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| Titre: | Smart embedded system for sleep apnea monitoring from ECG signals |
| Auteur(s): | Ammar, Mohammed
Messaoudi, Noureddine
Faked, Djouher
Noui, Rima
Mahmoudi, Said |
| Mots-clés: | Support vector machine
Diseases and conditions
Medical diagnosis
Heart rate |
| Date de publication: | 2023 |
| Editeur: | American Institute of Physics |
| Collection/Numéro: | AIP Conference Proceedings : 2nd International Conference on Advances in Communication Technology and Computer Engineering, ICACTCE 2022, Mekne/ Vol. 2814, N° 1, Article N° 040007 |
| Résumé: | In this paper, an intelligent monitoring system was proposed to follow vital parameters such as the electrocardiogram (ECG), oxygen saturation (SPO2), the temperature of the patient, and also heart rate. The system is built around a Raspberry 3B+ and an Arduino Uno. The prototype is equipped with an intelligent system that can currently detect sleep apnea from ECG signals. These parameters are detected by the following sensors: AD8232, and MAX 30102. We have implemented and compared three algorithms: Perceproron multi-layer, Support Vector Machine, and a Random Forest Classifier. |
| URI/URL: | https://doi.org/10.1063/5.0148843
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/12912
https://pubs.aip.org/aip/acp/article-abstract/2814/1/040007/2901945/Smart-embedded-system-for-sleep-apnea-monitoring?redirectedFrom=fulltext |
| ISSN: | 0094-243X |
| Collection(s) : | Communications Internationales
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