The Effect of the Viewing Distance of Stimulus on SSVEP Response for Use in Brain-Computer Interfaces

Wu, Chi-Hsu; Lakany, Heba

doi:10.1109/smc.2013.317

Cited by 20 publications

(15 citation statements)

References 21 publications

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“…Compared with PC-200, the contrast of the stimulus is same, but the size of the stimulus in the field of view becomes smaller as the viewing distance increases, and this may result in a weakened SSVEP response. There are several studies support our explanation [37], [38], and it has been reported that the size of the stimulus is the most important parameter affecting the SSVEP classification accuracy [39].…”

Section: Discussion a Feasibility From Pc-ssvep To Ar-ssvepsupporting

confidence: 79%

SSVEP Stimulus Layout Effect on Accuracy of Brain-Computer Interfaces in Augmented Reality Glasses

Zhao

Liu

et al. 2020

IEEE Access

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Steady-state visual evoked potentials-based brain-computer interfaces (SSVEP-BCI) has the advantage of high information transfer rate (ITR) and little user training, and it has a high application value in the field of disability assistance and human-computer interaction. Generally SSVEP-BCI requires a personal computer screen (PC) to display several repetitive visual stimuli for inducing the SSVEP response, which reduces its portability and flexibility. Using augmented reality (AR) glasses worn on the head to display the repetitive visual stimuli could solve the above drawbacks, but whether it could achieve the same accuracy as PC screen in the case of reduced brightness and increased interference is unknown. In current study, we firstly designed 4 stimulus layouts and displayed them with Microsoft HoloLens (AR-SSVEP) glasses, comparison analysis showed that the classification accuracies are influenced by the stimulus layout when the stimulus duration is less than 3s. When the stimulus duration exceeds 3s, there is no significant accuracy difference between the 4 layouts. Then we designed a similar experimental paradigm on PC screen (PC-SSVEP) based on the best layout of AR. Classification results showed that AR-SSVEP achieved similar accuracy with PC-SSVEP when the stimulus duration is more than 3s, but when the stimulus duration is less than 2s, the accuracy of AR-SSVEP is lower than PC-SSVEP. Brain topological analysis indicated that the spatial distribution of SSVEP responses is similar, both of which are strongest in the occipital region. Current study indicated that stimulus layout is a key factor when building SSVEP-BCI with AR glasses, especially when the stimulation time is short. INDEX TERMS Steady-state visual evoked potentials (SSVEP), brain-computer interfaces (BCI), augmented reality (AR), optical see-through (OST), human-computer interaction. FIGURE 1. AR-SSVEP experiment environment, hardware devices include EEG acquisition and HoloLens.

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Section: Discussion a Feasibility From Pc-ssvep To Ar-ssvepsupporting

confidence: 79%

SSVEP Stimulus Layout Effect on Accuracy of Brain-Computer Interfaces in Augmented Reality Glasses

Zhao

Liu

et al. 2020

IEEE Access

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“…However, the differences of the mean accuracies at different viewing distances are not significant for all attended frequencies. In our previous study [17], the accuracies at 250cm and 350cm were very low without intensities compensation.…”

Section: Resultsmentioning

confidence: 70%

“…During the experiment, the visual stimulator board comprising 4 LEDs was present to the subject at four viewing distances 60cm, 150cm, 250cm and 350cm. In our previous study [17], it was found that the impact of the viewing distance can be compensated by changing the intensities of the visual stimuli. Therefore, the intensities of LEDs presented to the subjects were different at different viewing distance.…”

Section: Visual Stimuli and Experiments Protocolmentioning

confidence: 93%

Evaluation of the feasibility of a novel distance adaptable steady-state visual evoked potential based brain-computer interface

Lakany

2015

2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)

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Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has attracted great attention in BCI research due to its advantages over the other electroencephalography (EEG) based BCI paradigms, such as high speed, high signal to noise ratio, high accuracy, commands scalability and minimal user training time. Several studies have demonstrated that SSVEP BCI can provide a reliable channel to the users to communicate and control an external device. While most SSVEP based BCI studies focus on encoding the visual stimuli, enhancing the signal detection and improving the classification accuracy, there is a need to bridge the gap between BCI "bench" research and real world application. This study proposes a novel distance adaptable SSVEP based BCI paradigm which allows its users to operate the system in a range of viewing distances between the user and the visual stimulator. Unlike conventional SSVEP BCI where users can only operate the system at a fixed distance in front of the visual stimulator, users can operate the proposed BCI at a range of viewing distances. 10 healthy subjects participated in the experiment to evaluate the feasibility of the proposed SSVEP BCI. The visual stimulator was presented to the subjects at 4 viewing distances, 60cm, 150cm, 250cm and 350cm. The mean classification accuracy across the subjects and the viewing distances is over 75 The results demonstrate the feasibility of a distance adaptable SSVEP based BCI

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“…where t refers to time and n refers to the number of channels. Through the use of MVAR, EEG data set X can be expressed as the following autoregressive process ( Bartels and Zeki, 2004):…”

Section: Dtf and Flow Gainmentioning

confidence: 99%

Auditory Noise Leads to Increased Visual Brain-Computer Interface Performance: A Cross-Modal Study

Xie

Cao

et al. 2020

Front. Neurosci.

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Noise has been proven to have a beneficial role in non-linear systems, including the human brain, based on the stochastic resonance (SR) theory. Several studies have been implemented on single-modal SR. Cross-modal SR phenomenon has been confirmed in different human sensory systems. In our study, a cross-modal SR enhanced brain–computer interface (BCI) was proposed by applying auditory noise to visual stimuli. Fast Fourier transform and canonical correlation analysis methods were used to evaluate the influence of noise, results of which indicated that a moderate amount of auditory noise could enhance periodic components in visual responses. Directed transfer function was applied to investigate the functional connectivity patterns, and the flow gain value was used to measure the degree of activation of specific brain regions in the information transmission process. The results of flow gain maps showed that moderate intensity of auditory noise activated the brain area to a greater extent. Further analysis by weighted phase-lag index (wPLI) revealed that the phase synchronization between visual and auditory regions under auditory noise was significantly enhanced. Our study confirms the existence of cross-modal SR between visual and auditory regions and achieves a higher accuracy for recognition, along with shorter time window length. Such findings can be used to improve the performance of visual BCIs to a certain extent.

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The Effect of the Viewing Distance of Stimulus on SSVEP Response for Use in Brain-Computer Interfaces

Cited by 20 publications

References 21 publications

SSVEP Stimulus Layout Effect on Accuracy of Brain-Computer Interfaces in Augmented Reality Glasses

SSVEP Stimulus Layout Effect on Accuracy of Brain-Computer Interfaces in Augmented Reality Glasses

Evaluation of the feasibility of a novel distance adaptable steady-state visual evoked potential based brain-computer interface

Auditory Noise Leads to Increased Visual Brain-Computer Interface Performance: A Cross-Modal Study

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