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Items: 1 to 20 of 102

1.

Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort.

Horner F, Bilzon JL, Rayson M, Blacker S, Richmond V, Carter J, Wright A, Nevill A.

J Sports Sci. 2013;31(4):354-60. doi: 10.1080/02640414.2012.734632. Epub 2012 Nov 5.

PMID:
23121502
2.

Distributed lag and spline modeling for predicting energy expenditure from accelerometry in youth.

Choi L, Chen KY, Acra SA, Buchowski MS.

J Appl Physiol (1985). 2010 Feb;108(2):314-27. doi: 10.1152/japplphysiol.00374.2009. Epub 2009 Dec 3.

3.

Energy expenditure compared to physical activity measured by accelerometry and self-report in adolescents: a validation study.

Hallal PC, Reichert FF, Clark VL, Cordeira KL, Menezes AM, Eaton S, Ekelund U, Wells JC.

PLoS One. 2013 Nov 4;8(11):e77036. doi: 10.1371/journal.pone.0077036. eCollection 2013.

4.

Relationship between physical activity measured using accelerometers and energy expenditure measured using doubly labelled water in Indian children.

Krishnaveni GV, Veena SR, Kuriyan R, Kishore RP, Wills AK, Nalinakshi M, Kehoe S, Fall CH, Kurpad AV.

Eur J Clin Nutr. 2009 Nov;63(11):1313-9. doi: 10.1038/ejcn.2009.95. Epub 2009 Aug 19.

PMID:
19690580
5.

Validity of hip-mounted uniaxial accelerometry with heart-rate monitoring vs. triaxial accelerometry in the assessment of free-living energy expenditure in young children: the IDEFICS Validation Study.

Ojiambo R, Konstabel K, Veidebaum T, Reilly J, Verbestel V, Huybrechts I, Sioen I, Casajús JA, Moreno LA, Vicente-Rodriguez G, Bammann K, Tubic BM, Marild S, Westerterp K, Pitsiladis YP; IDEFICS Consortium.

J Appl Physiol (1985). 2012 Nov;113(10):1530-6. doi: 10.1152/japplphysiol.01290.2011. Epub 2012 Sep 20.

6.

Validation of cross-sectional time series and multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents using doubly labeled water.

Butte NF, Wong WW, Adolph AL, Puyau MR, Vohra FA, Zakeri IF.

J Nutr. 2010 Aug;140(8):1516-23. doi: 10.3945/jn.109.120162. Epub 2010 Jun 23.

7.

Wrist-worn accelerometers in assessment of energy expenditure during intensive training.

Kinnunen H, Tanskanen M, Kyröläinen H, Westerterp KR.

Physiol Meas. 2012 Nov;33(11):1841-54. doi: 10.1088/0967-3334/33/11/1841. Epub 2012 Oct 31.

PMID:
23110981
8.

The Actiheart in adolescents: a doubly labelled water validation.

Campbell N, Prapavessis H, Gray C, McGowan E, Rush E, Maddison R.

Pediatr Exerc Sci. 2012 Nov;24(4):589-602.

PMID:
23196766
9.

The use of uniaxial accelerometry for the assessment of physical-activity-related energy expenditure: a validation study against whole-body indirect calorimetry.

Kumahara H, Schutz Y, Ayabe M, Yoshioka M, Yoshitake Y, Shindo M, Ishii K, Tanaka H.

Br J Nutr. 2004 Feb;91(2):235-43.

PMID:
14756909
10.

Estimation of free-living energy expenditure using a novel activity monitor designed to minimize obtrusiveness.

Bonomi AG, Plasqui G, Goris AH, Westerterp KR.

Obesity (Silver Spring). 2010 Sep;18(9):1845-51. doi: 10.1038/oby.2010.34. Epub 2010 Feb 25.

11.

Estimation of resistance exercise energy expenditure using accelerometry.

Rawson ES, Walsh TM.

Med Sci Sports Exerc. 2010 Mar;42(3):622-8. doi: 10.1249/MSS.0b013e3181b64ef3.

PMID:
19952824
12.

Estimation of Free-Living Energy Expenditure by Heart Rate and Movement Sensing: A Doubly-Labelled Water Study.

Brage S, Westgate K, Franks PW, Stegle O, Wright A, Ekelund U, Wareham NJ.

PLoS One. 2015 Sep 8;10(9):e0137206. doi: 10.1371/journal.pone.0137206. eCollection 2015.

13.

Predicting physical activity energy expenditure using accelerometry in adults from sub-Sahara Africa.

Assah FK, Ekelund U, Brage S, Corder K, Wright A, Mbanya JC, Wareham NJ.

Obesity (Silver Spring). 2009 Aug;17(8):1588-95. doi: 10.1038/oby.2009.39. Epub 2009 Feb 26.

14.

Validation of the TracmorD triaxial accelerometer to assess physical activity in preschool children.

Sijtsma A, Schierbeek H, Goris AH, Joosten KF, van Kessel I, Corpeleijn E, Sauer PJ.

Obesity (Silver Spring). 2013 Sep;21(9):1877-83. doi: 10.1002/oby.20401. Epub 2013 Jul 2.

15.

Multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents.

Zakeri IF, Adolph AL, Puyau MR, Vohra FA, Butte NF.

J Appl Physiol (1985). 2010 Jan;108(1):128-36. doi: 10.1152/japplphysiol.00729.2009. Epub 2009 Nov 5.

16.

An investigation of a novel three-dimensional activity monitor to predict free-living energy expenditure.

Carter J, Wilkinson D, Blacker S, Rayson M, Bilzon J, Izard R, Coward A, Wright A, Nevill A, Rennie K, McCaffrey T, Livingstone B.

J Sports Sci. 2008 Apr;26(6):553-61. doi: 10.1080/02640410701708979.

PMID:
18344125
17.

Human energy expenditure in affluent societies: an analysis of 574 doubly-labelled water measurements.

Black AE, Coward WA, Cole TJ, Prentice AM.

Eur J Clin Nutr. 1996 Feb;50(2):72-92.

PMID:
8641250
18.

Estimation of daily energy expenditure in pregnant and non-pregnant women using a wrist-worn tri-axial accelerometer.

van Hees VT, Renström F, Wright A, Gradmark A, Catt M, Chen KY, Löf M, Bluck L, Pomeroy J, Wareham NJ, Ekelund U, Brage S, Franks PW.

PLoS One. 2011;6(7):e22922. doi: 10.1371/journal.pone.0022922. Epub 2011 Jul 29.

19.

Measuring free-living energy expenditure and physical activity with triaxial accelerometry.

Plasqui G, Joosen AM, Kester AD, Goris AH, Westerterp KR.

Obes Res. 2005 Aug;13(8):1363-9.

20.

Predicting doubly labeled water energy expenditure from ambulatory activity.

Tudor-Locke C, Martin CK, Brashear MM, Rood JC, Katzmarzyk PT, Johnson WD.

Appl Physiol Nutr Metab. 2012 Dec;37(6):1091-100. doi: 10.1139/h2012-097. Epub 2012 Sep 11.

PMID:
22963352

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