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A user-friendly SSVEP-based BCI using imperceptible phase-coded flickers at 60Hz

A brain-computer interface (BCI) system based on steady-state visual evoked potentials (SSVEP) was developed by four-class phase-coded stimuli. SSVEPs elicited by flickers at 60Hz, which is higher than the critical fusion frequency (CFF), were compared with those at 15Hz and 30Hz. SSVEP components i...

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Published in:China communications 2022-02, Vol.19 (2), p.1-14
Main Authors: Jiang, Lu, Pei, Weihua, Wang, Yijun
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description A brain-computer interface (BCI) system based on steady-state visual evoked potentials (SSVEP) was developed by four-class phase-coded stimuli. SSVEPs elicited by flickers at 60Hz, which is higher than the critical fusion frequency (CFF), were compared with those at 15Hz and 30Hz. SSVEP components in electroencephalogram (EEG) were detected using task related component analysis (TRCA) method. Offline analysis with 17 subjects indicated that the highest information transfer rate (ITR) was 29.80±4.65bpm with 0.5s data length for 60Hz and the classification accuracy was 70.07±4.15%. The online BCI system reached an averaged classification accuracy of 87.75±3.50% at 60Hz with 4s, resulting in an ITR of 16.73±1.63bpm. In particular, the maximum ITR for a subject was 80bpm with 0.5s at 60Hz. Although the BCI performance of 60Hz was lower than that of 15Hz and 30Hz, the results of the behavioral test indicated that, with no perception of flicker, the BCI system with 60Hz was more comfortable to use than 15Hz and 30Hz. Correlation analysis revealed that SSVEP with higher signal-to-noise ratio (SNR) corresponded to better classification performance and the improvement in comfortableness was accompanied by a decrease in performance. This study demonstrates the feasibility and potential of a user-friendly SSVEP-based BCI using imperceptible flickers.
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SSVEPs elicited by flickers at 60Hz, which is higher than the critical fusion frequency (CFF), were compared with those at 15Hz and 30Hz. SSVEP components in electroencephalogram (EEG) were detected using task related component analysis (TRCA) method. Offline analysis with 17 subjects indicated that the highest information transfer rate (ITR) was 29.80±4.65bpm with 0.5s data length for 60Hz and the classification accuracy was 70.07±4.15%. The online BCI system reached an averaged classification accuracy of 87.75±3.50% at 60Hz with 4s, resulting in an ITR of 16.73±1.63bpm. In particular, the maximum ITR for a subject was 80bpm with 0.5s at 60Hz. Although the BCI performance of 60Hz was lower than that of 15Hz and 30Hz, the results of the behavioral test indicated that, with no perception of flicker, the BCI system with 60Hz was more comfortable to use than 15Hz and 30Hz. Correlation analysis revealed that SSVEP with higher signal-to-noise ratio (SNR) corresponded to better classification performance and the improvement in comfortableness was accompanied by a decrease in performance. This study demonstrates the feasibility and potential of a user-friendly SSVEP-based BCI using imperceptible flickers.</description><subject>brain-computer interface</subject><subject>Electric potential</subject><subject>Electrodes</subject><subject>electroencephalogram</subject><subject>Electroencephalography</subject><subject>imperceptible flickers</subject><subject>Liquid crystal displays</subject><subject>Monitoring</subject><subject>phase coding</subject><subject>steady-state visual evoked potentials</subject><subject>Task analysis</subject><subject>task related component analysis</subject><subject>Visualization</subject><issn>1673-5447</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNo9UMFOwzAMzQEkprE7EpdeOHY4SZu0x1ENNjSJSQOuUdI4o6PrqrQTbF9PxhDWkyz5vWfLj5AbCmPGc5rfPxfFmAFjYwgAekEGVEgep0kir8io6zYQKhOCCzYgy0m079DHzlfY2PoQrVbv02VsdIc2eijmga2adVRtW_Qltn1laozaj0DH5c4Gjaur8hN9F-k-EjA7XpNLp-sOR399SN4ep6_FLF68PM2LySIueQJ9jDyVmQQmgFM0Za5dlqRSM6NLKwylKLTNjXTUUmZcmFgjwaTWScA0o5YPyd1575dunG7WarPb-yZcVMd1_336HxgACzo460q_6zqPTrW-2mp_UBTUb2AqBKZOBgUBQIPl9mypEPFfnkvGpMj4D_NWZ4M</recordid><startdate>20220201</startdate><enddate>20220201</enddate><creator>Jiang, Lu</creator><creator>Pei, Weihua</creator><creator>Wang, Yijun</creator><general>China Institute of Communications</general><general>University of Chinese Academy of Sciences,Beijing 100049,China%State Key Laboratory on Integrated Optoelectronics,Institute of Semiconductors,Chinese Academy of Sciences,Beijing 100083,China</general><general>State Key Laboratory on Integrated Optoelectronics,Institute of Semiconductors,Chinese Academy of Sciences,Beijing 100083,China</general><general>University of Chinese Academy of Sciences,Beijing 100049,China</general><general>Chinese Institute for Brain Research,Beijing 102206,China</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20220201</creationdate><title>A user-friendly SSVEP-based BCI using imperceptible phase-coded flickers at 60Hz</title><author>Jiang, Lu ; Pei, Weihua ; Wang, Yijun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c340t-e35787026031ebc9af8457a2bacd6b11e6ad9b7f1d12bf6b1db70b5df70e581d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>brain-computer interface</topic><topic>Electric potential</topic><topic>Electrodes</topic><topic>electroencephalogram</topic><topic>Electroencephalography</topic><topic>imperceptible flickers</topic><topic>Liquid crystal displays</topic><topic>Monitoring</topic><topic>phase coding</topic><topic>steady-state visual evoked potentials</topic><topic>Task analysis</topic><topic>task related component analysis</topic><topic>Visualization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jiang, Lu</creatorcontrib><creatorcontrib>Pei, Weihua</creatorcontrib><creatorcontrib>Wang, Yijun</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) Online</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>China communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jiang, Lu</au><au>Pei, Weihua</au><au>Wang, Yijun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A user-friendly SSVEP-based BCI using imperceptible phase-coded flickers at 60Hz</atitle><jtitle>China communications</jtitle><stitle>ChinaComm</stitle><date>2022-02-01</date><risdate>2022</risdate><volume>19</volume><issue>2</issue><spage>1</spage><epage>14</epage><pages>1-14</pages><issn>1673-5447</issn><coden>CCHOBE</coden><abstract>A brain-computer interface (BCI) system based on steady-state visual evoked potentials (SSVEP) was developed by four-class phase-coded stimuli. SSVEPs elicited by flickers at 60Hz, which is higher than the critical fusion frequency (CFF), were compared with those at 15Hz and 30Hz. SSVEP components in electroencephalogram (EEG) were detected using task related component analysis (TRCA) method. Offline analysis with 17 subjects indicated that the highest information transfer rate (ITR) was 29.80±4.65bpm with 0.5s data length for 60Hz and the classification accuracy was 70.07±4.15%. The online BCI system reached an averaged classification accuracy of 87.75±3.50% at 60Hz with 4s, resulting in an ITR of 16.73±1.63bpm. In particular, the maximum ITR for a subject was 80bpm with 0.5s at 60Hz. Although the BCI performance of 60Hz was lower than that of 15Hz and 30Hz, the results of the behavioral test indicated that, with no perception of flicker, the BCI system with 60Hz was more comfortable to use than 15Hz and 30Hz. Correlation analysis revealed that SSVEP with higher signal-to-noise ratio (SNR) corresponded to better classification performance and the improvement in comfortableness was accompanied by a decrease in performance. This study demonstrates the feasibility and potential of a user-friendly SSVEP-based BCI using imperceptible flickers.</abstract><pub>China Institute of Communications</pub><doi>10.23919/JCC.2022.02.001</doi><tpages>14</tpages></addata></record>
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source IEEE Electronic Library (IEL) Journals
subjects brain-computer interface
Electric potential
Electrodes
electroencephalogram
Electroencephalography
imperceptible flickers
Liquid crystal displays
Monitoring
phase coding
steady-state visual evoked potentials
Task analysis
task related component analysis
Visualization
title A user-friendly SSVEP-based BCI using imperceptible phase-coded flickers at 60Hz
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