<p>Steady-state visual evoked potential (SSVEP) brain-computer interface (BCI) are known for high speed, accuracy, and multivalue input. Integrating ear-electroencephalogram (EEG) can make SSVEP-BCI more accessible for everyday use. This study introduces a reliability score to enhance the performance of ear-EEG SSVEP-BCI by dynamically adjusting measurement duration and enabling asynchronous detection. Two analysis methods, learning canonical correlation analysis (LCCA) and task-related component analysis, were evaluated. Using the reliability score, the accuracy for ear-EEG SSVEP-BCI reached <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10015_2025_1025_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="25" /> </InlineMediaObject> <EquationSource Format="TEX">$100$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>100</mn> </mrow> </math></EquationSource> </InlineEquation>% with an information transfer rate (ITR) of <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10015_2025_1025_Article_IEq2.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="87" /> </InlineMediaObject> <EquationSource Format="TEX">$22.36\pm 3.54$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>22.36</mn> <mo>±</mo> <mn>3.54</mn> </mrow> </math></EquationSource> </InlineEquation> bits/min, compared to <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10015_2025_1025_Article_IEq3.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="87" /> </InlineMediaObject> <EquationSource Format="TEX">$61.93\pm 9.22$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>61.93</mn> <mo>±</mo> <mn>9.22</mn> </mrow> </math></EquationSource> </InlineEquation>% accuracy and <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10015_2025_1025_Article_IEq4.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="87" /> </InlineMediaObject> <EquationSource Format="TEX">$15.32\pm 4.59$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>15.32</mn> <mo>±</mo> <mn>4.59</mn> </mrow> </math></EquationSource> </InlineEquation> bits/min ITR without the reliability score. These findings demonstrate that the reliability score significantly improves ear-EEG SSVEP-BCI performance, suggesting its potential to enhance usability in practical applications. </p>

Performance improvement of Ear-EEG SSVEP-BCI using reliability score

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2025年4月30日

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Sodai Kondo,
Hideyuki Harafuji,
Ren Kiuchi,
Asahi Saito,
Kakeru Tanaka,
Wataru Wakayama,
Hisaya Tanaka

摘要

Steady-state visual evoked potential (SSVEP) brain-computer interface (BCI) are known for high speed, accuracy, and multivalue input. Integrating ear-electroencephalogram (EEG) can make SSVEP-BCI more accessible for everyday use. This study introduces a reliability score to enhance the performance of ear-EEG SSVEP-BCI by dynamically adjusting measurement duration and enabling asynchronous detection. Two analysis methods, learning canonical correlation analysis (LCCA) and task-related component analysis, were evaluated. Using the reliability score, the accuracy for ear-EEG SSVEP-BCI reached $100$ $100$ % with an information transfer rate (ITR) of $22.36\pm 3.54$ $22.36 \pm 3.54$ bits/min, compared to $61.93\pm 9.22$ $61.93 \pm 9.22$ % accuracy and $15.32\pm 4.59$ $15.32 \pm 4.59$ bits/min ITR without the reliability score. These findings demonstrate that the reliability score significantly improves ear-EEG SSVEP-BCI performance, suggesting its potential to enhance usability in practical applications.