A Deep Learning Approach to Classify Sitting and Sleep History from Raw Accelerometry Data during Simulated Driving

Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledge of a driver’s recent sitting and sleep history could help reduce safety risks. This study aimed to apply deep learning to raw accelerometry data collected during a simulated driving task to classify...

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Detalles Bibliográficos
Autores principales: Tuckwell, Georgia A., Keal, James A., Gupta, Charlotte C., Ferguson, Sally A., Kowlessar, Jarrad D., Vincent, Grace E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460180/
https://www.ncbi.nlm.nih.gov/pubmed/36081057
http://dx.doi.org/10.3390/s22176598

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460180/
https://www.ncbi.nlm.nih.gov/pubmed/36081057
http://dx.doi.org/10.3390/s22176598

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