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

Authors

  • 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
Further Information

Publication History



accepted after revision 13 February 2013

Publication Date:
22 May 2013 (online)

Abstract

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.