Modeling long-term human activeness using recurrent neural networks for biometric data

BACKGROUND: With the invention of fitness trackers, it has been possible to continuously monitor a user’s biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three types of biometric data, the user’s “activeness”, an...

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Detalles Bibliográficos
Autores principales: Kim, Zae Myung, Oh, Hyungrai, Kim, Han-Gyu, Lim, Chae-Gyun, Oh, Kyo-Joong, Choi, Ho-Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5444042/
https://www.ncbi.nlm.nih.gov/pubmed/28539116
http://dx.doi.org/10.1186/s12911-017-0453-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5444042/
https://www.ncbi.nlm.nih.gov/pubmed/28539116
http://dx.doi.org/10.1186/s12911-017-0453-1

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