Detail publikace

EEG signal analysis based on EMD and discrete energy separation algorythm

Originální název

EEG signal analysis based on EMD and discrete energy separation algorythm

Anglický název

EEG signal analysis based on EMD and discrete energy separation algorythm

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

BibTex


@inproceedings{BUT128679,
  author="Tomáš {Potočňák} and Jiří {Kozumplík}",
  title="EEG signal analysis based on EMD and discrete energy separation algorythm",
  annote="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.",
  booktitle="Proceedings of the 22nd Conference STUDENT EEICT 2016",
  chapter="128679",
  howpublished="online",
  year="2016",
  month="april",
  pages="528--532",
  type="conference paper"
}