Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

The importance of nuance in statements about methods for human energy expenditure estimation that use motion sensors

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

References

  1. Sardinha LB, Júdice PB . Usefulness of motion sensors to estimate energy expenditure in children and adults: a narrative review of studies using DLW. Eur J Clin Nutr 2017; 71: 331–339.

    CAS  Article  Google Scholar 

  2. Rowlands AV, Yates T, Davies M, Khunti K, Edwardson CL . Raw accelerometer data analysis with GGIR R-package: does accelerometer brand matter? Med Sci Sports Exerc 2016; 48: 1935–1941.

    Article  Google Scholar 

  3. van HeesVT, Gorzelniak L, Dean LeónEC, Eder M, Pias M, Taherian S et al. Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity. PLoS ONE 2013; 8: e61691.

    Article  Google Scholar 

  4. van Hees VT, Thaler-Kall K, Wolf K-H, Brønd JC, Bonomi A, Schulze M et al. Challenges and opportunities for harmonizing research methodology: raw accelerometry. Methods Inf Med 2016; 55: 525–532.

    Article  Google Scholar 

  5. Assah FK, Ekelund U, Brage S, Wright A, Mbanya JC, Wareham NJ . Accuracy and validity of a combined heart rate and motion sensor for the measurement of free-living physical activity energy expenditure in adults in Cameroon. Int J Epidemiol 2011; 40: 112–120.

    Article  Google Scholar 

  6. Bonomi AG, Plasqui G, Goris AH, Westerterp KR . Improving the assessment of daily energy expenditure by identifying types of physical activity using a single accelerometer. J Appl Physiol 2009; 107: 655–661.

    CAS  Article  Google Scholar 

  7. van Hees VT, van Lummel RC, Westerterp KR . Estimating activity-related energy expenditure under sedentary conditions using a tri-axial seismic accelerometer. Obesity 2009; 17: 1287–1292.

    PubMed  Google Scholar 

  8. van Hees VT, Ekelund U . Novel daily energy expenditure estimation by using objective activity type classification: where do we go from here? J Appl Physiol 2009; 107: 639–640.

    Article  Google Scholar 

  9. Crouter SE, Clowers KG, Bassett DR . A novel method for using accelerometer data to predict energy expenditure. J Appl Physiol 2006; 100: 1324–1331.

    Article  Google Scholar 

  10. Plasqui G, Joosen AM, Kester AD, Goris AH, Westerterp KR . Measuring free-living energy expenditure and physical activity with triaxial accelerometry. Obes Res 2005; 13: 1363–1369.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V T van Hees.

Ethics declarations

Competing interests

The author declares no conflict of interest.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

van Hees, V. The importance of nuance in statements about methods for human energy expenditure estimation that use motion sensors. Eur J Clin Nutr 71, 1136–1137 (2017). https://doi.org/10.1038/ejcn.2017.65

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ejcn.2017.65

This article is cited by

Search

Quick links