An Oximetry Based Wireless Device for Sleep Apnea Detection
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 a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/3/888 |
| _version_ | 1817996420191354880 |
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| author | Fábio Mendonça Sheikh Shanawaz Mostafa Fernando Morgado-Dias Antonio G. Ravelo-García |
| author_facet | Fábio Mendonça Sheikh Shanawaz Mostafa Fernando Morgado-Dias Antonio G. Ravelo-García |
| author_sort | Fábio Mendonça |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T02:21:00Z |
| format | Article |
| id | doaj.art-6628bc8114224a43b3a239630110059b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T02:21:00Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6628bc8114224a43b3a239630110059b2022-12-22T02:18:01ZengMDPI AGSensors1424-82202020-02-0120388810.3390/s20030888s20030888An Oximetry Based Wireless Device for Sleep Apnea DetectionFábio Mendonça0Sheikh Shanawaz Mostafa1Fernando Morgado-Dias2Antonio G. Ravelo-García3Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, PortugalInstituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, PortugalITI/Larsys/Madeira Interactive Technologies Institute, 9020-105 Funchal, PortugalITI/Larsys/Madeira Interactive Technologies Institute, 9020-105 Funchal, PortugalSleep 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.https://www.mdpi.com/1424-8220/20/3/888osaapneaspo2home monitoring device |
| spellingShingle | Fábio Mendonça Sheikh Shanawaz Mostafa Fernando Morgado-Dias Antonio G. Ravelo-García An Oximetry Based Wireless Device for Sleep Apnea Detection Sensors osa apnea spo2 home monitoring device |
| title | An Oximetry Based Wireless Device for Sleep Apnea Detection |
| title_full | An Oximetry Based Wireless Device for Sleep Apnea Detection |
| title_fullStr | An Oximetry Based Wireless Device for Sleep Apnea Detection |
| title_full_unstemmed | An Oximetry Based Wireless Device for Sleep Apnea Detection |
| title_short | An Oximetry Based Wireless Device for Sleep Apnea Detection |
| title_sort | oximetry based wireless device for sleep apnea detection |
| topic | osa apnea spo2 home monitoring device |
| url | https://www.mdpi.com/1424-8220/20/3/888 |
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