A Novel Hybrid BCI Web Browser Based on SSVEP and Eye-Tracking
In this study, we developed and tested assistive technology for neuro-rehabilitation consisting of a novel hybrid web browser following "true web access" principles. We combined Steady-State Visual Evoked Potentials (SSVEP) derived from electroencephalography (EEG) together with gaze-point...
Saved in:
| Published in | 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS) pp. 1 - 4 |
|---|---|
| Main Authors | , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.10.2019
|
| Subjects | |
| Online Access | Get full text |
| DOI | 10.1109/BIOCAS.2019.8919087 |
Cover
| Abstract | In this study, we developed and tested assistive technology for neuro-rehabilitation consisting of a novel hybrid web browser following "true web access" principles. We combined Steady-State Visual Evoked Potentials (SSVEP) derived from electroencephalography (EEG) together with gaze-point data from an eye-tracker to provide a natural method for people with severe motor impairment to access the internet without using a computer mouse. This system was tested by three healthy subjects. All subjects completed the online experiment successfully. The results showed an average overall accuracy of 88.5 ± 1.72%, whereas the copy-spelling accuracy of 100% was achieved by every subject. The average overall ITR value was 32.2 ± 1.14 bits/min. Thanks to the joining of eye-tracking technology, our system outperformed other BCI web browsers in command detection time and information transfer rate. And the user interface is much more friendly while the control panel and webpages are highly fused together. |
|---|---|
| AbstractList | In this study, we developed and tested assistive technology for neuro-rehabilitation consisting of a novel hybrid web browser following "true web access" principles. We combined Steady-State Visual Evoked Potentials (SSVEP) derived from electroencephalography (EEG) together with gaze-point data from an eye-tracker to provide a natural method for people with severe motor impairment to access the internet without using a computer mouse. This system was tested by three healthy subjects. All subjects completed the online experiment successfully. The results showed an average overall accuracy of 88.5 ± 1.72%, whereas the copy-spelling accuracy of 100% was achieved by every subject. The average overall ITR value was 32.2 ± 1.14 bits/min. Thanks to the joining of eye-tracking technology, our system outperformed other BCI web browsers in command detection time and information transfer rate. And the user interface is much more friendly while the control panel and webpages are highly fused together. |
| Author | Lin, Xinyuan Zhang, Shaomin Malik, Wasim Q. |
| Author_xml | – sequence: 1 givenname: Xinyuan surname: Lin fullname: Lin, Xinyuan organization: Zhejiang University,Key Laboratory for BME of MOE Qiushi Academy for Advanced Studies,Hangzhou,Zhejiang,China,310027 – sequence: 2 givenname: Wasim Q. surname: Malik fullname: Malik, Wasim Q. organization: Harvard Medical School,Dept. of Anesthesia, Critical Care & Pain Medicine, MGH,Boston,MA,02114 – sequence: 3 givenname: Shaomin surname: Zhang fullname: Zhang, Shaomin organization: Zhejiang University,Key Laboratory for BME of MOE Qiushi Academy for Advanced Studies,Hangzhou,Zhejiang,China,310027 |
| BookMark | eNotj91KwzAYQCPohZt7gt3kBVrz0ybNjdCW6grDDVr0cnxtvkhwppKK0rdXcFfn7hzOilyHKSAhW85Szpm5r9pDXXapYNykheGGFfqKrHjODGOKa3VLHkr6PH3jme6WIXpLq7qlrzjQKk4_M0ZawYyWToF23UtzpBAsbRZM-gjjuw9vd-TGwXnGzYVr0j82fb1L9oenti73iRdMfiWD-Ssa4PkossEp0IW2zOlR6cIgaJ2NUioQ3EqJWZFDbpzJlBACQeTWyTXZ_ms9Ip4-o_-AuJwuR_IXG4tChg |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/BIOCAS.2019.8919087 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Xplore POP ALL IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 1509006176 9781509006175 |
| EndPage | 4 |
| ExternalDocumentID | 8919087 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i203t-b90909a15c24bf6a787d0f7c6789ea774c336a21d33e485a59f946222ea25df3 |
| IEDL.DBID | RIE |
| IngestDate | Thu Jun 29 18:38:49 EDT 2023 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i203t-b90909a15c24bf6a787d0f7c6789ea774c336a21d33e485a59f946222ea25df3 |
| PageCount | 4 |
| ParticipantIDs | ieee_primary_8919087 |
| PublicationCentury | 2000 |
| PublicationDate | 2019-Oct. |
| PublicationDateYYYYMMDD | 2019-10-01 |
| PublicationDate_xml | – month: 10 year: 2019 text: 2019-Oct. |
| PublicationDecade | 2010 |
| PublicationTitle | 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS) |
| PublicationTitleAbbrev | BIOCAS |
| PublicationYear | 2019 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.7305982 |
| Snippet | In this study, we developed and tested assistive technology for neuro-rehabilitation consisting of a novel hybrid web browser following "true web access"... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1 |
| SubjectTerms | brain-computer interface Browsers Electrodes Electroencephalography eye-tracking Liquid crystal displays Navigation Object detection rehabilitation steady-state visual evoked potential Visualization web browser |
| Title | A Novel Hybrid BCI Web Browser Based on SSVEP and Eye-Tracking |
| URI | https://ieeexplore.ieee.org/document/8919087 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3NS8MwFA_bTp5UNvGbHDzarU2TtrkI29jYhM3Bpu42kuYFRGlFOmH-9b60c6J4kFxCCPl6L_m9JO-DkCsXvAGPfekxGQiPg2CeNsjLkcGDkIMWuvTOP5lGo3t-uxTLGrne2cIAQKl8Bm2XLf_yTZ6u3VNZJ5EIX0lcJ_U4iSpbra0jocCXnd74rt-dO20tJH9V80fIlBIxhvtk8tVXpSjy3F4Xup1-_HLD-N_BHJDWt20ene1Q55DUIGuSmy6d5u_wQkcbZ4FFe_0xfQRN3SUbeYz2EKsMzTM6nz8MZlRlhg424CFQpe6pvEUWw8GiP_K2kRG8J-aHhaelj0kFImVc20jhrjO-jVNEHgkKJbo0DCPFAhOGwBOhhLSSRygKgGLC2PCINLI8g2NCkyB1Eh1KPoojTlltsWVltG-Nb1gUn5Cmm_rqtfJ9sdrO-vTv4jOy55a_UnY7J43ibQ0XCNqFviyp9Qkv45Uy |
| linkProvider | IEEE |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LTwIxEJ4gHvSkBoxve_Dowj7a3e3FBAhkUUASULmRdttNiGbXmMUEf73TXcRoPJhemqbpI53ON53OA-DKJG9Ats8tlzvMopq5llRIy75CRki1ZLKIzj8c-dEDvZ2xWQWuN74wWuvC-Ew3TLX4y1dZvDSqsmbIEb7CYAu2GaWUld5a61BCjs2b7f59pzUx9lpIAGXfH0lTCszo7cHwa7bSVOS5scxlI_74FYjxv8vZh_q3dx4Zb3DnACo6rcFNi4yyd_1CopXxwSLtTp88aUnMMxupjLQRrRTJUjKZPHbHRKSKdFfaQqiKjbK8DtNed9qJrHVuBGvh2l5uSW5jEQ6LXSoTX-C9U3YSxIg9XAuU6WLP84XrKM_TNGSC8YRTH4UBLVymEu8QqmmW6iMgoRMbmQ5lH0ERqRKZ4MhCSTtRtnL94BhqZuvz1zL6xXy965O_my9hJ5oOB_NBf3R3CrvmKAynd4IzqOZvS32OEJ7Li-LkPgE1hZiG |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2019+IEEE+Biomedical+Circuits+and+Systems+Conference+%28BioCAS%29&rft.atitle=A+Novel+Hybrid+BCI+Web+Browser+Based+on+SSVEP+and+Eye-Tracking&rft.au=Lin%2C+Xinyuan&rft.au=Malik%2C+Wasim+Q.&rft.au=Zhang%2C+Shaomin&rft.date=2019-10-01&rft.pub=IEEE&rft.spage=1&rft.epage=4&rft_id=info:doi/10.1109%2FBIOCAS.2019.8919087&rft.externalDocID=8919087 |