Optimizing a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear
Objective. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has the characteristics of fast communication speed, high stability, and wide applicability, thus it has been widely studied. With the rapid development in paradigm, algorithm, and system design, SSVEP-BCI i...
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description | Objective. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has the characteristics of fast communication speed, high stability, and wide applicability, thus it has been widely studied. With the rapid development in paradigm, algorithm, and system design, SSVEP-BCI is gradually applied in clinical and real-life scenarios. In order to improve the ease of use of the SSVEP-BCI system, many studies have been focusing on developing it on the hairless area, but due to the lack of redesigning the stimulation paradigm to better adapt to the new area, the electroencephalography response in the hairless area is worse than occipital region. Approach. This study first proposed a phase difference estimation method based on stimulating the left and right visual field separately, then developed and optimized a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear. Main results. In the 12-target online experiment, after a short model estimation training, all 16 subjects used their best stimulus condition. The paradigm designed in this study can increase the proportion of applicable subjects for the behind-ear SSVEP-BCI system from 58.3% to 75% and increase the accuracy from 74.6 +/- 20.0% (the existing best SSVEP stimulus with hairless region behind the ear) to 84.2 +/- 14.7%, and the information transfer rate from 14.2 +/- 6.4 bits min(-1) to 17.8 +/- 5.7 bits min(-1). Significance. These results demonstrated that the proposed paradigm can effectively improve the BCI performance using the signal from the hairless region behind the ear, compared with the standard SSVEP stimulation paradigm. |
doi_str_mv | 10.1088/1741-2552/ac40a1 |
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Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has the characteristics of fast communication speed, high stability, and wide applicability, thus it has been widely studied. With the rapid development in paradigm, algorithm, and system design, SSVEP-BCI is gradually applied in clinical and real-life scenarios. In order to improve the ease of use of the SSVEP-BCI system, many studies have been focusing on developing it on the hairless area, but due to the lack of redesigning the stimulation paradigm to better adapt to the new area, the electroencephalography response in the hairless area is worse than occipital region. Approach. This study first proposed a phase difference estimation method based on stimulating the left and right visual field separately, then developed and optimized a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear. Main results. In the 12-target online experiment, after a short model estimation training, all 16 subjects used their best stimulus condition. The paradigm designed in this study can increase the proportion of applicable subjects for the behind-ear SSVEP-BCI system from 58.3% to 75% and increase the accuracy from 74.6 +/- 20.0% (the existing best SSVEP stimulus with hairless region behind the ear) to 84.2 +/- 14.7%, and the information transfer rate from 14.2 +/- 6.4 bits min(-1) to 17.8 +/- 5.7 bits min(-1). Significance. These results demonstrated that the proposed paradigm can effectively improve the BCI performance using the signal from the hairless region behind the ear, compared with the standard SSVEP stimulation paradigm.</description><identifier>ISSN: 1741-2560</identifier><identifier>EISSN: 1741-2552</identifier><identifier>DOI: 10.1088/1741-2552/ac40a1</identifier><identifier>PMID: 34875637</identifier><identifier>CODEN: JNEIEZ</identifier><language>eng</language><publisher>BRISTOL: IOP Publishing</publisher><subject>Algorithms ; Brain-Computer Interfaces ; brain–computer interface ; Electroencephalography ; Engineering ; Engineering, Biomedical ; Evoked Potentials, Visual ; hairless region ; Humans ; Life Sciences & Biomedicine ; Neurosciences ; Neurosciences & Neurology ; optimization method ; Photic Stimulation ; Science & Technology ; steady-state visual evoked potentials ; Technology ; Visual Fields</subject><ispartof>Journal of neural engineering, 2021-12, Vol.18 (6), p.66040, Article 066040</ispartof><rights>2021 IOP Publishing Ltd</rights><rights>2021 IOP Publishing Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>5</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000735174900001</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c336t-e278d812f419485e22826c1d8e5e4f8b015057e0fe0d94787f1dc3ed17b621ae3</citedby><cites>FETCH-LOGICAL-c336t-e278d812f419485e22826c1d8e5e4f8b015057e0fe0d94787f1dc3ed17b621ae3</cites><orcidid>0000-0002-8161-2150 ; 0000-0003-0909-7200 ; 0000-0002-5334-1728</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1741-2552/ac40a1/pdf$$EPDF$$P50$$Giop$$H</linktopdf><link.rule.ids>315,781,785,27929,27930,39262,39263,53851,53898</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34875637$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liang, Liyan</creatorcontrib><creatorcontrib>Bin, Guangyu</creatorcontrib><creatorcontrib>Chen, Xiaogang</creatorcontrib><creatorcontrib>Wang, Yijun</creatorcontrib><creatorcontrib>Gao, Shangkai</creatorcontrib><creatorcontrib>Gao, Xiaorong</creatorcontrib><title>Optimizing a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear</title><title>Journal of neural engineering</title><addtitle>JNE</addtitle><addtitle>J NEURAL ENG</addtitle><addtitle>J. Neural Eng</addtitle><description>Objective. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has the characteristics of fast communication speed, high stability, and wide applicability, thus it has been widely studied. With the rapid development in paradigm, algorithm, and system design, SSVEP-BCI is gradually applied in clinical and real-life scenarios. In order to improve the ease of use of the SSVEP-BCI system, many studies have been focusing on developing it on the hairless area, but due to the lack of redesigning the stimulation paradigm to better adapt to the new area, the electroencephalography response in the hairless area is worse than occipital region. Approach. This study first proposed a phase difference estimation method based on stimulating the left and right visual field separately, then developed and optimized a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear. Main results. In the 12-target online experiment, after a short model estimation training, all 16 subjects used their best stimulus condition. The paradigm designed in this study can increase the proportion of applicable subjects for the behind-ear SSVEP-BCI system from 58.3% to 75% and increase the accuracy from 74.6 +/- 20.0% (the existing best SSVEP stimulus with hairless region behind the ear) to 84.2 +/- 14.7%, and the information transfer rate from 14.2 +/- 6.4 bits min(-1) to 17.8 +/- 5.7 bits min(-1). Significance. These results demonstrated that the proposed paradigm can effectively improve the BCI performance using the signal from the hairless region behind the ear, compared with the standard SSVEP stimulation paradigm.</description><subject>Algorithms</subject><subject>Brain-Computer Interfaces</subject><subject>brain–computer interface</subject><subject>Electroencephalography</subject><subject>Engineering</subject><subject>Engineering, Biomedical</subject><subject>Evoked Potentials, Visual</subject><subject>hairless region</subject><subject>Humans</subject><subject>Life Sciences & Biomedicine</subject><subject>Neurosciences</subject><subject>Neurosciences & Neurology</subject><subject>optimization method</subject><subject>Photic Stimulation</subject><subject>Science & Technology</subject><subject>steady-state visual evoked potentials</subject><subject>Technology</subject><subject>Visual Fields</subject><issn>1741-2560</issn><issn>1741-2552</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GIZIO</sourceid><sourceid>HGBXW</sourceid><sourceid>EIF</sourceid><recordid>eNqNkM9r1jAYgIsobk7vniRHYda9SX8kPWqZbjCYMPVa0uTN14y2qUnqmBf_dfPZ7bsJnvISnudNeLLsNYX3FIQ4o7ykOasqdiZVCZI-yY4PV08Pcw1H2YsQbgEKyht4nh0VpeBVXfDj7Pf1Eu1kf9l5RyQZ0UQiZ0283Q2R_LRhlSMxFkdNersMMlhFQhLWUUbrZrJIL7XdTcQ4T25uvp9_yXsZUJOP7WUgdzYOZJDWjxgC8bjbKz0ONr0QByQo_cvsmZFjwFcP50n27dP51_Yiv7r-fNl-uMpVUdQxR8aFFpSZkjalqJAxwWpFtcAKSyN6oBVUHMEg6KbkghuqVYGa8r5mVGJxkr3d9i7e_VgxxG6yQeE4yhndGjpWg4CmLssmobChyrsQPJpu8XaS_r6j0O2zd_uu3b5xt2VPypuH7Ws_oT4Ij50TIDbgDntngrI4KzxgAMCLKm1t0gS0tfFv3datc0zq6f-riX630dYt3a1b_Zyq_vvjfwCdAKyp</recordid><startdate>20211228</startdate><enddate>20211228</enddate><creator>Liang, Liyan</creator><creator>Bin, Guangyu</creator><creator>Chen, Xiaogang</creator><creator>Wang, Yijun</creator><creator>Gao, Shangkai</creator><creator>Gao, Xiaorong</creator><general>IOP Publishing</general><general>IOP Publishing Ltd</general><scope>17B</scope><scope>BLEPL</scope><scope>DTL</scope><scope>DVR</scope><scope>EGQ</scope><scope>GIZIO</scope><scope>HGBXW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-8161-2150</orcidid><orcidid>https://orcid.org/0000-0003-0909-7200</orcidid><orcidid>https://orcid.org/0000-0002-5334-1728</orcidid></search><sort><creationdate>20211228</creationdate><title>Optimizing a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear</title><author>Liang, Liyan ; Bin, Guangyu ; Chen, Xiaogang ; Wang, Yijun ; Gao, Shangkai ; Gao, Xiaorong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c336t-e278d812f419485e22826c1d8e5e4f8b015057e0fe0d94787f1dc3ed17b621ae3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Brain-Computer Interfaces</topic><topic>brain–computer interface</topic><topic>Electroencephalography</topic><topic>Engineering</topic><topic>Engineering, Biomedical</topic><topic>Evoked Potentials, Visual</topic><topic>hairless region</topic><topic>Humans</topic><topic>Life Sciences & Biomedicine</topic><topic>Neurosciences</topic><topic>Neurosciences & Neurology</topic><topic>optimization method</topic><topic>Photic Stimulation</topic><topic>Science & Technology</topic><topic>steady-state visual evoked potentials</topic><topic>Technology</topic><topic>Visual Fields</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liang, Liyan</creatorcontrib><creatorcontrib>Bin, Guangyu</creatorcontrib><creatorcontrib>Chen, Xiaogang</creatorcontrib><creatorcontrib>Wang, Yijun</creatorcontrib><creatorcontrib>Gao, Shangkai</creatorcontrib><creatorcontrib>Gao, Xiaorong</creatorcontrib><collection>Web of Knowledge</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>Social Sciences Citation Index</collection><collection>Web of Science Primary (SCIE, SSCI & AHCI)</collection><collection>Web of Science - Social Sciences Citation Index – 2021</collection><collection>Web of Science - Science Citation Index Expanded - 2021</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of neural engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liang, Liyan</au><au>Bin, Guangyu</au><au>Chen, Xiaogang</au><au>Wang, Yijun</au><au>Gao, Shangkai</au><au>Gao, Xiaorong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimizing a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear</atitle><jtitle>Journal of neural engineering</jtitle><stitle>JNE</stitle><stitle>J NEURAL ENG</stitle><addtitle>J. Neural Eng</addtitle><date>2021-12-28</date><risdate>2021</risdate><volume>18</volume><issue>6</issue><spage>66040</spage><pages>66040-</pages><artnum>066040</artnum><issn>1741-2560</issn><eissn>1741-2552</eissn><coden>JNEIEZ</coden><abstract>Objective. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has the characteristics of fast communication speed, high stability, and wide applicability, thus it has been widely studied. With the rapid development in paradigm, algorithm, and system design, SSVEP-BCI is gradually applied in clinical and real-life scenarios. In order to improve the ease of use of the SSVEP-BCI system, many studies have been focusing on developing it on the hairless area, but due to the lack of redesigning the stimulation paradigm to better adapt to the new area, the electroencephalography response in the hairless area is worse than occipital region. Approach. This study first proposed a phase difference estimation method based on stimulating the left and right visual field separately, then developed and optimized a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear. Main results. In the 12-target online experiment, after a short model estimation training, all 16 subjects used their best stimulus condition. The paradigm designed in this study can increase the proportion of applicable subjects for the behind-ear SSVEP-BCI system from 58.3% to 75% and increase the accuracy from 74.6 +/- 20.0% (the existing best SSVEP stimulus with hairless region behind the ear) to 84.2 +/- 14.7%, and the information transfer rate from 14.2 +/- 6.4 bits min(-1) to 17.8 +/- 5.7 bits min(-1). Significance. These results demonstrated that the proposed paradigm can effectively improve the BCI performance using the signal from the hairless region behind the ear, compared with the standard SSVEP stimulation paradigm.</abstract><cop>BRISTOL</cop><pub>IOP Publishing</pub><pmid>34875637</pmid><doi>10.1088/1741-2552/ac40a1</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-8161-2150</orcidid><orcidid>https://orcid.org/0000-0003-0909-7200</orcidid><orcidid>https://orcid.org/0000-0002-5334-1728</orcidid></addata></record> |
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subjects | Algorithms Brain-Computer Interfaces brain–computer interface Electroencephalography Engineering Engineering, Biomedical Evoked Potentials, Visual hairless region Humans Life Sciences & Biomedicine Neurosciences Neurosciences & Neurology optimization method Photic Stimulation Science & Technology steady-state visual evoked potentials Technology Visual Fields |
title | Optimizing a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear |
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