ECG and SpO<sub>2</sub> Signal-Based Real-Time Sleep Apnea Detection Using Feed-Forward Artificial Neural Network.
Tanmoy Paul, Omiya Hassan, Khuder Alaboud, Humayera Islam, Md Kamruz Zaman Rana, Syed K. Islam, Abu Saleh Mohammad Mosa
Abstract
-based model performed better than the ECG-based model with an accuracy of 90.78 ± 10.12% and 80.04 ± 7.7%, respectively. Once combined, these two signals complemented each other and resulted in a better model with an accuracy of 91.83 ± 1.51%.
Topics & Concepts
PolysomnographyApneaSleep apneaArtificial neural networkPattern recognition (psychology)Gold standard (test)Computer scienceArtificial intelligenceOxygen saturationMedicineCardiologyAnesthesiaInternal medicineOrganic chemistryOxygenChemistryObstructive Sleep Apnea ResearchNon-Invasive Vital Sign MonitoringEEG and Brain-Computer Interfaces