Int J Sports Med 2013; 34(11): 975-982
DOI: 10.1055/s-0033-1337945
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

Actigraph GT3X: Validation and Determination of Physical Activity Intensity Cut Points

A. Santos-Lozano
1   Faculty of Health Science, Department of Biomedical Sciences, University of León, Spain
2   Department of Physioteraphy and Nursing, Universidad de Zaragoza, Huesca, Spain
F. Santín-Medeiros
2   Department of Physioteraphy and Nursing, Universidad de Zaragoza, Huesca, Spain
G. Cardon
3   Department of Movement and Sports Sciences, Ghent University, Gent, Belgium
G. Torres-Luque
4   Faculty of Science of Education, University of Jaén, Spain
R. Bailón
5   Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Spain
6   CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
C. Bergmeir
7   Department of Computer Science and Artificial Intelligence, E.T.S. de Ingenierías Informática y de Telecomunicación, University of Granada, Spain
J. R. Ruiz
8   Physical Education and Sport, University of Granada, Spain
A. Lucia
9   Physiology, Universidad Europea De Madrid, Spain
N. Garatachea
2   Department of Physioteraphy and Nursing, Universidad de Zaragoza, Huesca, Spain
› Author Affiliations
Further Information

Publication History

accepted after revision 13 February 2013

Publication Date:
22 May 2013 (online)


The aims of this study were: to compare energy expenditure (EE) estimated from the existing GT3X accelerometer equations and EE measured with indirect calorimetry; to define new equations for EE estimation with the GT3X in youth, adults and older people; and to define GT3X vector magnitude (VM) cut points allowing to classify PA intensity in the aforementioned age-groups. The study comprised 31 youth, 31 adults and 35 older people. Participants wore the GT3X (setup: 1-s epoch) over their right hip during 6 conditions of 10-min duration each: resting, treadmill walking/running at 3, 5, 7, and 9 km · h−1, and repeated sit-stands (30 times · min−1). The GT3X proved to be a good tool to predict EE in youth and adults (able to discriminate between the aforementioned conditions), but not in the elderly. We defined the following equations: for all age-groups combined, EE (METs)=2.7406+0.00056 · VM activity counts (counts · min−1)−0.008542 · age (years)−0.01380 ·  body mass (kg); for youth, METs=1.546618+0.000658 · VM activity counts (counts · min−1); for adults, METs=2.8323+0.00054 · VM activity counts (counts · min−1)−0.059123 · body mass (kg)+1.4410 · gender (women=1, men=2); and for the elderly, METs=2.5878+0.00047 · VM activity counts (counts · min−1)−0.6453 · gender (women=1, men=2). Activity counts derived from the VM yielded a more accurate EE estimation than those derived from the Y-axis. The GT3X represents a step forward in triaxial technology estimating EE. However, age-specific equations must be used to ensure the correct use of this device.

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