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.
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Baranowski, J., Piątek, P., Kawala-Janik, A., Pelc, M., Anthony, R.J. (2012). Application of Kernel Density Estimators for Analysis of EEG Signals. In: Bravo, J., López-de-Ipiña, D., Moya, F. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2012. Lecture Notes in Computer Science, vol 7656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35377-2_56
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DOI: https://doi.org/10.1007/978-3-642-35377-2_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35376-5
Online ISBN: 978-3-642-35377-2
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