Application of machine learning to predict transport modes from GPS, accelerometer, and heart rate data

BACKGROUND: There has been an increased focus on active transport, but the measurement of active transport is still difficult and error-prone. Sensor data have been used to predict active transport. While heart rate data have very rarely been considered before, this study used random forests (RF) to...

Descripción completa

Detalles Bibliográficos
Autores principales: Giri, Santosh, Brondeel, Ruben, El Aarbaoui, Tarik, Chaix, Basile
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667683/
https://www.ncbi.nlm.nih.gov/pubmed/36384535
http://dx.doi.org/10.1186/s12942-022-00319-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9667683/
https://www.ncbi.nlm.nih.gov/pubmed/36384535
http://dx.doi.org/10.1186/s12942-022-00319-y

Ejemplares similares