Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The main idea of a traditional Steady State Visually Evoked Potentials (SSVEP)-BCI is the activation of commands through gaze control. Hover, 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 ll-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 re 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 re 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.
['Richard M. G. Tello', 'Sandra Mara Torres Müller', 'Muhammad A. Hasan', 'Andre Ferreira', 'Sridhar Krishnan', 'Teodiano Freire Bastos']
I am writing a research paper on a idea An independent-BCI based on SSVEP using Figure-Ground Perception (FGP)
[{"from": "human", "value": "I am writing a research paper on a idea An independent-BCI based on SSVEP using Figure-Ground Perception (FGP)"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The main idea of a traditional Steady State Visually Evoked Potentials (SSVEP)-BCI is the activation of commands through gaze control. Hover, the widely named \u201cdependent\u201d SSVEP-BCIs might not be applicable for patients with ocular motor impairments or severe neuromuscular problems. Nevertheless, an \u201cindependent\u201d 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 ll-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 re 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 re 15.0\u00a0Hz (vase) and 11.0\u00a0Hz (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."}]