Paper Abstract and Keywords |
Presentation |
2008-01-15 16:10
Feature Analysis of Auditory Evoked Potentials by Statistical Discrimination Yasuyuki Inoue (TUT), Akitoshi Ogawa (RIKEN), Kouta Arai, Hidehiko Matsumoto (Sakushin Gakuin Univ.), Atsuhito Toyomaki (Hokkaido Univ.), Hiroshige Takeichi (RIKEN), Takashi Omori, Sachiko Koyama (Hokkaido Univ.), Takashi Morotomi (Sakushin Gakuin Univ.), Michiteru Kitazaki (TUT) NC2007-94 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
To estimate the input stimulus from observer's evoked brain potentials (ERPs), we have developed a classification technique using Principal Component Analysis (PCA) and Naive Bayes method. Our method does not require a priori knowledge about stimuli, and it is easy to apply because of its simplicity and stability. In this study, we applied the technique to classify auditory ERPs that were elicited by temporal gaps embedded in a continuous pure tone. The classifier that was constructed from ERP data elicited by long gap showed higher correct rate than that of short gap. Accuracy was significantly higher than the chance level, indicating that statistical discrimination of temporal gap stimuli was successful and would be available for quantitative feature analysis method of ERPs. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Auditory Evoked Brain Potentials / Principal Component Analysis / Naive Bayes Method / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 107, no. 413, NC2007-94, pp. 43-48, Jan. 2008. |
Paper # |
NC2007-94 |
Date of Issue |
2008-01-08 (NC) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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NC2007-94 |
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