Publication detail

EEG signal analysis based on EMD and discrete energy separation algorythm

POTOČŇÁK, T. KOZUMPLÍK, J.

Original Title

EEG signal analysis based on EMD and discrete energy separation algorythm

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper deals with spectral analysis of nocturnal EEG signal from apnoea/hypopnea pa-tients. Main goal is to employ methods independent to Fourier Transform, because of nonsta-tionary character of signal, to better description of frequency changes. For this purpose, anal-ysis based on Empirical Mode Decomposition and Discrete Energy Separation Algorithm was tested. This method is similar to commonly used Hilber Huang Transform, but can provide higher time and frequency resolution due to algorithms based on Teager-Keiser Energy Oper-ator, which can work with very short time window.

Keywords

nocturnal EEG, Empirical Mode Decomposition, Teager-Keiser Energy Operator, Discrete Energy Separation Algorithm

Authors

POTOČŇÁK, T.; KOZUMPLÍK, J.

Released

28. 4. 2016

ISBN

978-80-214-5350-0

Book

Proceedings of the 22nd Conference STUDENT EEICT 2016

Pages from

528

Pages to

532

Pages count

5

BibTex

@inproceedings{BUT128679,
  author="Tomáš {Potočňák} and Jiří {Kozumplík}",
  title="EEG signal analysis based on EMD and discrete energy separation algorythm",
  booktitle="Proceedings of the 22nd Conference STUDENT EEICT 2016",
  year="2016",
  pages="528--532",
  isbn="978-80-214-5350-0"
}