NDLI: Sleep apnea detection using wavelet analysis of ECG derived respiratory signal

Content Provider	IEEE Xplore Digital Library
Author	Avci, C. Delibasoglu, I. Akbas, A.
Copyright Year	2012
Description	Author affiliation: Department of Computer Engineering, Yalova University, Turkey (Avci, C.; Delibasoglu, I.; Akbas, A.)
Abstract	The purpose of this study is to find a reliable and practical way for detecting the minute by minute occurrence of sleep apnea. For this aim, the time series of instantaneous respiratory rates (IRR) estimated with electrocardiography (ECG) derived respiratory (EDR) signals are analyzed by using wavelet decompositions. EDR signals are derived from the two sets of single-lead ECGs by 0.2–0.8 Hz band-pass filter implementations. ECG signals are obtained from apnea-ECG database on PhysioNet databank. Wavelet decompositions are implemented to the segments of 3-minutes length time series of IRRs in which the 2nd minute is accepted as deciding minute for apnea. According to the results obtained from wavelet analysis of the first data set consisting of 35 recordings, variances of 3rd, 4th, 5th and 6th detail components can be used as discriminative features which demonstrate the minute based real time apneas. The second data set consisting of 35 recordings is used for testing this consequence. For this aim, the feature vectors derived from the first data set is used for training a nonlinear auto-regressive (NARX) type artificial neural network (ANN) classifier. Due to the minute-based assessments of overnight sleep ECGs revealed that implementation of the NARX based classification following the wavelet decompositions has success level of %82.7 and %78.3 for the first (learning) and second (test) dataset, respectively. However, due to the subject-based assessment the success level is greater than %93,33.
Starting Page	272
Ending Page	275
File Size	1078792
Page Count	4
File Format	PDF
ISBN	9781457719905
e-ISBN	9781457719912
DOI	10.1109/ICoBE.2012.6179019
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-27
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	EDR Time series analysis Artificial neural networks Electrocardiography ECG Wavelet analysis Feature extraction Sleep apnea Band pass filters
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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