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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2017
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| Materias: | |
| 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 |