Using Hidden Markov Models to Improve Quantifying Physical Activity in Accelerometer Data – A Simulation Study

INTRODUCTION: The use of accelerometers to objectively measure physical activity (PA) has become the most preferred method of choice in recent years. Traditionally, cutpoints are used to assign impulse counts recorded by the devices to sedentary and activity ranges. Here, hidden Markov models (HMM)...

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Detalles Bibliográficos
Autores principales: Witowski, Vitali, Foraita, Ronja, Pitsiladis, Yannis, Pigeot, Iris, Wirsik, Norman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4251969/
https://www.ncbi.nlm.nih.gov/pubmed/25464514
http://dx.doi.org/10.1371/journal.pone.0114089

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4251969/
https://www.ncbi.nlm.nih.gov/pubmed/25464514
http://dx.doi.org/10.1371/journal.pone.0114089

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