Машинне навчання під час діагностування і моніторингу сонного апное
This paper contains a review and analysis of applications of modern ma-chine learning approaches to solve sleep apnea severity level detection by localization of apnea episodes and prediction of the subsequent apnea episodes. We demonstrate that signals provided by cheap wearable devices can be used...
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| Datum: | 2020 |
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| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | Ukrainisch |
| Veröffentlicht: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2020
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| Schlagworte: | |
| Online Zugang: | http://journal.iasa.kpi.ua/article/view/228369 |
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| Назва журналу: | System research and information technologies |
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System research and information technologies| Zusammenfassung: | This paper contains a review and analysis of applications of modern ma-chine learning approaches to solve sleep apnea severity level detection by localization of apnea episodes and prediction of the subsequent apnea episodes. We demonstrate that signals provided by cheap wearable devices can be used to solve typical tasks of sleep apnea detection. We review major publicly available datasets that can be used for training respective deep learning models, and we analyze the usage options of these datasets. In particular, we prove that deep learning could improve the accuracy of sleep apnea classification, sleep apnea localization, and sleep apnea prediction, especially using more complex models with multimodal data from several sensors. |
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