Automatic Sleep Stage Classification Using Nasal Pressure Decoding Based on a Multi-Kernel Convolutional BiLSTM Network

• Principais autores: Minji Lee (Autor), Hyeokmook Kang (Autor), Seong-Hyun Yu (Autor), Heeseung Cho (Autor), Junhyoung Oh (Autor), Glenn van der Lande (Autor), Olivia Gosseries (Autor), Ji-Hoon Jeong (Autor)
• Formato: Livro
• Publicado em: IEEE, 2024-01-01T00:00:00Z.
• Assuntos: article
• Acesso em linha: Connect to this object online.

Sleep quality is an essential parameter of a healthy human life, while sleep disorders such as sleep apnea are abundant. In the investigation of sleep and its malfunction, the gold-standard is polysomnography, which utilizes an extensive range of variables for sleep stage classification. However, un...