Abstract
This chapter is devoted to one of the most interesting applications of non-parametric statistical diagnosis, namely, to the analysis of the human brain’s electrical activity (the electroencephalogram, or EEG). The meaning and the features of the EEG, as well as the problems arising from the high non-stationarity of the EEG signal, are reviewed. We present experimental results demonstrating the application of the statistical diagnosis methods described in this book to the EEG, and discuss the prospects for further development of the change-point detection methodology with the emphasis on the estimation of coupling between different signal channels.
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© 2000 Springer Science+Business Media Dordrecht
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Kaplan, A.Y., Shishkin, S.L. (2000). Application of the change-point analysis to the investigation of the brain’s electrical activity. In: Non-Parametric Statistical Diagnosis. Mathematics and Its Applications, vol 509. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9530-8_7
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DOI: https://doi.org/10.1007/978-94-015-9530-8_7
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-5465-4
Online ISBN: 978-94-015-9530-8
eBook Packages: Springer Book Archive