Long-Short-Term-Memory-Based Deep Stacked Sequence-to-Sequence Autoencoder for Health Prediction of Industrial Workers in Closed Environments Based on Wearable Devices

To reduce the risks and challenges faced by frontline workers in confined workspaces, accurate real-time health monitoring of their vital signs is essential for improving safety and productivity and preventing accidents. Machine-learning-based data-driven methods have shown promise in extracting val...

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Detalles Bibliográficos
Autores principales: Xu, Weidong, He, Jingke, Li, Weihua, He, Yi, Wan, Haiyang, Qin, Wu, Chen, Zhuyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535786/
https://www.ncbi.nlm.nih.gov/pubmed/37765931
http://dx.doi.org/10.3390/s23187874

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535786/
https://www.ncbi.nlm.nih.gov/pubmed/37765931
http://dx.doi.org/10.3390/s23187874

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