NDLI: Classification of obstructive and central sleep apnea using wavelet packet analysis of ECG signals

Content Provider	IEEE Xplore Digital Library
Author	Gubbi, J. Khandoker, A. Palaniswami, M.
Copyright Year	2009
Description	Author affiliation: The University of Melbourne, Victoria, Australia (Gubbi, J.; Khandoker, A.; Palaniswami, M.)
Abstract	Obstructive sleep apnea (OSA) causes a pause in air-flow with continuing breathing effort. In contrast, central sleep apnea (CSA) event is not accompanied with breathing effort. The aim of this study is to differentiate characteristics of CSA and OSA using wavelet packet analysis of ECG signal over 5 second period and support vector machines. Six patients were used in the study that contained both CSA and OSA events. Eight level wavelet packet analysis was performed on each 5 sec clip using Daubechies (DB3) mother wavelet. Two features namely the best tree and the entropy of the best wavelet tree were extracted from each clip. One patient was used for testing at a time while all other patients' data was used for training. The accuracy range was between 82% and 92% with best tree as features. Entropy of best tree resulted in improved accuracies ranging between 87% and 94.5%.
Starting Page	733
Ending Page	736
File Size	86281
Page Count	4
File Format	PDF
ISBN	9781424472819
ISSN	02766547
e-ISBN	9781424472826
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Computers in Cardiology(CinC)
Subject Keyword	Sleep apnea Wavelet analysis Wavelet packets Signal analysis Electrocardiography Entropy Support vector machines Performance analysis Data mining Testing
Content Type	Text
Resource Type	Article

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