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Int. J. Environ. Res. Public Health 2019, 16(6), 931; https://doi.org/10.3390/ijerph16060931

Prediction of Physical Activity Intensity with Accelerometry in Young Children

1
Division of Integrated Sciences, J. F. Oberlin University, Tokyo 194-0294, Japan
2
Faculty of Creative Engineering, Chiba Institute of Technology, Chiba 275-0023, Japan
3
Japan Society for the Promotion of Science, Tokyo 102-0083, Japan
4
Faculty of Humanities and Social Sciences, University of Marketing and Distribution Sciences, Hyogo 651-2188, Japan
5
Waseda Institute for Sport Sciences, Waseda University, Saitama 359-1192, Japan
6
Graduate School of Media and Governance, Keio University, Kanagawa 252-0882, Japan
7
Faculty of Advanced Engineering, Chiba Institute of Technology, Chiba 275-0023, Japan
8
Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan
*
Author to whom correspondence should be addressed.
Received: 3 February 2019 / Revised: 10 March 2019 / Accepted: 11 March 2019 / Published: 15 March 2019
(This article belongs to the Collection Health Behaviors, Risk Factors, NCDs and Health Promotion)
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Abstract

Background: An algorithm for the classification of ambulatory and non-ambulatory activities using the ratio of unfiltered to filtered synthetic acceleration measured with a triaxial accelerometer and predictive models for physical activity intensity (METs) in adults and in elementary school children has been developed. The purpose of the present study was to derive predictive equations for METs with a similar algorithm in young children. Methods: Thirty-seven healthy Japanese children (four- to six-years old) participated in this study. The five non-ambulatory activities including low-intensity activities, and five ambulatory activities were selected. The raw accelerations using a triaxial accelerometer and energy expenditure by indirect calorimetry using the Douglas bag method during each activity were collected. Results: For non-ambulatory activities, especially light-intensity non-ambulatory activities, linear regression equations with a predetermined intercept (0.9) or quadratic equations were a better fit than the linear regression. The equations were different from those for adults and elementary school children. On the other hand, the ratios of unfiltered to filtered synthetic acceleration in non-ambulatory activities were different from those in ambulatory activities, as in adults and elementary school children. Conclusions: Our calibration model for young children could accurately predict intensity of physical activity including low-intensity non-ambulatory activities. View Full-Text
Keywords: triaxial accelerometer; algorithm; young children; non-ambulatory activities; ambulatory activities triaxial accelerometer; algorithm; young children; non-ambulatory activities; ambulatory activities
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Tanaka, C.; Hikihara, Y.; Ando, T.; Oshima, Y.; Usui, C.; Ohgi, Y.; Kaneda, K.; Tanaka, S. Prediction of Physical Activity Intensity with Accelerometry in Young Children. Int. J. Environ. Res. Public Health 2019, 16, 931.

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