Influence of stimuli color on steady-state visual evoked potentials based BCI wheelchair control

Singla, Rajesh; Khosla, Arun; Jha, Rakesh Kumar

doi:10.4236/jbise.2013.611131

Cited by 25 publications

(13 citation statements)

References 11 publications

(14 reference statements)

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“…S, M and L cone cells are therefore sensitive to blue (short-wavelength), green (medium-wavelength) and red (long-wavelength) light respectively. The brain combines the information from each cone cells to give different perceptions to different colors; as a result, the SSVEP strength elicited with different colors of the stimuli will be different [14]. In SSVEP based BCIs, visual stimulus modulated at different frequencies are simultaneously presented to the user.…”

Section: • Steady State Visually Evoked Potentials (Ssvep):-mentioning

confidence: 99%

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Screen Task Experiments for Eeg Signals Based on Ssvep Brain Computer Interface.

Fraga¹,

Escobedo²

2018

IJAR

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Development BCI system based stay state visual evoked potential (SSVEP), require establish the characteristics of the stimuli presented the user for optimal development of the extraction of signal characteristics; for it is necessary to determine the stimulation system and the evidence perform for detecting events. There are many types of stimulators that can be used to evoke the SSVEP: monitors include cathode ray tube (CRT) and liquid crystal display (LCD) or an array of light emitting diode (LED). This paper aims to show the different tests and methodologies that have been presented in different studies for generating visual stimuli in a short period of time.

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Section: • Steady State Visually Evoked Potentials (Ssvep):-mentioning

confidence: 99%

“…In a single trial, all the four frequencies were performed three times and the same procedure was repeated for another three trials, keeping a five minutes break between each trial. The time for completing one session for each subject was about 30 minutes [14].…”

Section: Square Flickered:-mentioning

confidence: 99%

Screen Task Experiments for Eeg Signals Based on Ssvep Brain Computer Interface.

Fraga¹,

Escobedo²

2018

IJAR

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“…Different stimuli have been used for SSVEP BCI-based applications, as reviewed by [14]. The same review also revealed that stimulation frequencies in the low (1-12 Hz) and medium (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) Hz) frequency band have been more often applied than those in the high frequency band (30-60 Hz). The first is graphic alternation, in which a simple form (circle, rectangles) is successively displayed and hidden at the preferred frequency.…”

Section: Related Workmentioning

confidence: 99%

Do the stimuli of an SSVEP-based BCI really have to be the same as the stimuli used for training it?

Évain

Argelaguet

Casiez

et al. 2016

Brain-Computer Interfaces

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International audienceDoes the stimulation used during the training on an SSVEP-based BCI have to be similar to that of the end use? We recorded six-channel EEG data from 12 subjects in various conditions of distance between targets, and of difference in color between targets. Our analysis revealed that the stimulation configuration used for training which leads to the best classification accuracy is not always the one which is closest to the end use configuration. We found that the distance between targets during training is of little influence if the end use targets are close to each other, but that training at far distance can lead to a better accuracy for far distance end use (p < .01). Additionally, an interaction effect is observed between training and testing color (p < .001): while training with monochrome targets leads to good performance only when the test context involves monochrome targets as well, a classifier trained on colored targets can be efficient for both colored and monochrome targets. In a nutshell, in the context of SSVEP-based BCI, training using distant targets of different colors seems to lead to the best and more robust performance in all end use contexts

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“…Steady-state visual evoked potential (SSVEP) is one of the most common brain responses in brain-computer interface (BCI) systems. Since SSVEP can be easily recorded from the scalp over the occipital area and it has high signal-to-noise ratio, many SSVEP-based BCI systems have been implemented and achieved satisfactory performances [1,2]. SSVEP is periodic evoked potential induced by a quickly repetitive visual stimulus.…”

Section: Introductionmentioning

confidence: 99%

Adaptive canonical correlation analysis for harmonic stimulation frequencies recognition in SSVEP-based BCIs

Sadeghi¹,

Maleki²

2019

Turk J Elec Eng & Comp Sci

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Steady-state visual evoked potential (SSVEP) is the brain's response to quickly repetitive visual stimulus with a certain frequency. To increase the information transfer rate (ITR) in SSVEP-based systems, due to the frequency resolution restriction, we are forced to broaden the frequency range, which causes harmonic frequencies to come into the stimulation frequency range. Conventional canonical correlation analysis (CCA) may be associated with error for SSVEP frequency recognition at stimulation frequencies with harmonic relations. The number of harmonics considered to construct reference signals are determined adaptively; for frequencies whose second harmonic exists in the frequency range, two harmonics are used, and for other frequencies, just one harmonic is used. After constructing reference signals and recognizing the frequency corresponding to the maximum value of correlation by CCA, the target frequency is determined after a postprocessing step. Results show that for the 8-s time window length, the average classification accuracy for the adaptive CCA was 84%, while the corresponding values for the CCA with one harmonic (N = 1) and two harmonics (N = 2) were 78% and 74%, respectively. For 4-s length, this accuracy for the adaptive CCA was 86%, while it was 78% for both harmonic selection modes of the standard CCA, N = 1 and N = 2 . In SSVEP applications with harmonic stimulation frequencies, the adaptive CCA has significantly improved the frequency recognition accuracy in comparison with the popularly standard CCA method. The proposed method can be useful for SSVEP-based BCI systems that use broad ranges of stimulation frequencies with harmonic relation.

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Influence of stimuli color on steady-state visual evoked potentials based BCI wheelchair control

Cited by 25 publications

References 11 publications

Screen Task Experiments for Eeg Signals Based on Ssvep Brain Computer Interface.

Screen Task Experiments for Eeg Signals Based on Ssvep Brain Computer Interface.

Do the stimuli of an SSVEP-based BCI really have to be the same as the stimuli used for training it?

Adaptive canonical correlation analysis for harmonic stimulation frequencies recognition in SSVEP-based BCIs

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