M. MacCallum
The Application of the Wavelet Transform to Polysomnographic Signals
MacCallum, M.; Almaini, A. E. A.
Authors
A. E. A. Almaini
Abstract
Polysomnographic (sleep) signals are recorded from patients exhibiting symptoms of a suspected sleep disorder such as Obstructive Sleep Apnoea (OSA). These non-stationary signals are characterised by having both quantitative information in the frequency domain and rich, dynamic data in the time domain. The collected data is subsequently analysed by skilled visual evaluation to determine whether arousals are present, an approach which is both time-consuming and subjective. This paper presents a wavelet-based methodology which seeks to alleviate some of the problems of the above method by providing: (a) an automated mechanism by which the appropriate stage of sleep for disorder observation may be extracted from the composite electroencephalograph (EEG) data set and (b) an ensuing technique to assist in the diagnosis of full arousal by correlation of wavelet-extracted information from a number of specific patient data sources (e.g. pulse oximetry, electromyogram [EMG] etc.).
Citation
MacCallum, M., & Almaini, A. E. A. (2003). The Application of the Wavelet Transform to Polysomnographic Signals. International Journal of Wavelets, Multiresolution and Information Processing, 01(03), 263-274. https://doi.org/10.1142/s0219691303000116
Journal Article Type | Article |
---|---|
Publication Date | Sep 30, 2003 |
Deposit Date | Jul 27, 2016 |
Journal | International Journal of Wavelets, Multiresolution and Information Processing |
Print ISSN | 0219-6913 |
Electronic ISSN | 1793-690X |
Publisher | World Scientific Publishing |
Peer Reviewed | Peer Reviewed |
Volume | 01 |
Issue | 03 |
Pages | 263-274 |
DOI | https://doi.org/10.1142/s0219691303000116 |
Keywords | Wavelets; sleep Apnoea; EEG, |
Public URL | http://researchrepository.napier.ac.uk/Output/317874 |
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search