title: Classifying real and imaginary finger press tasks on a P300-based brain-computer interface.
abstract: Brain computer interfaces based on P300 and sensory-motor rhythms are widely studied and recent advances show some interest in the combination of the two. In this paper, typical P300 paradigm is modified by adding animation guide of the finger press as a stimulus and by using different response strategies (silent counting and actual/imaginary left or right index finger press following the animation). Both P300 potentials and sensory-motor rhythms are directly exploited and discussed. Classification results showed that even under very demanding conditions, which was, 200 ms inter-stimulus interval of the P300 stimuli and actual/imaginary finger press once per 1.6s, the paradigm can evoke both P300 potentials and sensory-motor rhythms simultaneously. Actual finger press increased single trial P300 selection accuracy of different subjects by 5-29.5% compared with silent counting; imaginary finger press did not increase the P300 selection accuracy apparently for most subjects except the two who were very poor at counting task. This showed by using different interface design and adopting certain mental response strategies, the 'BCI illiteracy' may be cured. Also imaginary task had good performance of left versus right classification (with the best subject reached 81.1% of accuracy), which is an additional information that can be used to improve system performance.
authors.affiliation: Qiushi Academy for Advanced Studies and College of Computer Science, Zhejiang University, Hangzhou 310027, China.
authors.forename: Jicai
authors.initials: J
authors.lastname: Zhang
authors.forename: Weidong
authors.initials: W
authors.lastname: Chen
authors.forename: Yanlei
authors.initials: Y
authors.lastname: Gu
authors.forename: Bian
authors.initials: B
authors.lastname: Wu
authors.forename: Yu
authors.initials: Y
authors.lastname: Qi
authors.forename: Xiaoxiang
authors.initials: X
authors.lastname: Zheng
mesh_terms: D000328:Adult; D000465:Algorithms; D001288:Attention / Q000502:physiology; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000145:classification / Q000379:methods; D018913:Event-Related Potentials, P300 / Q000502:physiology; D005260:Female; D005385:Fingers / Q000502:physiology*; D006225:Hand / Q000502:physiology; D006801:Humans; D007092:Imagination; D008297:Male; D015233:Models, Statistical; D009048:Motor Skills; D015203:Reproducibility of Results; D012984:Software; D014584:User-Computer Interface