A Brain-Computer Interface Based on Miniature-Event-Related Potentials Induced by Very Small Lateral Visual Stimuli
Goal: Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct electroencephalography (EEG) features. However, the visual stimuli are of no interest to the users as they just serve as the hidden codes behind the...
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Published in | IEEE transactions on biomedical engineering Vol. 65; no. 5; pp. 1166 - 1175 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.05.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Abstract | Goal: Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct electroencephalography (EEG) features. However, the visual stimuli are of no interest to the users as they just serve as the hidden codes behind the characters. Furthermore, using stronger visual stimuli could cause visual fatigue and other adverse symptoms to users. Therefore, it's imperative for visual BCIs to use small and inconspicuous visual stimuli to code characters. Methods: This study developed a new BCI speller based on miniature asymmetric visual evoked potentials (aVEPs), which encodes 32 characters with a space-code division multiple access scheme and decodes EEG features with a discriminative canonical pattern matching algorithm. Notably, the visual stimulus used in this study only subtended 0.5° of visual angle and was placed outside the fovea vision on the lateral side, which could only induce a miniature potential about 0.5 μ V in amplitude and about 16.5 dB in signal-to-noise rate. A total of 12 subjects were recruited to use the miniature aVEP speller in both offline and online tests. Results: Information transfer rates up to 63.33 b/min could be achieved from online tests (online demo URL: https://www.youtube.com/edit?o=U&video_id=kC7btB3mvGY ). Conclusion: Experimental results demonstrate the feasibility of using very small and inconspicuous visual stimuli to implement an efficient BCI system, even though the elicited EEG features are very weak. Significance: The proposed innovative technique can broaden the category of BCIs and strengthen the brain-computer communication. |
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AbstractList | Goal: Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct electroencephalography (EEG) features. However, the visual stimuli are of no interest to the users as they just serve as the hidden codes behind the characters. Furthermore, using stronger visual stimuli could cause visual fatigue and other adverse symptoms to users. Therefore, it's imperative for visual BCIs to use small and inconspicuous visual stimuli to code characters. Methods: This study developed a new BCI speller based on miniature asymmetric visual evoked potentials (aVEPs), which encodes 32 characters with a space-code division multiple access scheme and decodes EEG features with a discriminative canonical pattern matching algorithm. Notably, the visual stimulus used in this study only subtended 0.5° of visual angle and was placed outside the fovea vision on the lateral side, which could only induce a miniature potential about 0.5 μV in amplitude and about 16.5 dB in signal-to-noise rate. A total of 12 subjects were recruited to use the miniature aVEP speller in both offline and online tests. Results: Information transfer rates up to 63.33 b/min could be achieved from online tests (online demo URL: https://www.youtube.com/edit?o=U&video_id=kC7btB3mvGY). Conclusion: Experimental results demonstrate the feasibility of using very small and inconspicuous visual stimuli to implement an efficient BCI system, even though the elicited EEG features are very weak. Significance: The proposed innovative technique can broaden the category of BCIs and strengthen the brain-computer communication. Goal: Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct electroencephalography (EEG) features. However, the visual stimuli are of no interest to the users as they just serve as the hidden codes behind the characters. Furthermore, using stronger visual stimuli could cause visual fatigue and other adverse symptoms to users. Therefore, it's imperative for visual BCIs to use small and inconspicuous visual stimuli to code characters. Methods: This study developed a new BCI speller based on miniature asymmetric visual evoked potentials (aVEPs), which encodes 32 characters with a space-code division multiple access scheme and decodes EEG features with a discriminative canonical pattern matching algorithm. Notably, the visual stimulus used in this study only subtended 0.5° of visual angle and was placed outside the fovea vision on the lateral side, which could only induce a miniature potential about 0.5 μ V in amplitude and about 16.5 dB in signal-to-noise rate. A total of 12 subjects were recruited to use the miniature aVEP speller in both offline and online tests. Results: Information transfer rates up to 63.33 b/min could be achieved from online tests (online demo URL: https://www.youtube.com/edit?o=U&video_id=kC7btB3mvGY ). Conclusion: Experimental results demonstrate the feasibility of using very small and inconspicuous visual stimuli to implement an efficient BCI system, even though the elicited EEG features are very weak. Significance: The proposed innovative technique can broaden the category of BCIs and strengthen the brain-computer communication. Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct electroencephalography (EEG) features. However, the visual stimuli are of no interest to the users as they just serve as the hidden codes behind the characters. Furthermore, using stronger visual stimuli could cause visual fatigue and other adverse symptoms to users. Therefore, it's imperative for visual BCIs to use small and inconspicuous visual stimuli to code characters. This study developed a new BCI speller based on miniature asymmetric visual evoked potentials (aVEPs), which encodes 32 characters with a space-code division multiple access scheme and decodes EEG features with a discriminative canonical pattern matching algorithm. Notably, the visual stimulus used in this study only subtended 0.5° of visual angle and was placed outside the fovea vision on the lateral side, which could only induce a miniature potential about 0.5 μV in amplitude and about 16.5 dB in signal-to-noise rate. A total of 12 subjects were recruited to use the miniature aVEP speller in both offline and online tests. Information transfer rates up to 63.33 b/min could be achieved from online tests (online demo URL: https://www.youtube.com/edit?o=U&video_id=kC7btB3mvGY ). Experimental results demonstrate the feasibility of using very small and inconspicuous visual stimuli to implement an efficient BCI system, even though the elicited EEG features are very weak. The proposed innovative technique can broaden the category of BCIs and strengthen the brain-computer communication. Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct electroencephalography (EEG) features. However, the visual stimuli are of no interest to the users as they just serve as the hidden codes behind the characters. Furthermore, using stronger visual stimuli could cause visual fatigue and other adverse symptoms to users. Therefore, it's imperative for visual BCIs to use small and inconspicuous visual stimuli to code characters.GOALTraditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct electroencephalography (EEG) features. However, the visual stimuli are of no interest to the users as they just serve as the hidden codes behind the characters. Furthermore, using stronger visual stimuli could cause visual fatigue and other adverse symptoms to users. Therefore, it's imperative for visual BCIs to use small and inconspicuous visual stimuli to code characters.This study developed a new BCI speller based on miniature asymmetric visual evoked potentials (aVEPs), which encodes 32 characters with a space-code division multiple access scheme and decodes EEG features with a discriminative canonical pattern matching algorithm. Notably, the visual stimulus used in this study only subtended 0.5° of visual angle and was placed outside the fovea vision on the lateral side, which could only induce a miniature potential about 0.5 μV in amplitude and about 16.5 dB in signal-to-noise rate. A total of 12 subjects were recruited to use the miniature aVEP speller in both offline and online tests.METHODSThis study developed a new BCI speller based on miniature asymmetric visual evoked potentials (aVEPs), which encodes 32 characters with a space-code division multiple access scheme and decodes EEG features with a discriminative canonical pattern matching algorithm. Notably, the visual stimulus used in this study only subtended 0.5° of visual angle and was placed outside the fovea vision on the lateral side, which could only induce a miniature potential about 0.5 μV in amplitude and about 16.5 dB in signal-to-noise rate. A total of 12 subjects were recruited to use the miniature aVEP speller in both offline and online tests.Information transfer rates up to 63.33 b/min could be achieved from online tests (online demo URL: https://www.youtube.com/edit?o=U&video_id=kC7btB3mvGY ).RESULTSInformation transfer rates up to 63.33 b/min could be achieved from online tests (online demo URL: https://www.youtube.com/edit?o=U&video_id=kC7btB3mvGY ).Experimental results demonstrate the feasibility of using very small and inconspicuous visual stimuli to implement an efficient BCI system, even though the elicited EEG features are very weak.CONCLUSIONExperimental results demonstrate the feasibility of using very small and inconspicuous visual stimuli to implement an efficient BCI system, even though the elicited EEG features are very weak.The proposed innovative technique can broaden the category of BCIs and strengthen the brain-computer communication.SIGNIFICANCEThe proposed innovative technique can broaden the category of BCIs and strengthen the brain-computer communication. |
Author | Xu, Minpeng Ming, Dong Qi, Hongzhi Xiao, Xiaolin Jung, Tzyy-Ping Wang, Yijun |
Author_xml | – sequence: 1 givenname: Minpeng surname: Xu fullname: Xu, Minpeng email: minpeng.xu@tju.edu.cn organization: Department of Biomedical Engineering, Laboratory of Neural Engineering and Rehabilitation, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China – sequence: 2 givenname: Xiaolin surname: Xiao fullname: Xiao, Xiaolin organization: Department of Biomedical Engineering, Lab of Neural Engineering and Rehabilitation, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China – sequence: 3 givenname: Yijun surname: Wang fullname: Wang, Yijun organization: State Key Laboratory on Integrated OptoelectronicsInstitute of SemiconductorsChinese Academy of Sciences – sequence: 4 givenname: Hongzhi surname: Qi fullname: Qi, Hongzhi organization: Department of Biomedical Engineering, Lab of Neural Engineering and Rehabilitation, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China – sequence: 5 givenname: Tzyy-Ping surname: Jung fullname: Jung, Tzyy-Ping organization: Swartz Center for Computational NeuroscienceUniversity of California – sequence: 6 givenname: Dong surname: Ming fullname: Ming, Dong email: richardming@tju.edu.cn organization: Department of Biomedical Engineering, Laboratory of Neural Engineering and Rehabilitation, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29683431$$D View this record in MEDLINE/PubMed |
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Snippet | Goal: Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct... Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct... |
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SubjectTerms | Adult Algorithms asymmetric visual evoked potential (aVEP) Attention Brain-computer interface (BCI) Brain-Computer Interfaces Code Division Multiple Access discriminative canonical pattern matching (DCPM) EEG Electroencephalography Electroencephalography - methods Event-related potentials Evoked Potentials, Visual - physiology Eye Fatigue Female Fovea Human-computer interface Humans Information transfer Interfaces Internet Male Multiaccess communication Neural engineering Noise levels Pattern matching Photic Stimulation Retina Signal Processing, Computer-Assisted Signs and symptoms Sociology space-code division multiple access (SCDMA) Visual discrimination Visual evoked potentials Visual stimuli Visualization Young Adult |
Title | A Brain-Computer Interface Based on Miniature-Event-Related Potentials Induced by Very Small Lateral Visual Stimuli |
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