EEG Signal Analysis based on EMD and Discrete Energy Separation Algorithm
Alternative metrics PlumXhttp://hdl.handle.net/11012/83989
MetadataShow full item record
This paper deals with spectral analysis of nocturnal EEG signal from apnoea/hypopnea patients. Main goal is to employ methods independent to Fourier Transform, because of nonstationary character of signal, to better description of frequency changes. For this purpose, analysis based on Empirical Mode Decomposition and Discrete Energy Separation Algorithm was tested. This method is similar to commonly used Hilbert Huang Transform, but can provide higher time and frequency resolution due to algorithms based on Teager-Keiser Energy Operator, which can work with very short time window.
Document typePeer reviewed
SourceProceedings of the 22st Conference STUDENT EEICT 2016. s. 528-532. ISBN 978-80-214-5350-0
- Student EEICT 2016