Performance Improvement of Person Verification Using Evoked EEG by Imperceptible Vibratory Stimulation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 14164 LNCS, Page: 14-24
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
In this study, we focus on the electroencephalogram (EEG) as a biometric that can be detected continuously with high confidentiality, and aim to realize the person verification using the evoked EEG when presented with an imperceptible vibration stimulus. In previous studies, the content ratios of the power spectrum in theta (4–8 Hz), alpha (8–13 Hz), and beta (13–43 Hz) wavebands as individual features were derived from the evoked EEG data generated by imperceptible vibration stimulation, and the verification performance was evaluated by Support Vector Machine (SVM). The results showed that the Equal Error Rate (EER) was 28.2%; however, this was not a sufficient verification result. In this paper, for the purpose of improving the verification performance, the weighted (normalized) content ratios are adopted as new features and the verification performance is evaluated. Accordingly, the EER is improved to 17.0%. The verification performance is further improved by changing the feature bandwidth to 6–10 Hz, which contains many spectral components in evoked EEG, and the EER is reduced to 16.4%.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85174443176&origin=inward; http://dx.doi.org/10.1007/978-3-031-42823-4_2; https://link.springer.com/10.1007/978-3-031-42823-4_2; https://dx.doi.org/10.1007/978-3-031-42823-4_2; https://link.springer.com/chapter/10.1007/978-3-031-42823-4_2
Springer Science and Business Media LLC
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