Cargando…
Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms
Background: Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transporta...
Autores principales: | Ellis, Katherine, Godbole, Suneeta, Marshall, Simon, Lanckriet, Gert, Staudenmayer, John, Kerr, Jacqueline |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001067/ https://www.ncbi.nlm.nih.gov/pubmed/24795875 http://dx.doi.org/10.3389/fpubh.2014.00036 |
Ejemplares similares
-
Improving Hip-Worn Accelerometer Estimates of Sitting Using Machine Learning Methods
por: KERR, JACQUELINE, et al.
Publicado: (2018) -
The Relationship Between Outdoor Activity and Health in Older Adults Using GPS
por: Kerr, Jacqueline, et al.
Publicado: (2012) -
Context-Specific Outdoor Time and Physical Activity among School-Children Across Gender and Age: Using Accelerometers and GPS to Advance Methods
por: Klinker, Charlotte Demant, et al.
Publicado: (2014) -
Convergent validity of ActiGraph and Actical accelerometers for estimating physical activity in adults
por: Duncan, Scott, et al.
Publicado: (2018) -
Methods for Real-Time Prediction of the Mode of Travel Using Smartphone-Based GPS and Accelerometer Data
por: Martin, Bryan D., et al.
Publicado: (2017)