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A Hybrid Feature Selection and Extraction Methods for Sleep Apnea Detection Using Bio-Signals
People with sleep apnea (SA) are at increased risk of having stroke and cardiovascular diseases. Polysomnography (PSG) is used to detect SA. This paper conducts feature selection from PSG signals and uses a support vector machine (SVM) to detect SA. To analyze SA, the Physionet Apnea Database was us...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436101/ https://www.ncbi.nlm.nih.gov/pubmed/32756353 http://dx.doi.org/10.3390/s20154323 |