Depth-Camera-Based Under-Blanket Sleep Posture Classification Using Anatomical Landmark-Guided Deep Learning Model

Emerging sleep health technologies will have an impact on monitoring patients with sleep disorders. This study proposes a new deep learning model architecture that improves the under-blanket sleep posture classification accuracy by leveraging the anatomical landmark feature through an attention stra...

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Detalles Bibliográficos
Autores principales: Tam, Andy Yiu-Chau, Zha, Li-Wen, So, Bryan Pak-Hei, Lai, Derek Ka-Hei, Mao, Ye-Jiao, Lim, Hyo-Jung, Wong, Duo Wai-Chi, Cheung, James Chung-Wai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603239/
https://www.ncbi.nlm.nih.gov/pubmed/36294072
http://dx.doi.org/10.3390/ijerph192013491

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603239/
https://www.ncbi.nlm.nih.gov/pubmed/36294072
http://dx.doi.org/10.3390/ijerph192013491

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