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Reseach Article

Classification of Sleep Apnea using ECG-Signal Sequency Ordered Hadamard Transform Features

by Padmavathi Kora, Ambika Annavarapu, Priyanka Yadlapalli, Nagaja Katragadda
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 156 - Number 14
Year of Publication: 2016
Authors: Padmavathi Kora, Ambika Annavarapu, Priyanka Yadlapalli, Nagaja Katragadda
10.5120/ijca2016912506

Padmavathi Kora, Ambika Annavarapu, Priyanka Yadlapalli, Nagaja Katragadda . Classification of Sleep Apnea using ECG-Signal Sequency Ordered Hadamard Transform Features. International Journal of Computer Applications. 156, 14 ( Dec 2016), 7-11. DOI=10.5120/ijca2016912506

@article{ 10.5120/ijca2016912506,
author = { Padmavathi Kora, Ambika Annavarapu, Priyanka Yadlapalli, Nagaja Katragadda },
title = { Classification of Sleep Apnea using ECG-Signal Sequency Ordered Hadamard Transform Features },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 156 },
number = { 14 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 7-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume156/number14/26784-2016912506/ },
doi = { 10.5120/ijca2016912506 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:02:35.607595+05:30
%A Padmavathi Kora
%A Ambika Annavarapu
%A Priyanka Yadlapalli
%A Nagaja Katragadda
%T Classification of Sleep Apnea using ECG-Signal Sequency Ordered Hadamard Transform Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 156
%N 14
%P 7-11
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sleep apnea is a potentially serious breath disorder. This can be detected using a test called as Polysomnography (PSG). But this method is very inconvenient because of its time consuming and expensive nature. This can be overcome by using other methods like Respiratory rate interval, ECG – derived respiration and heart rate variability analysis using Electrocardiography (ECG). These methods are used to differentiate sleep apnea affected patients and normal persons. But the major drawback of these is in performance. Hence, in this paper this disadvantage is overcome by considering Sequency Ordered Complex Hadamard Transform (SCHT) as a feature extraction technique. A minute to minute classification of thirty – five patients based on sensitivity, specificity and accuracy are 93.74%, 96.15% and 95.6%.

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Index Terms

Computer Science
Information Sciences

Keywords

ECG SCHT Sleep Apnea SVM