Robust estimation of event-related potentials via particle filter
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- 作者：Tadanori Fukamia ; fukami@yz.yamagata-u.ac.jp" class="auth_mail" title="E-mail the corresponding author ; Jun Watanabea ; tcn68797@st.yamagata-u.ac.jp" class="auth_mail" title="E-mail the corresponding author ; Fumito Ishikawab ; fumitoi@hotmail.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Particle filter ; Event-related potential ; P300 ; Robust estimation
- 刊名：Computer Methods and Programs in Biomedicine
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：125
- 期：Complete
- 页码：26-36
- 全文大小：2062 K
文摘
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We constructed a model describing event-related potential (ERP) by trend model.
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A 400-particle filter produced the best mean square error in the ERP estimation.
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The filter reduced an amount of average by 42.8% compared with simple averaging.
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The filter could estimate P300 robustly by application to EEG in P300 speller.
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Real-time processing is realized in any computer with an appropriate particle number.