A Review of Obstructive Sleep Apnea Detection Approaches

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F19%3A00071054" target="_blank" >RIV/00159816:_____/19:00071054 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/abstract/document/8331075/metrics#metrics" target="_blank" >https://ieeexplore.ieee.org/abstract/document/8331075/metrics#metrics</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/JBHI.2018.2823265" target="_blank" >10.1109/JBHI.2018.2823265</a>

Result language

angličtina

Original language name

A Review of Obstructive Sleep Apnea Detection Approaches

Original language description

Sleep disorders are a common health condition that can affect numerous aspects of life. Obstructive sleep apnea is one of the most common disorders and is characterized by a reduction or cessation of airflow during sleep. In many countries, this disorder is usually diagnosed in sleep laboratories, by polysomnography, which is an expensive procedure involving much effort for the patient. Multiple systems have been proposed to address this situation, including performing the examination and analysis in the patient&apos;s home, using sensors to detect physiological signals that are automatically analyzed by algorithms. However, the precision of these devices is usually not enough to provide clinical diagnosis. Therefore, the objective of this review is to analyze already existing algorithms that have not been implemented on hardware but have had their performance verified by at least one experiment that aims to detect obstructive sleep apnea to predict trends. The performance of different algorithms and methods for apnea detection through the use of different sensors (pulse oximetry, electrocardiogram, respiration, sound, and combined approaches) has been evaluated. 84 original research articles published from 2003 to 2017 with the potential to be promising diagnostic tools have been selected to cover multiple solutions. This paper could provide valuable information for those researchers who want to carry out a hardware implementation of potential signal processing algorithms.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Journal of Biomedical and Health Informatics

ISSN

2168-2194

e-ISSN

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Volume of the periodical

23

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

13

Pages from-to

825-837

UT code for WoS article

000460666400038

EID of the result in the Scopus database

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