TY  - JOUR
A1  - Schinkel, Stefan
A1  - Marwan, Norbert
A1  - Kurths, Jürgen
T1  - Brain signal analysis based on recurrences
N2  - The EEG is one of the most commonly used tools in brain research. Though of high relevance in research, the data obtained is very noisy and nonstationary. In the present article we investigate the applicability of a nonlinear data analysis method, the recurrence quantification analysis (RQA), to Such data. The method solely rests on the natural property of recurrence which is a phenomenon inherent to complex systems, such as the brain. We show that this method is indeed suitable for the analysis of EEG data and that it might improve contemporary EEG analysis.
Y1  - 2009
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/32027
UR  - http://www.sciencedirect.com/science/journal/09284257
SN  - 0928-4257
ER  -