A comparison of different machine learning algorithms, types and placements of activity monitors for physical activity classification-Reference-Cited by-同舟云学术

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A comparison of different machine learning algorithms, types and placements of activity monitors for physical activity classification

Published:2020-03 Issue: Volume:154 Page:107480
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Sheng Bo,Moosman Oscar Moroni,Del Pozo-Cruz Borja,Del Pozo-Cruz Jesus,Alfonso-Rosa Rosa Maria,Zhang Yanxin

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference52 articles.

1. Are currently available wearable devices for activity tracking and heart rate monitoring accurate, precise, and medically beneficial?;ElAmrawy;Healthc. Inform. Res.,2015

2. Assessment of energy expenditure for physical activity using a triaxial accelerometer;Bouten;Med. Sci. Sports Exerc.,1994

3. Objective measurement of physical activity and sedentary behaviour: review with new data;Reilly;Arch. Dis. Child.,2008

4. Calibration and validation of accelerometer-based activity monitors: a systematic review of machine-learning approaches;Farrahi;Gait Posture,2018

5. Physical activity classification using the GENEA wrist-worn accelerometer;Zhang;Med. Sci. Sports Exerc.,2012

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