SAMON: Sleep apnea monitoring

Author

Burgos, Alfredo ; Goñ, Alfredo ; Illarramendi, Arantza ; Bermúdez, Jesús

Author_Institution

Fac. de Inf., Univ. of the Basque Country, Donostia, Spain

fYear

2009

fDate

1-4 Nov. 2009

Firstpage

353

Lastpage

353

Abstract

Patients suspected of suffering Sleep Apnea and Hypopnea Syndrome (SAHS) have to undergo sleep studies such as expensive polysomnographies 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. In this paper we present an alternative proposal that promotes not only a transmission of physiological data but also a real-time analysis of these data locally at a mobile device. For that, we have built a classifier that provides an accuracy of 93% and a ROC-AUC of 98.5% on SpO₂ signals available in the annotated Apnea-ECG Database.

Keywords

medical signal processing; patient diagnosis; patient monitoring; sleep; Apnea-ECG Database; Healthcare; SAMON; Sleep Apnea and Hypopnea Syndrome; polysomnography; sleep apnea monitoring; Bagging; Biomedical monitoring; Classification tree analysis; Hospitals; Medical services; Patient monitoring; Proposals; Real time systems; Sleep apnea; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine Workshop, 2009. BIBMW 2009. IEEE International Conference on

Conference_Location

Washington, DC

Print_ISBN

978-1-4244-5121-0

Type

conf

DOI

10.1109/BIBMW.2009.5332072

Filename

5332072