This paper is in the following e-collection/theme issue:

Wearable Devices and Sensors (903) Fitness Trackers and Smart Pedometers/Accelerometers (571) Parent and Child Education on Physical Activity (137) Asthma Education and Self-Management in Childhood and Adolescence (71)

Published on in Vol 7, No 2 (2019): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11201, first published .
Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data

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

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

Authors of this article:

Kenan Li1 Author Orcid Image ;   Rima Habre1 Author Orcid Image ;   Huiyu Deng1 Author Orcid Image ;   Robert Urman1 Author Orcid Image ;   John Morrison1 Author Orcid Image ;   Frank D Gilliland1 Author Orcid Image ;   José Luis Ambite2 Author Orcid Image ;   Dimitris Stripelis2 Author Orcid Image ;   Yao-Yi Chiang3 Author Orcid Image ;   Yijun Lin3 Author Orcid Image ;   Alex AT Bui4 Author Orcid Image ;   Christine King5 Author Orcid Image ;   Anahita Hosseini6 Author Orcid Image ;   Eleanne Van Vliet1 Author Orcid Image ;   Majid Sarrafzadeh6 Author Orcid Image ;   Sandrah P Eckel1 Author Orcid Image
Article Authors Cited by (32) Tweetations Metrics

Journals

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  19. Hendry D, Rohl A, Rasmussen C, Zabatiero J, Cliff D, Smith S, Mackenzie J, Pattinson C, Straker L, Campbell A. Objective Measurement of Posture and Movement in Young Children Using Wearable Sensors and Customised Mathematical Approaches: A Systematic Review. Sensors 2023;23(24):9661 View
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Books/Policy Documents

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