Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
Electrical and electronic engineering
Abstract
This paper introduces a new time-resolved spectral analysis method based on Linear Prediction Coding (LPC) method that is particularly suited to the study of the dynamics of EEG (Electroencephalogram) activity. The spectral dynamic of EEG signals can be challenging to analyse as they contain multiple frequency components and are often heavily corrupted by noise. Furthermore, the temporal and spectral resolution that can be achieved is limited by the Heisenberg-Gabor uncertainty principle [1]. The method described here is based on a z-plane analysis of the poles of the LPC which allows us to identify and estimate the frequency of the dominant spectral peaks. We demonstrate how this method can be used to track the temporal variations of the various frequency components in a noisy EEG signal.
DOI
https://doi.org/10.21427/z94d-mw11
Recommended Citation
Xu, J., Davis, M. & de Fréin, R. (2020). A Robust LPC Filtering Method for Time-Resolved Morphology of EEG Activity Analysis. 26th Annual Conference of the Section of Bioengineering of the Royal Academy of Medicine in Ireland, 17th–8th January, 2020. doi:10.21427/z94d-mw11
Funder
Science Foundation Ireland
Included in
Architectural History and Criticism Commons, Bioelectrical and Neuroengineering Commons, Other Biomedical Engineering and Bioengineering Commons, Signal Processing Commons
Publication Details
26th Annual Conference of the Section of Bioengineering of the Royal Academy of Medicine in Ireland