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APNEA Detection on Smart Phone

by Dipti Patil, V. M. Wadhai, Snehal Gujar, Karishma Surana, Prajakta Devkate, Shruti Waghmare
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 7
Year of Publication: 2012
Authors: Dipti Patil, V. M. Wadhai, Snehal Gujar, Karishma Surana, Prajakta Devkate, Shruti Waghmare
10.5120/9559-4022

Dipti Patil, V. M. Wadhai, Snehal Gujar, Karishma Surana, Prajakta Devkate, Shruti Waghmare . APNEA Detection on Smart Phone. International Journal of Computer Applications. 59, 7 ( December 2012), 15-19. DOI=10.5120/9559-4022

@article{ 10.5120/9559-4022,
author = { Dipti Patil, V. M. Wadhai, Snehal Gujar, Karishma Surana, Prajakta Devkate, Shruti Waghmare },
title = { APNEA Detection on Smart Phone },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 7 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 15-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number7/9559-4022/ },
doi = { 10.5120/9559-4022 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:03:32.636642+05:30
%A Dipti Patil
%A V. M. Wadhai
%A Snehal Gujar
%A Karishma Surana
%A Prajakta Devkate
%A Shruti Waghmare
%T APNEA Detection on Smart Phone
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 7
%P 15-19
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A flexible framework that performs real-time analysis of physiological data to monitor people's health conditions is discussed in this paper. Patients suspected of suffering sleep apnea and hypopnea syndrome (SAHS) have to undergo sleep studies such as expensive polysomnography to be diagnosed. Healthcare professionals are constantly looking for ways to improve the ease of diagnosis and comfort for this kind of patients as well as reducing both the number of sleep studies they need to undergo and the waiting times. Relating to this scenario, some research proposals and commercial products are appearing, but all of them record the physiological data of patients to portable devices and, in the morning, these data are loaded into hospital computers where physicians analyze them by making use of specialized software. The aim of this paper is to show a very accurate classifier that is able of identifying the presence of sleep apneas from blood oxygen saturation signal fragments taken from pulsioximetry systems (SpO2 & HRV) implemented on smart phone in real time.

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Index Terms

Computer Science
Information Sciences

Keywords

Real time Data stream mining signal Processing Feature Extraction

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