Abstract
Apnea is a Sleep Disorder Syndrome characterized by an interruption or reduction of air flow for at least 10 seconds. Polysomnography is a test used to apnea diagnosis. Several signals, including Electrocardiogram (ECG), Electroencephalogram (EEG) and Oxygen Saturation (SpO_2) are obtained in this diagnostic test. Since most tests for apnea are uncomfortable, there is an increase search for alternative methods to reduce cost and improve patient well-being.In this work, we use only SpO_2 data from 25 patients of the St Vincent's University Hospital, Dublin, to extract parameters connected to a Neural Network attempting to classify patients with apnea or non-apnea. Results confirm that our alternative method can be used as an auxiliary tool for diagnosis by using exclusively SpO_2 signal.
Highlights
On the past decades, the improvement in diagnosis of several diseases was ensured by the evolution of medical instrumentation and computational systems; the data volume to be processed has increased significantly [6, 11]
We focus on only one of these signals: the Oxygen Saturation Signal (SpO2) is used to evaluate apnea patterns of the data base UCDDB [22] and we use these results to compare to what is found in the literature [4, 7, 8]
Our results in this study indicate that Oxygen Saturation (SpO2) evaluation could aid in diagnosis, since it supports patients exclusion with mild or light apnea
Summary
The improvement in diagnosis of several diseases was ensured by the evolution of medical instrumentation and computational systems; the data volume to be processed has increased significantly [6, 11]. In order to deal with increasing amount of information, and to optimize data analysis, computational methods are introduced to reduce the time spent by specialists, who would normally make the diagnosis just visually, as well to try granting better results. Sleep apnea is a disease with great impacts on individuals and to the health public system, characterized by an interruption or reduction of air flow for at least 10 seconds. Some comorbidities associated with sleep apnea include: depression, heart diseases, mellitus diabetes and obesity
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
