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Advisor(s)
Abstract(s)
Sleep related disorders can severely disturb the quality of sleep. Among these disorders,
obstructive sleep apnea (OSA) is highly prevalent and commonly undiagnosed. Polysomnography is
considered to be the gold standard exam for OSA diagnosis. Even though this multi-parametric test
provides highly accurate results, it is time consuming, labor-intensive, and expensive. A non-invasive
and easy to self-assemble home monitoring device was developed to address these issues. The device
can perform the OSA diagnosis at the patient’s home and a specialized technician is not required to
supervise the process. An automatic scoring algorithm was developed to examine the blood oxygen
saturation signal for a minute-by-minute OSA assessment. It was performed by analyzing statistical
and frequency-based features that were fed to a classifier. Afterward, the ratio of the number of
minutes classified as OSA to the time in bed in minutes was compared with a threshold for the global
(subject-based) OSA diagnosis. The average accuracy, sensitivity, specificity, and area under the
receiver operating characteristic curve for the minute-by-minute assessment were, respectively, 88%,
80%, 91%, and 0.86. The subject-based accuracy was 95%. The performance is in the same range as
the best state of the art methods for the models based only on the blood oxygen saturation analysis.
Therefore, the developed model has the potential to be employed in clinical analysis.
Description
Keywords
OSA Apnea SpO2 Home monitoring device . Faculdade de Ciências Exatas e da Engenharia
Citation
Mendonça, F., Mostafa, S. S., Dias, F. M., & Ravelo-García, A. G. (2020). An oximetry based wireless device for sleep apnea detection. Sensors, 20(3), 888.
Publisher
MDPI