Abstract
Automatic Electroencephalography (EEG) interpretation system had been developed as an important tool for the inspection of brain diseases. In this study, an automatic reference selection technique was developed to obtain the appropriate derivation for EEG components interpretation. The cross spectrum of bipolar EEG was adopted to detect the phase reversal among the EEG channels covering the scalp of head. Appropriate reference was selected automatically based on the detected phase reversal. Finally, a referential derivation was constructed. The distribution of EEG components was analyzed based on the constructed referential derivation to evaluate the effectiveness of selected reference for quantitative EEG component interpretation.
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Wang, B. et al. (2010). Automatic Reference Selection for Quantitative EEG Component Interpretation: Cross Spectrum Analysis Based on Bipolar EEG. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16527-6_12
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DOI: https://doi.org/10.1007/978-3-642-16527-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16526-9
Online ISBN: 978-3-642-16527-6
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