Temporal Feature Extraction and Machine Learning for Classification of Sleep Stages Using Telemetry Polysomnography

Accurate sleep stage detection is crucial for diagnosing sleep disorders and tailoring treatment plans. Polysomnography (PSG) is considered the gold standard for sleep assessment since it captures a diverse set of physiological signals. While various studies have employed complex neural networks for...

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Detalles Bibliográficos
Autores principales: Lal, Utkarsh, Mathavu Vasanthsena, Suhas, Hoblidar, Anitha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10452545/
https://www.ncbi.nlm.nih.gov/pubmed/37626557
http://dx.doi.org/10.3390/brainsci13081201

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10452545/
https://www.ncbi.nlm.nih.gov/pubmed/37626557
http://dx.doi.org/10.3390/brainsci13081201

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