Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data

Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data

BackgroundTime-resolved quantification of physical activity can contribute to both personalized medicine and epidemiological research studies, for example, managing and identifying triggers of asthma exacerbations. A growing number of reportedly accurate machine learning algo...

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Bibliographic Details
Main Authors: Li, Kenan, Habre, Rima, Deng, Huiyu, Urman, Robert, Morrison, John, Gilliland, Frank D, Ambite, José Luis, Stripelis, Dimitris, Chiang, Yao-Yi, Lin, Yijun, Bui, Alex AT, King, Christine, Hosseini, Anahita, Vliet, Eleanne Van, Sarrafzadeh, Majid, Eckel, Sandrah P
Format: Article
Language:English
Published: JMIR Publications 2019-02-01
Series:JMIR mHealth and uHealth
Online Access:http://mhealth.jmir.org/2019/2/e11201/

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http://mhealth.jmir.org/2019/2/e11201/

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