A Neural Network System for Detection of Obstructive Sleep Apnea Through SpO2 Signal Features
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2012, Vol 3, Issue 5
Abstract
Obstructive sleep apnea (OSA) is a common disorder in which individuals stop breathing during their sleep. These episodes last 10 seconds or more and cause oxygen levels in the blood to drop. Most of sleep apnea cases are currently undiagnosed because of expenses and practicality limitations of overnight polysomnography (PSG) at sleep labs, where an expert human observer is required. New techniques for sleep apnea classification are being developed by bioengineers for most comfortable and timely detection. In this study, we develop and validate a neural network (NN) using SpO2 measurements obtained from pulse oximetry to predict OSA. The results show that the NN is useful as a predictive tool for OSA with a high performance and improved accuracy, approximately 93.3%, which is better than reported techniques in the literature.
Authors and Affiliations
Laiali Almazaydeh, Miad Faezipour, Khaled Elleithy
Keywords
Related Articles
- EP ID EP130073
- DOI -
- Views 85
- Downloads 0
The Analysis of Anticancer Drug Sensitivity of Lung Cancer Cell Lines by using Machine Learning Clustering Techniques
Lung cancer is the commonest type of cancer with the highest fatality rate worldwide. There is continued research that experiments on drug development for lung cancer patients by assessing their responses to chemotherape...
A Self-organizing Location and Mobility-Aware Route Optimization Protocol for Bluetooth Wireless
Bluetooth allows multi-hop ad-hoc networks that contain multiple interconnected piconets in a common area to form a scatternet. Routing is one of the technical issues in a scatternet because nodes can arrive and leave at...
New Deep Kernel Learning based Models for Image Classification
Deep learning system is used for solving many problems in different domains but it gives an over-fitting risk when richer representations are increased. In this paper, three different models with different deep multiple...
Urdu Sentiment Analysis
Internet is the most significant source of getting up thoughts, surveys for a product, and reviews for any type of service or activity. A Bulky amount of reviews are produced on daily basis on the cyberspace about online...
Bio-NER: Biomedical Named Entity Recognition using Rule-Based and Statistical Learners
The purpose of extracting of Bio-Medical Entities is to recognize the particular entities, whether word or phrases, from the unstructured data contained in the text. This work proposes different approaches and methods, i...