Steady-State Motion Visual Evoked Potentials Produced by Oscillating Newton's Rings: Implications for Brain-Computer Interfaces

• Published in: PloS one Vol. 7; no. 6; p. e39707
• Main Authors: Xie, Jun, Xu, Guanghua, Wang, Jing, Zhang, Feng, Zhang, Yizhuo
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 19.06.2012; Public Library of Science (PLoS)
• Subjects: Adaptation; Adult; Biology; Brain research; Brain-Computer Interfaces; Computer Science; Contraction; Correlation analysis; Electroencephalography; Engineering; Evoked Potentials, Visual - physiology; Human motion; Human-computer interface; Humans; Interfaces; Laboratories; Magnetic fields; Male; Mechanical engineering; Motion detection; Motion Perception - physiology; Photic Stimulation - methods; Retailing; Steady state; Stimulation; Stimulators; Visual evoked potentials; Visual perception; Visual stimuli; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0039707

In this study, we utilize a special visual stimulation protocol, called motion reversal, to present a novel steady-state motion visual evoked potential (SSMVEP)-based BCI paradigm that relied on human perception of motions oscillated in two opposite directions. Four Newton's rings with the oscillating expansion and contraction motions served as visual stimulators to elicit subjects' SSMVEPs. And four motion reversal frequencies of 8.1, 9.8, 12.25 and 14 Hz were tested. According to Canonical Correlation Analysis (CCA), the offline accuracy and ITR (mean ± standard deviation) over six healthy subjects were 86.56 ± 9.63% and 15.93 ± 3.83 bits/min, respectively. All subjects except one exceeded the level of 80% mean accuracy. Circular Hotelling's T-Squared test (T2 circ) also demonstrated that most subjects exhibited significantly strong stimulus-locked SSMVEP responses. The results of declining exponential fittings exhibited low-adaptation characteristics over the 100-s stimulation sequences in most experimental conditions. Taken together, these results suggest that the proposed paradigm can provide comparable performance with low-adaptation characteristic and less visual discomfort for BCI applications.