An independent-BCI based on SSVEP using Figure-Ground Perception (FGP). (April 2016)

• Record Type: Journal Article
• Authors: Tello, Richard M.G.; Müller, Sandra M.T.; Hasan, Muhammad A.; Ferreira, André; Krishnan, Sridhar; Bastos, Teodiano F.
• Is Part Of: Biomedical signal processing and control. Volume 26(2016)
• Page Start: 69
• Page End: 79
• Publication Date: 2016-04
• Subjects: AAC alternative and augmentative communication -- ALS amyotrophic lateral sclerosis -- BCI brain-computer interface -- CAR Common Average Reference -- CCA canonical correlation analysis -- CTI Command Transfer Interval -- EEG electroencephalogram -- ITR Information Transfer Rate -- LCD liquid crystal display -- LED light emitting diodes -- LIS locked-in syndrome -- MSI Multivariate Synchronization Index -- STD standard deviation -- SSVEP Steady-State Visual Evoked Potentials -- VEP Visual Evoked Potential; SSVEP-BCI -- Perception -- Spatial attention -- MSI -- CCA -- Brain signals; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2015.12.010
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: It is the first study published where perception for SSVEP-BCIs was evaluated in off/on-line tasks. An improvement in performance using the channel Oz in a SSVEP-BCI by FGP was noticeable. Channel Oz is the best channel for characterization of visual perception in SSVEP-BCIs. Visual selectivity through the perception and neural mechanism of spatial attention in an SSVEP-BCI was confirmed. This new BCI-SSVEP based on FGP has shown a new approach compared to the traditional way. Abstract: The main idea of a traditional Steady State Visually Evoked Potentials (SSVEP)-BCI is the activation of commands through gaze control. However, the widely named "dependent" SSVEP-BCIs might not be applicable for patients with ocular motor impairments or severe neuromuscular problems. Nevertheless, an "independent" SSVEP-BCIs might be a potential approach to solve this problem. This study presents a novel independent-BCI based on SSVEP using Figure-Ground Perception (FGP), terminology widely known and used in Gestalt psychology for object recognition by means of changes in perception. This BCI proposes to identify two different targets that represent commands in a limited visual space without needing to shift the gaze by the paradigm of covert attention. For that purpose, the well-known example of Rubin's face-vase in FGP was used. The traditional EEG signal analysis consists of three steps: filtering, feature extraction and classification. In this work, two techniques were used for performance comparison, and the classification was obtained through a criterion of maxima for both techniques. Ten subjects participated in this study in offline tests and five subjects for online tests. The flickering frequencies were 15.0 Hz (vase) and 11.0 Hz (faces). Our results demonstrate that the electrode Oz is the best channel for characterization of visual perception, from a quantitative point of view based on the canonical correlation, after a channel analysis by independent way. Regarding the classification, MSI technique was more accurate in relation to CCA, in all the cases with same conditions, either using three electrodes or a single electrode (Oz), even for different window lengths. The online performance appeared to decrease as participants switched from Face (82.7%) to Vase (76%) stimulus. These results are consistent with our results in offline tasks. Muscular activity related to the eye movements was also evaluated using a commercial device of eye tracking (Eye Tribe). These findings strongly support the hypothesis of visual selectivity by means of perception and neural mechanism of spatial attention.