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Call for Papers:Vol.11 Issue.3

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Title: :  Detection of Obstructive Sleep Apnea
PaperId: :  10014
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 5 Issue 2 2019
DUI:    16.0415/IJARIIE-10014
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Akash NeelnaikAlva's Institute of Engineering and Technology
Mahalakshmi Alva's Institute of Engineering and Technology
Megha K Alva's Institute of Engineering and Technology
NamrathaAlva's Institute of Engineering and Technology
Parveez Shariff B GAlva's Institute of Engineering and Technology

Abstract

Electronics and communication engineering
Sleep apnea, Electrocardiogram (ECG), QRS complex, Support Vector Machine (SVM).
Sleep disorders are the most common health condition that can influence various aspects of life. Obstructive sleep apnea (OSA) is one of the serious sleep disorder, which causes the breathing to repeatedly start and stop during sleep. In many countries these kind of disorder is generally analyzed in sleep laboratories by the traditional detection process called Polysomnography. Most of the apnea disease are currently not analysed properly because of high cost of the test and the limitations of overnight sleep in the laboratories, where an expert human observer is needed to work over night. Multiple methods have been proposed to detect the physiological signals that are automatically analysed by different algorithms. In the proposed methodology different techniques are used for detecting the minute based analysis of OSA by Electrocardiogram (ECG) signal processing. Using the Physionet apnea ECG database, QRS complex is detected by pan Tompkins algorithm. Feature like Mean, Standard deviation and covariance is extracted from the output of the QRS complex. The classification algorithm is based on Support Vector Machines (SVM) and has been used to classify the apnea and nonapnea events from the features extracted. The software tool used for the detection of OSA is MATLAB platform. The main objective of the methodology is to detecting the OSA in a more accurate way to compute the sleep apnea score.

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IJARIIE Akash Neelnaik, Mahalakshmi , Megha K , Namratha, and Parveez Shariff B G. "Detection of Obstructive Sleep Apnea" International Journal Of Advance Research And Innovative Ideas In Education Volume 5 Issue 2 2019 Page 2243-2248
MLA Akash Neelnaik, Mahalakshmi , Megha K , Namratha, and Parveez Shariff B G. "Detection of Obstructive Sleep Apnea." International Journal Of Advance Research And Innovative Ideas In Education 5.2(2019) : 2243-2248.
APA Akash Neelnaik, Mahalakshmi , Megha K , Namratha, & Parveez Shariff B G. (2019). Detection of Obstructive Sleep Apnea. International Journal Of Advance Research And Innovative Ideas In Education, 5(2), 2243-2248.
Chicago Akash Neelnaik, Mahalakshmi , Megha K , Namratha, and Parveez Shariff B G. "Detection of Obstructive Sleep Apnea." International Journal Of Advance Research And Innovative Ideas In Education 5, no. 2 (2019) : 2243-2248.
Oxford Akash Neelnaik, Mahalakshmi , Megha K , Namratha, and Parveez Shariff B G. 'Detection of Obstructive Sleep Apnea', International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 2, 2019, p. 2243-2248. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Detection_of_Obstructive_Sleep_Apnea_ijariie10014.pdf (Accessed : ).
Harvard Akash Neelnaik, Mahalakshmi , Megha K , Namratha, and Parveez Shariff B G. (2019) 'Detection of Obstructive Sleep Apnea', International Journal Of Advance Research And Innovative Ideas In Education, 5(2), pp. 2243-2248IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Detection_of_Obstructive_Sleep_Apnea_ijariie10014.pdf (Accessed : )
IEEE Akash Neelnaik, Mahalakshmi , Megha K , Namratha, and Parveez Shariff B G, "Detection of Obstructive Sleep Apnea," International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 2, pp. 2243-2248, Mar-App 2019. [Online]. Available: https://ijariie.com/AdminUploadPdf/Detection_of_Obstructive_Sleep_Apnea_ijariie10014.pdf [Accessed : ].
Turabian Akash Neelnaik, Mahalakshmi , Megha K , Namratha, and Parveez Shariff B G. "Detection of Obstructive Sleep Apnea." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 5 number 2 ().
Vancouver Akash Neelnaik, Mahalakshmi , Megha K , Namratha, and Parveez Shariff B G. Detection of Obstructive Sleep Apnea. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2019 [Cited : ]; 5(2) : 2243-2248. Available from: https://ijariie.com/AdminUploadPdf/Detection_of_Obstructive_Sleep_Apnea_ijariie10014.pdf
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