Application of kernel density estimators for analysis of EEG signals

Authors:
Jerzy Baranowski;Paweł Piątek;Aleksandra Kawala-Janik;Mariusz Pelc;Richard J. Anthony
Affiliations:
AGH University of Science and Technology, Krakow, Poland;AGH University of Science and Technology, Krakow, Poland;School of Computing and Mathematical Sciences, University of Greenwich, London, UK;School of Computing and Mathematical Sciences, University of Greenwich, London, UK;School of Computing and Mathematical Sciences, University of Greenwich, London, UK
Venue:
UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence
Year:
2012

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Abstract

Nowadays analysis of EEG signals is a very popular area of biomedical engineering and science for both civil and military markets. In this paper a novel analysis of EEG signal with the implementation of kernel density estimators in order to construct densitograms of the examined EEG signals was presented. This approach allows obtaining the statistically filtered signals, which enables to conduct the analysis in easier and quicker way. It is also important to mention that analysed signals were obtained from an inexpensive, easily available on the open market headset --- Emotiv EPOC. This paper also contains illustration of signal processing and justification of the chosen approach by spectral analysis.