authors.affiliation: Department of Instrument Science and Technology, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, ShaanXi, China.
authors.forename: Yingying
authors.initials: Y
authors.lastname: Wu
authors.affiliation: Department of Instrument Science and Technology, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, ShaanXi, China.
authors.forename: Man
authors.initials: M
authors.lastname: Li
authors.affiliation: Department of Instrument Science and Technology, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, ShaanXi, China. wangpele@gmail.com.
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D062207:Brain-Computer Interfaces; D003199:Computer Systems; D004569:Electroencephalography / Q000379:methods; D005074:Evoked Potentials, Visual / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D010775:Photic Stimulation / Q000379:methods*; D060388:Support Vector Machine
keywords: Brain Computer Interface (BCI); Electroencephalogram (EEG); Omitted stimulus potential (OSP); Steady-state visually evoked potential (SSVEP)